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Free Download [New] The Python Programmer Published 10/2024 Created by Shehab Abdel-Salam MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 148 Lectures ( 8h 53m ) | Size: 3.6 GB Learn Python with Hands-On Practice: 100 Exercises and Over 20 Code Challenges to Sharpen Your Skills What you'll learn You will gain practical knowledge and experience with Python programming language from fundamentals to advanced topics. Practice with 100 code exercises and over 20 code challenges with written test cases. Learn how to design and build real-world applications using Python. Learn Python's best practices and how to develop clean Python code. Learn how to apply Object-Oriented Programming and Functional Programming in Python. Requirements No programming experience needed. You will learn everything you need to know. A Mac or PC computer with internet access No paid software required. You will learn how to use the VS Code editor for writing Python programs Description Whether you're planning to work in software development, data science, data analytics, or simply want to learn programming, The Python Programmer course is designed to equip you with the expertise needed to develop Python professionally. This course is more than just theory - it's a hands-on journey through Python's core and advanced features, preparing you for real-world applications.With 15+ chapters, you'll explore everything from basic syntax to advanced topics. You'll solve 100 exercises, test your knowledge with 150+ MCQs, and optionally solve 20+ coding challenges. Each chapter is packed with practical exercises, code challenges, and quizzes that will test and solidify your understanding of Python.This course comes with customised learning journeys to help you achieve your goals efficiently. We start with programming fundamentals like data types, control flows, and data-structures, and then progress to object-oriented programming and advanced topics like decorators, generators, and concurrency. You'll also gain valuable experience by applying Python to real-world problems, ensuring you're ready for any Python-related task in your career.Whether you want to enhance your programming skills or simply learn advanced topics in Python, I've incorporated all of my knowledge and experience into this course to ensure it provides the tools and confidence you need to succeed. I hope you enjoy this course and get the best experience out of this journey!Shehab Who this course is for First-time learners who want to learn programming in Python. Beginner Python developers who want to practice and advance their Python knowledge and skills. Homepage https://www.udemy.com/course/the-python-programmer/ Screenshot Rapidgator https://rg.to/file/051e414b9433f820c5e51dd998f01eb6/iicsk.New.The.Python.Programmer.part4.rar.html https://rg.to/file/3d93501f18f80fa0b650f367d3f9b699/iicsk.New.The.Python.Programmer.part1.rar.html https://rg.to/file/951401c58a8fd01a719bb4bf5b539b50/iicsk.New.The.Python.Programmer.part3.rar.html https://rg.to/file/bdd216e20dfb268a160e04a631b12bba/iicsk.New.The.Python.Programmer.part2.rar.html Fikper Free Download https://fikper.com/1Na9lUdPrk/iicsk.New.The.Python.Programmer.part3.rar.html https://fikper.com/W94IdkV3Hp/iicsk.New.The.Python.Programmer.part2.rar.html https://fikper.com/dWjUHdek3H/iicsk.New.The.Python.Programmer.part4.rar.html https://fikper.com/mSmfM7JGaY/iicsk.New.The.Python.Programmer.part1.rar.html No Password - Links are Interchangeable

Free Download Weekend Python Crash Course From Zero to Code Published 10/2024 Created by Manan Khaneja MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 8 Lectures ( 3h 13m ) | Size: 2.8 GB Get hands-on with the fundamentals: From basic syntax to appying object-oriented principles in just two days What you'll learn Understand the basic syntax and structure of Python programs. Learn how to work with variables, data types, and operators in Python. Master the use of control flow structures like loops and conditionals. Get hands-on experience with functions and basic input/output operations in Python. Requirements No programming experience required; this course starts with the basics and focuses on fundamental concepts, including object-oriented programming. Description Welcome to the "Weekend Python Crash Course: From Zero to Code"! This beginner-friendly course is designed to take you from having no programming experience to confidently writing Python code in just two days. Whether you're looking to enhance your skill set for career opportunities or dive into programming for personal projects, this course will provide you with a strong foundation in Python.We'll begin by getting your environment set up, followed by an introduction to why Python is one of the most popular programming languages today. You'll learn Python's core syntax and keywords, which form the backbone of any Python program. From there, we'll dive into variables, data types, and simple operations, which are essential for performing tasks within your programs.As the course progresses, we'll cover control structures, including conditionals and loops, to help you create more dynamic programs. You'll then move on to functions and modules, where you'll learn to organize your code into reusable blocks. By the end of the course, you'll understand the basics of object-oriented programming (OOP) through classes and objects-critical concepts for building complex, real-world applications.Throughout the course, you'll be challenged with quizzes and hands-on coding assignments to test your knowledge and solidify your learning. We'll wrap up with file handling and I/O operations, enabling you to interact with external files and data.By the end of this weekend course, you'll have the confidence and skills to continue your Python coding journey. Who this course is for This course is for beginners who want to learn Python from scratch, individuals with no prior programming experience, or those looking to strengthen their understanding of Python's fundamental concepts and object-oriented programming. It's perfect for anyone interested in quickly getting started with Python over a weekend. Homepage https://www.udemy.com/course/weekend-python-crash-course-from-zero-to-code/ Screenshot Rapidgator https://rg.to/file/a1f6a3a115c495600e4789e0f943546a/cocoo.Weekend.Python.Crash.Course.From.Zero.to.Code.part3.rar.html https://rg.to/file/c8d6fb9d7258d26c88f8c70a9bf1029a/cocoo.Weekend.Python.Crash.Course.From.Zero.to.Code.part2.rar.html https://rg.to/file/d0caae19e4a78608ca2caebd26b16cb6/cocoo.Weekend.Python.Crash.Course.From.Zero.to.Code.part1.rar.html Fikper Free Download https://fikper.com/421SUwUykZ/cocoo.Weekend.Python.Crash.Course.From.Zero.to.Code.part1.rar.html https://fikper.com/cWOhtYMpT1/cocoo.Weekend.Python.Crash.Course.From.Zero.to.Code.part2.rar.html https://fikper.com/mfQcWOFHre/cocoo.Weekend.Python.Crash.Course.From.Zero.to.Code.part3.rar.html No Password - Links are Interchangeable

Free Download Udemy - The Complete Python Microservices Published 10/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 942.54 MB | Duration: 0h 56m You will learn the best practices of Python Microservices and learn how to build Python Microservices! What you'll learn Learn everything about Python Microservices Learn how to build the Python Microservices Learn python development, deployment, scaling, and management Learn Python and best practices of Python microservices Requirements You need to be interested in learning Python Microservices Description Python Microservices are an architectural style that structures an application as a collection of loosely coupled services, each of which represents a specific business capability. In Python, microservices have gained popularity due to the language's simplicity, readability, and vast ecosystem of libraries. Each microservice operates independently and communicates with other services over a network, typically through HTTP or messaging protocols. Python has libraries such as Prometheus for monitoring and OpenTelemetry for tracing, which help developers track the health and performance of their services.Python microservices architecture, each service is developed, deployed, and maintained independently. This isolation allows teams to work on different services without worrying about breaking other parts of the system. The microservices paradigm contrasts with monolithic applications, where all functionality is built into a single, large codebase. One key advantage of microservices is scalability. Services can be scaled individually based on their specific load requirements rather than scaling the entire application, as is often necessary with monoliths. Flask and FastAPI are two popular lightweight web frameworks used to build RESTful APIs for microservices. Python's simplicity, wide library support, and ease of integration with modern cloud-native tools make it an excellent choice for building microservices architectures. Python supports several methods, including synchronous HTTP requests and asynchronous message queues like RabbitMQ and Kafka. Overview Section 1: Introduction Lecture 1 Introduction Lecture 2 Data Visualization and Chats in Python Microservices Lecture 3 Methods in programming language Lecture 4 Matplotlib in Python Microservices Lecture 5 Pandas Dataframe in Python Microservices Lecture 6 Python lists to Nampy in Python Microservices Lecture 7 Operating on Nampy arrays in Python Microservices Lecture 8 Retrieving data frim a data frame This course is for those wanting to learn Python Microservices Screenshot Homepage https://www.udemy.com/course/the-complete-python-microservices/ Rapidgator https://rg.to/file/9935aa8d57b1c3c7daf05b967cce9f67/vgdgp.The.Complete.Python.Microservices.rar.html Fikper Free Download https://fikper.com/A7336vbz7E/vgdgp.The.Complete.Python.Microservices.rar.html No Password - Links are Interchangeable

Free Download Udemy - Python 101 - The Basics Published 10/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.03 GB | Duration: 3h 0m Python Programming for Beginners: From Basics to Beyond Unlock the world of programming with our comprehensive Python c What you'll learn Learn how to install Python and run scripts effectively Master the basics and core concepts of Python programming Develop a clear understanding of programming logic Be prepared to create small and simple applications Build confidence in your ability to program independently Requirements There are no prerequisites except for a working computer. We'll cover how to install Python for both Windows and Linux users. Description Python Programming for Beginners: From Basics to BeyondUnlock the world of programming with our comprehensive Python course! Whether you're a complete novice or looking to sharpen your skills, this class is designed to take you from the fundamentals to more advanced concepts in a fun and engaging way.What You'll Learn:- Foundational Concepts: Understand the basics of Python, including data types (strings, integers, and floats), variables, and how to use the `print()` and `input()` functions.- Control Flow: Master the use of conditional statements (`if`, `elif`, and `else`) and loops (`for` and `while`) to create dynamic programs that respond to user input.- Data Structures: Explore essential data structures like lists, tuples, and dictionaries, and learn how to manipulate and store data efficiently.- Functions: Discover how to write reusable code with functions, including how to define parameters and return values for maximum efficiency.- Error Handling: Learn how to anti[beeep]te and manage errors in your code using try-except blocks, ensuring your programs run smoothly.Course Features:- Hands-On Projects: Apply your knowledge through practical projects that reinforce learning and boost your confidence in coding.- Interactive Lessons: Enjoy engaging lectures with clear explanations and real-world examples that make complex concepts easy to understand.- Supportive Community: Join a vibrant community of learners where you can ask questions, share ideas, and collaborate on coding challenges.Who This Course Is For:- Absolute beginners with no prior programming experience.- Anyone looking to build a solid foundation in Python programming for further learning or career advancement.Enroll today and embark on your journey to becoming a proficient Python programmer! Let's code your future together! Overview Section 1: Lesson 1: Setting things up Lecture 1 Installing Python and an IDE Section 2: Lesson 2 Lecture 2 Print(), Input(), Variables Introduction, and Running Scripts Section 3: Lesson 3 Lecture 3 Types and Variables Explained Section 4: Lesson 4 Lecture 4 If, Elif, Else, Booleans, and Conditions Section 5: Lesson 5 Lecture 5 For and While Loops Section 6: Lesson 6 Lecture 6 Totally Not Rigged Guess the Number Game Section 7: Lesson 7 Lecture 7 Error Handling: Try, Except, Finally, and Exceptions Section 8: Lesson 8 Lecture 8 Lists introduction and Debugging Crisis! Lecture 9 Why it didn't work This course is intended for anyone interested in learning Python programming Screenshot Homepage https://www.udemy.com/course/python-101-the-basics/ Rapidgator https://rg.to/file/3d33c35ab79cd0f2ade15a20d124278a/smixm.Python.101..The.Basics.part1.rar.html https://rg.to/file/b905b3dc95b1b66957b2cc9a27d60f1c/smixm.Python.101..The.Basics.part2.rar.html Fikper Free Download https://fikper.com/IjGFSE2ynh/smixm.Python.101..The.Basics.part2.rar.html https://fikper.com/iErdpxRsy6/smixm.Python.101..The.Basics.part1.rar.html No Password - Links are Interchangeable

Free Download Udemy - Oops In Python Published 10/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 4.17 GB | Duration: 4h 43m Mastering Object-Oriented Programming in Python: From Fundamentals to Advanced Design Patterns What you'll learnCore OOP Concepts: Classes, Objects, Methods Inheritance: Create class hierarchies Polymorphism: Implement flexible behaviors Encapsulation & Abstraction: Hide details Magic Methods: Customize class operations Multiple Inheritance: Use complex class structures Design Patterns: Clean and maintainable code Dynamic Classes: Modify classes at runtime Real-World Projects: Practical OOP applications Debug & Optimize: Improve performance and code RequirementsBasic Python Programming Knowledge Understanding of Data Types & Variables Familiarity with Functions and Loops Experience with Python Syntax and IDEs Problem-Solving and Logical Thinking Basic Knowledge of File Handling in Python Willingness to Learn OOP Concepts Access to a Computer with Python Installed DescriptionThis course is designed to provide a comprehensive understanding of Object-Oriented Programming (OOP) in Python, focusing on building efficient, scalable, and reusable software components. It covers fundamental concepts such as classes, objects, inheritance, polymorphism, encapsulation, and abstraction, while also exploring advanced topics like magic methods, multiple inheritance, and dynamic class modifications.Throughout the course, parti[beeep]nts will start by learning the basics of OOP and progress to more complex aspects, including the implementation of design patterns that promote code modularity and maintainability. Each module includes hands-on coding exercises and real-world projects to reinforce key concepts, ensuring that learners can apply their knowledge in practical scenarios. Additionally, the course emphasizes best practices for structuring OOP code, debugging techniques, and performance optimization.By the end of the program, students will have mastered the skills needed to develop complex applications and implement sophisticated OOP designs in Python. The curriculum is designed for both beginners who want to build a strong foundation in Python programming and experienced developers looking to enhance their understanding of software architecture. Upon completion, learners will have the confidence to apply OOP principles in a variety of software development environments, making this course ideal for anyone aiming to elevate their Python programming skills and pursue roles in software engineering or design.With a focus on practical learning and real-world applications, this course is the perfect stepping stone for mastering OOP in Python and building a solid foundation for future software development projects. OverviewSection 1: Advance Python (OOP) Lecture 1 Introduction to Object Oriented Programming (OOP) in Python Lecture 2 Class vs Object in OOP Lecture 3 Writing our first Class in OOP Lecture 4 Methods vs Functions Lecture 5 Class Diagram in OOP Lecture 6 Magic Methods/Dunder Methods in OOP Lecture 7 Concept of self in OOP Lecture 8 How object access attributes in OOP Lecture 9 Reference Variable in OOP Lecture 10 Pass by reference in OOP Lecture 11 Mutibility of Object in OOP Lecture 12 What is instance variable in OOP Lecture 13 Encapsulation in OOP Lecture 14 getter & setter methods in OOP Lecture 15 Collection of class objects in OOP Lecture 16 Static Variables & Methods in OOP Lecture 17 Aggregation in OOP Lecture 18 Aggregation class diagram in OOP Lecture 19 Inheritance in OOP Lecture 20 Inheritance class diagram in OOP Lecture 21 What gets Inherited Lecture 22 Method Overriding in OOP Lecture 23 Super Keyword in OOP Lecture 24 Types of Inheritance in OOP Lecture 25 Polymorphism in OOP Lecture 26 Abstraction in OOP Section 2: Moduler Coding in Python Lecture 27 Moduler Coding in Python Lecture 28 if __name__ == "__main__" in Python Section 3: Mega OOP Project Lecture 29 Mega OOP Project Lecture 30 Conclusion & Future Advice Beginner Python Programmers seeking to learn OOP concepts.,Experienced Developers wanting to deepen OOP skills.,Students looking to enhance their programming foundations.,Software Engineers aiming to improve code modularity.,Data Scientists wanting to build reusable data models.,Tech Enthusiasts interested in software design principles.,Freelancers needing to write scalable applications.,Career Switchers exploring software development roles. 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Free Download Udemy - Efficient Coding in Python Published 10/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 14h 12m | Size: 5.48 GB Efficient Coding in Python What you'll learn Gain proficiency in using various Python Integrated Development Environments for efficient coding. Understand the basics of Python programming, including data types, formatting, and control structures. Learn about functions, recursion, regular expressions, and data structures. Explore the powerful NumPy library for numerical computations and data manipulation. Develop skills in web scraping with Python and interact with databases using PyMySQL. Requirements Basic Understanding of Programming A keen interest in learning Python programming and improving coding efficiency. Who is this course for? Description Welcome to the Efficient Coding in Python course! This comprehensive program is designed to equip you with essential skills and techniques to write efficient, effective, and elegant Python code. Whether you're new to Python or looking to enhance your coding practices, this course covers everything needed to build, optimize, and streamline your Python coding skills for various applications.Throughout the course, you will explore a wide range of Python programming concepts, emphasizing practical applications and best practices. You'll begin by familiarizing yourself with Python Integrated Development Environments (IDEs) and the fundamentals of programming. The course covers crucial topics such as data types, formatting, conditional statements, loops, functions, recursion, and regular expressions. You'll also dive into data structures, arrays, and explore the powerful NumPy library for numerical computing. In addition, this course covers advanced topics such as web scraping and interacting with databases using PyMySQL.By the end of this course, you will be proficient in writing clean, optimized, and efficient Python code. You will be able to tackle complex problems with confidence and apply Python skills to real-world scenarios. Get ready to unlock limitless opportunities and elevate your programming capabilities with Python, positioning yourself for success in various technology-driven fields! Who this course is for Aspiring Python developers Software engineers and developers Data scientists and analysts Students and beginners IT professionals Freelancers and consultants Entrepreneurs Anyone interested in learning Python to apply in real-world scenarios across different industries. Homepage https://www.udemy.com/course/efficient-coding-in-python/ Rapidgator https://rg.to/file/029710a16146095b361d92ec2d413a9b/xosfa.Efficient.Coding.in.Python.part1.rar.html https://rg.to/file/2e2e093aeb28624c9647a5e780371a3f/xosfa.Efficient.Coding.in.Python.part6.rar.html https://rg.to/file/6e527e2b16c06fb8fc0cc355278f4d27/xosfa.Efficient.Coding.in.Python.part5.rar.html https://rg.to/file/8fe046f69f140b9d960dd91a29c22c2a/xosfa.Efficient.Coding.in.Python.part3.rar.html https://rg.to/file/a2b1b5deb0b81c4e90e2e149fc3fd4d1/xosfa.Efficient.Coding.in.Python.part4.rar.html https://rg.to/file/f375d224308c9c6b0df40fc17b2b432c/xosfa.Efficient.Coding.in.Python.part2.rar.html Fikper Free Download https://fikper.com/3v1ecZN7y9/xosfa.Efficient.Coding.in.Python.part6.rar.html https://fikper.com/4WLaXC7xOM/xosfa.Efficient.Coding.in.Python.part5.rar.html https://fikper.com/CHsUOCVl9h/xosfa.Efficient.Coding.in.Python.part4.rar.html https://fikper.com/bMxW4wGjYn/xosfa.Efficient.Coding.in.Python.part1.rar.html https://fikper.com/tDEvlWVUKp/xosfa.Efficient.Coding.in.Python.part3.rar.html https://fikper.com/zZFq6MTMwh/xosfa.Efficient.Coding.in.Python.part2.rar.html No Password - Links are Interchangeable

Free Download The Ultimate Python Data Visualization Course- Step By Step Published 10/2024 Created by Click Learning MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 28 Lectures ( 4h 34m ) | Size: 1.61 GB Master Data Visualization with Python: A Complete Step-by-Step Guide to Unlocking the Power of Your Data What you'll learn Introduction to Python for Data Visualization Installing Required Libraries (Matplotlib, Seaborn, Plotly, etc.) Basic Plotting: Line Plots, Scatter Plots, and Bar Charts Customizing Plots: Titles, Labels, and Legends Creating Subplots for Multiple Charts Adding Annotations and Text to Plots Saving and Exporting Charts for Different Formats Customizing Aesthetics with Seaborn Themes and Styles Creating Pair Plots, Heatmaps, and Violin Plots Visualizing Relationships with Seaborn (Categorical, Linear, and Non-linear) Creating Interactive Line, Bar, and Scatter Plots Building Interactive Dashboards with Plotly Dash Visualizing Time Series Data Optimizing Performance for Large Data Visualizations Principles of Effective Data Storytelling Using Color Effectively in Data Visualizations Requirements No Prior Experience Required Description Unlock the power of your data with 'The Ultimate Python Data Visualization Course- Step By Step.' This comprehensive course is designed to take you from a beginner to an expert in Python data visualization. You'll learn how to create stunning and informative visuals that communicate your data's story effectively.Starting with the basics, you'll delve into Python's powerful libraries like Matplotlib, Seaborn, and Plotly. Each section of the course builds on the previous one, ensuring a solid understanding of core concepts before moving on to more advanced techniques. You'll work on real-world projects and practical examples that bring theory to life and equip you with skills you can apply immediately.This Course Include:Introduction to Data VisualizationIntroduction to Python for Data VisualizationThe Importance of Data Visualization and TypessInstalling Required Libraries (Matplotlib, Seaborn, Plotly, etc.)Getting Started with MatplotlibBasic Plotting: Line Plots, Scatter Plots, and Bar ChartsCustomizing Plots: Titles, Labels, and LegendsWorking with Colors, Markers, and Line StylesCreating Subplots for Multiple ChartsAdvanced Matplotlib TechniquesCustomizing Plot Axes and TicksAdding Annotations and Text to PlotsCreating Histograms and Density PlotsWorking with 3D Plots in MatplotlibSaving and Exporting Charts for Different FormatsData Visualization with SeabornCreating Pair Plots, Heatmaps, and Violin PlotsCustomizing Aesthetics with Seaborn Themes and StylesVisualizing Relationships with Seaborn (Categorical, Linear, and Non-linear)Interactive Visualizations with PlotlyCreating Interactive Line, Bar, and Scatter PlotsVisualizing Geospatial Data with PlotlyBuilding Interactive Dashboards with Plotly DashVisualizing Data with Pandas and Other LibrariesUsing Pandas for Quick Data VisualizationVisualizing Time Series DataData Visualization with Altair and BokehCreating Interactive Visualizations with AltairVisualizing Large DatasetsWorking with Big Data: Challenges and StrategiesVisualizing Data with Dask and VaexOptimizing Performance for Large Data VisualizationsVisual Storytelling and Design PrinciplesPrinciples of Effective Data StorytellingUsing Color Effectively in Data VisualizationsTypography and Layout for Enhanced ClarityDesigned for data analysts, business professionals, and aspiring data scientists, this course provides the tools to make data-driven decisions with confidence. Unlock your data's potential with this comprehensive, step-by-step guide and become a visualization expert.Enroll now in this transformative journey and start making your data speak volumes! Who this course is for Anyone interested in Python programming, Python scripting, machine learning, data science and data visualization. Those who are interested to learn data science or data visualization application. Homepage https://www.udemy.com/course/the-ultimate-python-data-visualization-course-step-by-step/ Screenshot Rapidgator https://rg.to/file/783f9c110dcde69cf132342f3a221ea7/ewjek.The.Ultimate.Python.Data.Visualization.Course.Step.By.Step.part1.rar.html https://rg.to/file/edaa199bbd8532f73322222a990ffd74/ewjek.The.Ultimate.Python.Data.Visualization.Course.Step.By.Step.part2.rar.html Fikper Free Download https://fikper.com/8CpWwNFahM/ewjek.The.Ultimate.Python.Data.Visualization.Course.Step.By.Step.part1.rar.html https://fikper.com/QWUmkdlzrZ/ewjek.The.Ultimate.Python.Data.Visualization.Course.Step.By.Step.part2.rar.html No Password - Links are Interchangeable

Free Download The Ultimate Beginners Guide to Python NumPy Published 10/2024 Created by Jones Granatyr,Denny Ceccon MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 75 Lectures ( 7h 46m ) | Size: 2.8 GB Master everything you need to know about NumPy for numerical analysis and scientific calculations! Solved exercises! What you'll learn Strengthen your Python knowledge and enhance your programming skills to work with NumPy arrays in your projects. Explore the powerful nature of NumPy arrays and their essential attributes for efficient data manipulation. Create, populate, and navigate NumPy arrays, extracting and modifying data seamlessly. Use methods and functions to perform complex operations on your arrays, optimizing your code and leveraging the full potential of NumPy. Dive into fundamental data science concepts, learning to manipulate and analyze data effectively. Requirements Basic programming logic and Python programming, although it's possible to follow the course without deep knowledge in these areas. Description This course is designed for Python developers who want to explore the powerful features of the NumPy library. Through hands-on lessons, you will acquire the skills needed to work with multidimensional arrays, perform complex scientific calculations, and manipulate data efficiently.We will cover the following topics:ndarrays (the fundamental class of NumPy) and their attributes:Create and manipulate multidimensional arrays with the `ndarray` class Explore the essential attributes of `ndarrays` Learn array indexing and slicing techniques, and value assignment Understand the different ways to create populated arrays ndarray methods:Extract attributes and perform mathematical operations on arrays Use `ndarray` methods to efficiently manipulate data Array manipulation:Use array manipulation functions to modify and transform data Combine arrays in different ways to create more complex datasets Learn how to transpose, reorder, and invert arrays Explore advanced indexing techniques to extract specific information from arrays Powerful NumPy functions for analysis:Use linear algebra functions to solve systems of equations, compute inverse matrices, and more Apply statistical functions to analyze data, calculate measures of central tendency and dispersion Master NumPy universal functions to perform mathematical operations on arrays And more:Generate random numbers with different probability distributions Discover useful NumPy constants for scientific calculations Save and load arrays for data persistence By the end of this course, you will confidently use the NumPy library for numerical analysis in Python, work efficiently with multidimensional arrays, perform complex scientific calculations on arrays with precision and speed, manipulate data efficiently to extract valuable insights, and integrate the NumPy library into your existing Python development projects. With over 7 hours of step-by-step videos and solved exercises at the end of each section! Who this course is for Python developers interested in learning how to optimize operations involving vector and matrix calculations. Data Science students seeking essential knowledge in one of the key libraries for data manipulation and analysis in Python. Data Science professionals looking to deepen their understanding of the main concepts and functionalities of one of the most commonly used libraries in their daily work. Homepage https://www.udemy.com/course/the-ultimate-beginners-guide-to-python-numpy/ Welcome to Check it Every Days Rapidgator https://rg.to/file/42fa46ffdca20f93a261e64e984a9531/nfvya.The.Ultimate.Beginners.Guide.to.Python.NumPy.part2.rar.html https://rg.to/file/97b92a64781415766f5de0c9edb18d22/nfvya.The.Ultimate.Beginners.Guide.to.Python.NumPy.part1.rar.html https://rg.to/file/ca1b0115a5939c9d21d76bf2076452af/nfvya.The.Ultimate.Beginners.Guide.to.Python.NumPy.part3.rar.html Fikper Free Download https://fikper.com/aX8bAAM4aK/nfvya.The.Ultimate.Beginners.Guide.to.Python.NumPy.part1.rar.html https://fikper.com/nMoGOm2vU7/nfvya.The.Ultimate.Beginners.Guide.to.Python.NumPy.part3.rar.html https://fikper.com/olaeEsJFO1/nfvya.The.Ultimate.Beginners.Guide.to.Python.NumPy.part2.rar.html No Password - Links are Interchangeable

Free Download The Speedrun Python Unit Testing Course (unittest, mock) Published 10/2024 Created by Yurii Rohoza MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 17 Lectures ( 1h 11m ) | Size: 475 MB Let's make bug-free applications using tests! What you'll learn Write Unit Test Cases Run Test Cases Execution of test collections Develop Test Suites Use Unit Test Fixtures Mocking of functions and objects Organize test code Requirements Python Programming Fundamentals IDE Environment - Basic Familiarity Description In this course is that we're gonna learn how to test applications with python unittest framework.Unit Testing is the first level of software testing where the smallest testable parts of softwareare tested. This is used to validate that each software unit performs as designed.The unittest test framework is Python xUnit style framework. In this article, we will learn about unittest framework with the help of examples.You're gonna learn the basics concepts of applications testing such as:Individual unit of testingMake preparations and sharing test data by using test fixturesTest code organizationTest grouping using TestSuiteTest skippingExecution of test collectionsMocking of objects and functionsUsing mock decorators for objects patchingYou'll also learn how to use mock objects. Mocking Test is a technique or methodused in testing within the scope of software testing by replacing theoriginal object (dependent object) with a mock object. The mock object created can simulate the behavior of the dependent object thatis temporarily replaced. Testing in mock testing focuses on the unit being testedwithout involving or depending on other units by isolating the object to be tested.All source code for each video is available for download. Who this course is for Python Programmers Python Automation Engineers Homepage https://www.udemy.com/course/the-speedrun-python-unit-testing-course-unittest-mock/ Screenshot Rapidgator https://rg.to/file/d956d523eeb9f40c74f4f138defc4f33/ygnmy.The.Speedrun.Python.Unit.Testing.Course.unittest.mock.rar.html Fikper Free Download https://fikper.com/h65As1eJkk/ygnmy.The.Speedrun.Python.Unit.Testing.Course.unittest.mock.rar.html No Password - Links are Interchangeable

Free Download Siemens NX - Advanced Python topics Published 10/2024 Created by Frederik Vanhee MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 7 Lectures ( 44m ) | Size: 405 MB ONLY for EXPERIENCED developers with in depth knowledge of NXOPEN and Python What you'll learn Setup and use NX with external Python interpreter Use the nxopentse Python package Debugging NXOpen using Python Creating UI's using Python - to be added in the future HTTP requests within NXOpen - to be added in the future Requirements Experienced NXOpen user Experienced Python user Knowlege of pip and Python packages Description This course consists of a collection of loose topics covering advanced NXOpen concepts in Python. This course is only for seasoned developers which have already a lot of experience using NXOpen AND Python.The first section contains step by step instructions on how to point NX or Simcenter to the external python interpreter. Once this is done, you can start using external packages like nxopentse or numpy, and unlock the full potential of Python within your NX or Simcenter environment.The second section is a short demonstration of nxopentse, showing some of the functionality of this package and the power of working together on a code base.I'm building a community of NXOpen developers using Python. By working together we can leverage the power of the community and experts to create a fantastic library of NXOpen Python functions. This library is nxopentse and is open source, so it is free for everyone to use.Whether you are a seasoned developer, or taking your first steps, your help is welcome. You can contribute by adding code, testing, giving feedback,...Just like the African proverb goes: "If you want to go fast, go alone, if you want to go far, go toghether", we can go much further if we work together and join forces on the code in nxopentse. I hope to be able to build a community of NXOpen Python developers which becomes the reference go to place for NXOpen in Python.The third section will show the benefits of using nxopentse in Simcenter3D to non Python users. This is closely linked to my "Simcenter3D basic NXOpen course (C#)" (still to be completed)The fourth section shows how to get debugging to work with NXOpen journals.The fifth section (still to be completed) will show how to create windows using tKinterThe sixth section (still to be completed) will show how to performhttp requests from within NX. Who this course is for NXOpen developers with significant experience using Python Homepage https://www.udemy.com/course/siemens-nx-advanced-python-topics/ Screenshot Rapidgator https://rg.to/file/21ba748133fa3fb7bbca8b1516ab3d23/qfxus.Siemens.NX..Advanced.Python.topics.rar.html Fikper Free Download https://fikper.com/fz8D6IslB5/qfxus.Siemens.NX..Advanced.Python.topics.rar.html No Password - Links are Interchangeable

Free Download Python Programming Mastery From Beginner to Pro Published 10/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 1h 8m | Size: 621 MB Python Pro: Master Programming and Problem-Solving Skills What you'll learn Understand and apply fundamental Python concepts, including variables, data types, operators, and control structures. Gain the ability to solve real-world problems by writing efficient, reusable Python code. Learn to leverage Python's standard libraries and external packages to streamline data manipulation, web development, and automation tasks. pply Python skills in hands-on projects, such as building applications, automating tasks, and analyzing data, to reinforce learning and demonstrate proficiency. Requirements No prior experience is needed Description Unlock the Power of Python - From Beginner to ProWelcome to Python Programming Mastery: From Beginner to Pro! This course is designed to take you on a comprehensive journey from Python basics to advanced programming techniques. Whether you're starting fresh or looking to sharpen your skills, this course equips you with the tools, techniques, and problem-solving abilities needed to excel in Python programming.What You'll Learn:Foundational Python Concepts: Master variables, data types, control structures, and functions.Advanced Techniques: Dive into object-oriented programming, modules, and libraries to elevate your skills.Real-World Applications: Tackle hands-on projects to solidify your understanding, including data analysis, web scraping, and automation.Problem-Solving Essentials: Develop critical problem-solving skills and learn to write clean, efficient code.By the end of this course, you'll not only understand Python's core principles but also have the confidence to apply them in diverse fields like data science, web development, and automation. Our engaging lessons, comprehensive exercises, and real-world challenges ensure you're prepared to confidently build applications, automate workflows, analyze data, develop complex algorithms, and even launch your own innovative projects. Join us to become a Python Pro, equipped with highly marketable, in-demand skills for today's tech-driven world! So what are you waiting for? Who this course is for Beginner Python Developers Homepage https://www.udemy.com/course/python-programming-mastery-from-beginner-to-pro/ Screenshot Rapidgator https://rg.to/file/1eda6d22e84de008e21add01ccdc3d4e/wjubb.Python.Programming.Mastery.From.Beginner.to.Pro.rar.html Fikper Free Download https://fikper.com/bWa1wrUCTP/wjubb.Python.Programming.Mastery.From.Beginner.to.Pro.rar.html No Password - Links are Interchangeable

Free Download Python Programming Language For Complete Beginners Published 10/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 3.01 GB | Duration: 9h 13m On completion of this course you would be able to tackle programs in python What you'll learn The students after learning this python course would be able to get a basic understanding of what python is and will be able to solve problems regarding python This course covers algorithms, syntax, comments, loops, while loop, for loop, if statements elif statements, data types, variables, lists, tuples, functions Then it will also cover library modules , operator in python, strings, slicing operations They will get 20 python projects and 2 mini projects with their solutions Requirements No programming knowledge required Description This 25-video course is designed to introduce absolute beginners to the fundamentals of Python programming. Whether you are new to coding or looking to sharpen your skills in one of the most versatile and popular programming languages, this course will help you build a strong foundation. Python's simple syntax and readability make it an ideal starting point for anyone stepping into the world of programming.Throughout the course, you will cover a wide range of topics, including basic data types, control structures, functions, and modules. You'll learn how to manipulate strings, lists while understanding the importance of logic and flow in programming. As the course progresses, you will also gain practical experience by building real-world applications.Each day's session includes hands-on coding exercises and mini-projects, ensuring that you can immediately apply the concepts you learn. By the end of the course, you will be able to write clean, efficient, and well-structured Python code, and have the confidence to continue exploring advanced topics or transition into other programming languages.No prior programming experience is required, only a willingness to learn and explore. Join us to kickstart your journey in Python and discover the endless possibilities of coding! Lets see you in the course Overview Section 1: Intro and Basics Lecture 1 Intro Lecture 2 problems, algorithms and features Section 2: starting of with python Lecture 3 variables and data-types Lecture 4 indentation, comments and input operations Lecture 5 operators in python Lecture 6 programs Section 3: if conditions and loops in python Lecture 7 if condition Lecture 8 elif correction Lecture 9 nested if Lecture 10 while loop Lecture 11 for loop(1) Lecture 12 for loop(2) Lecture 13 for loop(3) Lecture 14 break statement in python Section 4: Tuples and Lists Lecture 15 lists(1) Lecture 16 lists(2) Lecture 17 lists(3) Lecture 18 lists methods(4) Lecture 19 tuples(1) Lecture 20 operations of tuples(2) Section 5: funtions and modules Lecture 21 functions(1) Lecture 22 functions(2) Lecture 23 global and local variables Lecture 24 calculator program in python Lecture 25 Strings in python Lecture 26 modules in python 11th , 12th, 1st/2nd year BE, Btech, BSC, BCA student Or anyone who wants to explore python programming language Screenshot Homepage https://www.udemy.com/course/python-programming-language-for-complete-beginners/ Rapidgator https://rg.to/file/21a6570d77d03e25b952af2e2a8aadcf/bquei.Python.Programming.Language.For.Complete.Beginners.part1.rar.html https://rg.to/file/6f4dc601217352653f0dad143d68b7e3/bquei.Python.Programming.Language.For.Complete.Beginners.part4.rar.html https://rg.to/file/7523128cfe138ec935f49b2fc5139b82/bquei.Python.Programming.Language.For.Complete.Beginners.part2.rar.html https://rg.to/file/85c5af47a64a78d4023e2250190507d0/bquei.Python.Programming.Language.For.Complete.Beginners.part3.rar.html Fikper Free Download https://fikper.com/a4flG1msf0/bquei.Python.Programming.Language.For.Complete.Beginners.part4.rar.html https://fikper.com/e9eijVMMg8/bquei.Python.Programming.Language.For.Complete.Beginners.part3.rar.html https://fikper.com/laObkSvm3t/bquei.Python.Programming.Language.For.Complete.Beginners.part2.rar.html https://fikper.com/tBuV2B3xhw/bquei.Python.Programming.Language.For.Complete.Beginners.part1.rar.html No Password - Links are Interchangeable

Free Download Python Programming For Beginners From Basics To Advanced Published 10/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 9.09 GB | Duration: 19h 39m Master Python Programming: Learn Syntax, Functions, OOP, and File Handling for Real-World Applications What you'll learn Understand Python syntax, variables, and data types to write basic programs Implement control structures like loops and conditional statements Build and utilize functions, including lambda functions, in Python Apply object-oriented programming concepts like classes, inheritance, and polymorphism Requirements No prior programming experience required-perfect for beginners Access to a computer with internet connection for coding exercises Optional: Install Python and an IDE (e.g., PyCharm or Anaconda) or use Google Colab for online coding Curiosity and a willingness to learn! Description Imagine this: You've always been curious about the world of technology and coding, but you've been hesitant to start. Maybe the jargon seemed overwhelming, or you felt like coding was only for those with an engineering background. But what if I told you that you could become proficient in Python, one of the most powerful and versatile programming languages in the world, without any prior experience?Now picture yourself, a few weeks from now, confidently writing your first Python program, automating tasks, analyzing data, or even building simple applications. You're the hero in this story-taking control of your learning journey, conquering new challenges, and equipping yourself with one of the most in-demand skills in today's tech-driven world.This course is designed to make you the hero of your coding adventure. Whether you're looking to start a new career, solve problems with technology, or simply satisfy your curiosity, this Python course will give you the skills you need. And the best part? No prior programming experience is required. All you need is a computer, access to the internet, and the willingness to learn and explore.What Will You Learn?By the end of this course, you will be able to:Master the basics of Python programming: Learn Python syntax, how to declare variables, use data types, and write simple programs.Work with control structures: Understand how to implement if-else statements, for loops, while loops, and other conditional logic to make your programs more dynamic.Create and use functions: Understand how to define and call functions, use parameters, and explore advanced topics like lambda functions.Understand object-oriented programming (OOP): Learn how to work with classes and objects, inheritance, polymorphism, and method overriding, making your code more efficient and reusable.Handle files: Discover how to open, read, write, and close files in Python, an essential skill for many real-world applications.Solve real-world problems: Use Python to automate repetitive tasks, manipulate data, and develop practical projects that you can apply in your personal or professional life.Why Python?Python is a high-level, versatile programming language known for its simplicity and readability, making it the perfect choice for beginners. It's also a favorite among developers, data scientists, and engineers due to its vast libraries and strong community support. Python powers everything from web development to data analysis, machine learning, and automation. So, whether you're aiming for a career in tech, looking to automate processes at work, or just want to explore programming for fun, Python is a great starting point.Who Is This Course For?This course is tailored for absolute beginners. You don't need any previous coding experience. It's ideal for:Students who want to develop coding skills for their studies or future careers.Professionals looking to upskill or transition into tech-related roles.Hobbyists or self-learners curious about programming and eager to solve problems using Python.Anyone who wants to learn how to automate tasks, analyze data, or develop web-based applications.What Tools Will You Use?In this course, you'll get hands-on experience using Python through:Google Colab: An easy-to-use, browser-based platform for writing and running Python code without installing anything on your computer.PyCharm or Anaconda: For those who prefer to set up a local Python environment, we'll walk you through the installation process and show you how to run Python code on your own machine.Jupyter Notebooks: For data analysis and visualization, a powerful tool commonly used by data scientists.Learning ApproachOur learning approach is centered around hands-on practice. Every lesson is followed by practical examples, quizzes, and coding challenges to help you reinforce what you've learned. As you progress through the course, you'll work on real-world projects that solidify your understanding and give you a portfolio of skills to showcase.Whether you're taking your first step into the world of programming or building on previous knowledge, this course will guide you through the essentials of Python in an easy-to-follow, structured way. The journey may be challenging at times, but with persistence and dedication, you'll find yourself mastering Python and unlocking new opportunities.Start Your Python JourneyYou are the hero of your own learning story. Don't let doubts or fear hold you back. Start today, and soon, you'll be navigating Python with confidence, solving problems, and perhaps even discovering a passion for coding you never knew you had.Are you ready to begin? Let's get started! Overview Section 1: Introduction to Python Lecture 1 Get to Know Your Instructor Lecture 2 What is Python? - Python Programming Language Explained Lecture 3 Use of Python Lecture 4 Python Code Execution Lecture 5 Features of Python Lecture 6 Queries Regarding Basics of Python Section 2: Basic Building Blocks of Python Lecture 7 Python Keywords and List of Keywords Lecture 8 Indentation and Comments, Identifiers, Variables in Python Lecture 9 Query Regarding Study Materials of Python Section 3: Hands on Python Activity Lecture 10 Using Print Statement in Python Lecture 11 Issues Regarding PyCharm Installation Lecture 12 Query Regarding Print Statement in Python Lecture 13 How to Run Google Colaboratory Lecture 14 More Queries Regarding Print Statement in Python Lecture 15 Queries Regarding Anaconda Installation Section 4: Using Variable in Python Lecture 16 How to Store Value in Variable in Python Lecture 17 Giving the Name of A Variable as A String Lecture 18 What Double Quotes Around a Variable Do Lecture 19 Queries Regarding Using Double Quotes Around a Variable Lecture 20 Problem with Kernel/Connecting with Server Lecture 21 Fixing the NameError in Jupyter Notebook Lecture 22 Reviewing Some Activities Regarding Variable in Python Section 5: Quick Overview on Basics of Python Lecture 23 Uses of Python Lecture 24 Features of Python Lecture 25 Keywords, List of Keywords and Comments Lecture 26 Python Identifiers and Variables Lecture 27 Data Types in Python Section 6: Working with Lists in Python Lecture 28 How Python List Works Lecture 29 How to Order Lists in Python Lecture 30 List Slicing in Python Lecture 31 Queries Regarding Python Lists Lecture 32 Solving an Undefined Variable NameError in Python Lecture 33 Fixing NameError Name is Not Defined Section 7: Essential Python List Functions and Troubleshooting Lecture 34 Using Python max() Function Lecture 35 Fixing Unterminated String Literal in Python Lecture 36 Issues Regarding Python Installation Lecture 37 Issues Regarding Function of List Section 8: Understanding and Troubleshooting Python Tuples Lecture 38 What is Tuple? Lecture 39 How do Tuples Work in Python Lecture 40 Queries Regarding Python Tuple Lecture 41 Issues Regarding Python Tuple Section 9: Introduction to Python Data Types and Structures Lecture 42 What You Have Learned So Far Lecture 43 Different Python Datatypes Lecture 44 Quick Overview on Python Tuple Lecture 45 Introduction to Strings in Python Section 10: Sets in Python : Everything You Need to Know About It Lecture 46 What Are Python Sets Lecture 47 Printing Set Variable Lecture 48 How to Print with Example Syntax Command Lecture 49 Understanding Google Colab Text color Lecture 50 Queries Regarding Sets in Python Lecture 51 Evaluating Assessments Section 11: Mastering Python Dictionaries and Booleans Lecture 52 Dictionary In Python Explained Lecture 53 Creating Dictionary in Python Lecture 54 Python Boolean Explained Section 12: Operators in Python - Everything You Need to Know Lecture 55 Introduction to Python Operators Lecture 56 Using Addition, Subtraction, Multiplication, Division and Modulus Operators Lecture 57 Using Comparison Operators Lecture 58 Logical, Membership and Identity Operators Lecture 59 Using Identity Operators in Python Lecture 60 Queries Regarding Python Operators Section 13: Getting Started with Conditional Statements in Python Lecture 61 Introduction to Conditional Statements in Python Lecture 62 Get to Know Your Instructor Lecture 63 Decision Making Statements Explained Lecture 64 Python If Statement Explained Lecture 65 If...Elif....Else Statement in Python Lecture 66 Assignments on Conditional Statements in Python Section 14: Hands on Activity on Conditional Statements Lecture 67 Using If Statement in Python Lecture 68 Using If Else Statement in Python Lecture 69 Using If...Elif...Else Statement in Python Lecture 70 Checking If True or False Using Conditional Statement in Python Lecture 71 Queries Regarding Checking If True or False Using Conditional Statement Lecture 72 Comparing Two Numbers Lecture 73 Queries Regarding Conditional Statements Section 15: Handling User Input and Integrating Online Tools in Python Lecture 74 Taking Integer Input in Python Lecture 75 Using Authorization Flow in Python Lecture 76 Using Another Online Tool to Run Python Code Lecture 77 Queries Regarding Python input() Function Section 16: Mastering Python Loops: For Loops and Beyond Lecture 78 Types of Loops in Python Lecture 79 Python For Loops Explained Lecture 80 Calculating Table with Loop Lecture 81 Flow Chart For Loop Lecture 82 Queries Regarding For Loop Section 17: Understanding and Using Python Loops and Break Statements Lecture 83 Python While Loop Explained Lecture 84 Python Break Statement with Flowchart Lecture 85 Working of Break with For and While Loop Section 18: Hands on Activity on Python Loops Lecture 86 Printing Digits using For Loop Lecture 87 Sum of Digits of a Number in Python Lecture 88 Python Looping Through a Range Lecture 89 Queries Regarding Looping Through a Range Lecture 90 Using a Break Statement with For Loops Lecture 91 Using If-Else Statements and While Loops in Python Lecture 92 Queries Regarding Accessing the Resources Section 19: Introduction to Python Functions: Basics and Syntax Lecture 93 What You Have Learned So Far Lecture 94 Making a "sub" Function Lecture 95 What Is Function? Lecture 96 Queries Regarding Basics of Function Lecture 97 Creating a Function Syntax Section 20: Defining and Calling a Function Lecture 98 Defining Any Name in Python Lecture 99 Defining Multiplication Function and Calling Sum Function in Print Statement Lecture 100 Queries Regarding Defining Sum Function Lecture 101 Creating Function Without Return Statement and Defining Square Number Lecture 102 Evaluating Assessments Section 21: Working with Parameters in Python Functions: Definition, Issues, and Assessment Lecture 103 Using Parameters in Sum Function Lecture 104 Defining Sum Function Using Parameters Lecture 105 Issues Regarding Defining Sum Function Using Parameters Lecture 106 Defining Name as Function and Printing The Hello Statement Lecture 107 Queries Regarding Using Parameters in Function Lecture 108 Evaluating Assessments Section 22: Creating and Using Functions with Arguments in Python Lecture 109 What You Have Learned So Far Lecture 110 Creating a Function With Arguments Lecture 111 Example on Creating a Function With Arguments Section 23: Exploring Python Lambda Functions: Basics and Practical Applications Lecture 112 What is Lambda Function in Python Lecture 113 Adding 10 to Argument A and Returning The Result Lecture 114 Queries Regarding Lambda Function Lecture 115 Program to Filter Out Only The Even Items From The List Lecture 116 Program to Filter Out Only The Odd Items From The List Lecture 117 Program to Filter Out Numbers Which are Greater Than 60 Using Lambda Function Section 24: Using Python Map, Local & Global Variables: Concepts and Examples Lecture 118 Program to Double Each Item in a List Using Map Lecture 119 Program to Add 10 to All The Values Using Map Lecture 120 What is a Local and Global Variable in Python? Lecture 121 Using Global Variable and Local Variable With the Same Name in Python Lecture 122 What are The Applications of Global and Local Variables? Lecture 123 Queries Regarding Global and Local Variables Lecture 124 Query Regarding Filtering Even Numbers Using Lambda Function Section 25: Introduction to Object-Oriented Programming in Python: Classes and Objects Lecture 125 What You Have Learned So Far Lecture 126 What is Object Oriented Programming Lecture 127 Class in Python Explained Lecture 128 Syntax and Object in Python Lecture 129 Program to Demonstrate Class and Object Concept Section 26: Troubleshooting Functions and Attributes in Python: Common Issues and Solutions Lecture 130 Why a Function Could Not Be Executed in Python Lecture 131 Why is Dot Operator Used in Python Lecture 132 Can We Have More Than One Object For The Same Class in Python Lecture 133 Query Regarding Display Function in Python Lecture 134 Fixing AttributeError in Python Section 27: Understanding and Implementing Constructors in Python Lecture 135 What is A Constructor in Python Lecture 136 Creating The Constructor in Python Lecture 137 Counting The Number of Objects with Non Parameterized Constructor Lecture 138 Fixing Invalid Syntax in Python SyntaxError Lecture 139 Fixing Issues Regarding Counting The Number of Objects Lecture 140 Short Recap on Object Oriented Programming and Python Constructor Lecture 141 Query on Extracting The Object Values Using Map Section 28: Exploring Inheritance in Python: Types and Examples Lecture 142 Recap on What You Have Learned So Far Lecture 143 What is an inheritance in Python Lecture 144 Types of Inheritance in Python Lecture 145 Single Inheritance in Python Explained Lecture 146 Multilevel Inheritance in Python with Example Lecture 147 Multilevel Inheritance in Python Explained Section 29: Mastering Multiple Inheritance in Python: Concepts and Examples Lecture 148 Multiple Inheritance in Python Explained Lecture 149 Example of Multiple Inheritance in Python Lecture 150 Queries Regarding Multiple Inheritance Lecture 151 Fixing Errors Regarding Multiple Inheritance Lecture 152 How to Use an Input() Function Within a Class in Python Section 30: Understanding and Implementing Method Overriding in Python Lecture 153 Method Overriding in Python Explained Lecture 154 Real Life Example Method Overriding Lecture 155 Query on Method Overriding Lecture 156 Use of Python super() Function Section 31: Overview on What You Have Learned So Far Lecture 157 Problems Regarding Practice Codes Lecture 158 Basics Of Python Lecture 159 Class and Object in Python Lecture 160 Creating The Constructor in Python Lecture 161 Types of Inheritance in Python Lecture 162 Method Overriding Explained Lecture 163 Queries on Object Oriented Programming Lecture 164 Additional Queries on Object Oriented Programming Section 32: Understanding Polymorphism in Python: Concepts and Examples Lecture 165 What is Polymorphism in Python Lecture 166 Polymorphism in len() Function in Python Section 33: File Handling in Python: Functions, Queries, and Applications Lecture 167 Python File Open Function Lecture 168 How to Open and Close a File in Python Lecture 169 Queries on Python Open File Function Lecture 170 Why Visual Studio Code is Used Lecture 171 Queries Regarding Commands Used for File Handling in Python Lecture 172 Can Python be Used for Data Analysis? Lecture 173 What Is Python Used For? This course is designed for beginners with no prior coding experience who want to learn Python from scratch. It's also ideal for students, professionals, and hobbyists interested in developing their programming skills for data analysis, automation, web development, or any field that requires coding knowledge. Additionally, anyone looking to transition into tech or enhance their problem-solving and logical thinking abilities will find this course valuable. 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Free Download Python Numpy Programming with Coding Exercises Published 10/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 1h 32m | Size: 312 MB Master Numerical Computing and Data Analysis with NumPy Through Hands-On Coding What you'll learn How to create and manipulate NumPy arrays for efficient numerical computing. Techniques for performing mathematical operations and statistical analysis with NumPy. Advanced array manipulations such as reshaping, indexing, and broadcasting. Application of NumPy in solving linear algebra problems and integrating with other data analysis tools. Requirements Basic knowledge of Python programming. Understanding of fundamental mathematical concepts. Description Welcome to Python NumPy Programming with Coding Exercises, a comprehensive course designed to teach you the essentials of numerical computing using the NumPy library. NumPy is a fundamental package for scientific computing in Python, providing support for arrays, matrices, and a wide range of mathematical functions. This course will guide you through the core functionalities of NumPy, enhancing your ability to perform efficient data manipulation and analysis.In today's data-driven world, proficiency in numerical computing is crucial for analyzing data, performing complex calculations, and building machine learning models. NumPy's powerful array operations and mathematical capabilities make it an indispensable tool for data scientists, analysts, and engineers. This course aims to equip you with practical skills and knowledge through hands-on coding exercises that reinforce learning and apply concepts to real-world problems.Throughout this course, you will cover:Introduction to NumPy and its array objects: Understand the basics of NumPy, including array creation, manipulation, and basic operations.Array operations and mathematical functions: Learn to perform arithmetic operations, statistical calculations, and algebraic manipulations with NumPy arrays.Advanced array manipulations: Explore topics such as indexing, slicing, reshaping, and broadcasting to handle complex data structures.Numerical methods and linear algebra: Apply NumPy for solving linear algebra problems, including matrix operations and decompositions.Data analysis and integration: Use NumPy for data cleaning, transformation, and integration with other libraries like pandas.Practical exercises: Apply your skills to solve real-world problems and work with datasets to reinforce learning and practice key concepts.By the end of this course, you will be proficient in using NumPy for numerical computing, enabling you to handle large datasets efficiently and perform advanced mathematical operations with ease.Instructor Introduction: Faisal Zamir is a seasoned Python developer and educator with over 7 years of experience in teaching and working with Python libraries. Faisal's expertise in numerical computing and his clear, practical teaching approach will guide you through the intricacies of NumPy, ensuring you gain valuable skills and insights.Certificate at the End of Course: Upon successful completion of the course, you will receive a certificate that validates your skills in Python NumPy programming, enhancing your professional profile. Who this course is for Data scientists and analysts seeking to enhance their skills in numerical computing. Python developers interested in mastering array operations and data manipulation. Professionals and students aiming to apply mathematical and statistical techniques in their projects. Homepage https://www.udemy.com/course/python-numpy-programming-with-coding-exercises/ Screenshot Rapidgator https://rg.to/file/6d10eb2c4afe507c5ab1e74c4339ec64/emglh.Python.Numpy.Programming.with.Coding.Exercises.rar.html Fikper Free Download https://fikper.com/Dn5C7znUHu/emglh.Python.Numpy.Programming.with.Coding.Exercises.rar.html No Password - Links are Interchangeable

Free Download Python Microservices from basics to Advanced Published 10/2024 Created by Tharun Bonampudi MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 8 Lectures ( 54m ) | Size: 591 MB Master how to build Python Microservices with their best practices! What you'll learn Learn basics and advanced concepts of Python Microservices Learn best practices of Python Microservices Learn python development, deployment, scaling, and management Learn Python microservices architecture Requirements You need to be interested in learning Python Microservices Description Python microservices represent a modern software architectural approach that breaks down monolithic applications into smaller, self-contained, and loosely coupled services. Each microservice is designed to perform a specific function, and they collectively work together to form a larger, more complex application. This architecture contrasts with traditional monolithic systems, where all components are tightly integrated into a single codebase. Microservices typically communicate with each other through APIs, often using lightweight protocols like HTTP/REST or message brokers like RabbitMQ or Kafka for asynchronous communication. This decoupled nature allows services to be written in different languages, though Python is frequently chosen for its robust ecosystem and ease of use.In Python microservices, each service is responsible for its own lifecycle, including development, deployment, scaling, and management. This allows teams to work on different services independently, enabling faster development cycles and more flexible updates. One of Python's key advantages in microservices architecture is its simplicity and readability, making it easy for developers to quickly write, understand, and maintain code. Additionally, Python offers a wide range of frameworks and tools that support microservice development, such as Flask, FastAPI, and Django REST Framework.Python microservices offer a flexible, scalable, and efficient way to build complex applications by breaking them into smaller, manageable components. While this approach requires more attention to infrastructure and management, the advantages of faster deployment, fault tolerance, and scalability make it a popular choice for modern software development. Who this course is for This course is for those wanting to learn Python Microservices Homepage https://www.udemy.com/course/microservices-from-basics-to-advanced/ Screenshot Rapidgator https://rg.to/file/a4d5b03fb3a65209dd246c11ec801658/wbydl.Python.Microservices.from.basics.to.Advanced.rar.html Fikper Free Download https://fikper.com/CBMWTeCsKM/wbydl.Python.Microservices.from.basics.to.Advanced.rar.html No Password - Links are Interchangeable

Free Download Python Mastery Devops, Automation, And Real-World Use Cases Published 10/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 2.23 GB | Duration: 9h 0m From Coding Fundamentals to Cloud Automation, GitHub Integration, CI/CD Automation with Jenkins and Game Development What you'll learn Python coding practice About Data Types in Python Regular Expression (regex) in Python How to identify and apply keywords in code How to declare and assign values to variables. The purpose and function of the return statement in functions. Python Functions: Definition and Usage Utilizing Modules in Function Design Organizing Your Code Using Python Packages The use of the sys module to access command line arguments The different types of operators in Python, including arithmetic, comparison, logical, and assignment operators. DevOps Use Cases with if..else..elif For/While Loops in Python: Syntax and Usage Real-time Use Case: Lists and Exception Handling in Python Python Script for Handling Exceptions Using Try Statements Integrating Python with GitHub Through the GitHub API Cloning a GitHub Repository with Python Performing operations on various AWS services like S3, EC2 using Boto3 Python Module Launching an EC2 Instance using Boto3 Python Module CI/CD Automation with Jenkins and Python Integrate GitHub Webhooks With Jenkins Develop Games in Python with PyCharm and ChatGPT Requirements Basic Computer Skills: Familiarity with using a computer and navigating the internet. No Prior Programming Experience Required: This course is designed for beginners, so no previous programming knowledge is necessary. Basic Knowledge of DevOps is required Description Python for DevOps means using Python to make DevOps tasks easier and more efficient. DevOps is all about automating tasks like building, testing, and deploying software quickly, as well as managing servers and infrastructure. Python is great for this because it's simple to learn, and it has many tools and libraries that help automate these tasks. For example, you can use Python to automatically create servers, manage cloud services, and set up continuous integration and delivery (CI/CD) pipelines. Python helps DevOps teams work faster and more effectively by reducing manual work and making processes smoother.Course Outline:Section1: Introduction-> Introduction-> An overview of Python-> About Shell Scripting-> Python vs. Shell Scripting-> When to Use Python vs. Shell ScriptingSection2: How to Begin Practicing Python Coding-> Begin Python Coding Practice-> Visual Studio Code - Python Coding Practice-> PyCharm - IDEs-> Codespaces - Online Coding PlatformSection3: Python Data Types-> About Data Types in Python-> Lab - String Data Type-> Lab - Integer Data Type-> Lab - Float Data Type-> Lab - len(), Length of a string-> Lab - String upper(), lower()-> Lab - String replace()-> Lab - String split()-> Lab - Print specific object in split()-> About List in Python-> Lab - List Data Type-> Lab - Add and Modify in a List Data Type (Mutable)-> About Tuples in Python-> Lab - Tuples in Python-> About Sets in Python-> Lab - Sets in Python-> Dictionary in Python-> Lab - Dictionary in Python-> Use Cases in DevOps-> Boolean Data Types-> Lab - Boolean in Python-> Coding Exercise 1:Create a Python script to add two integers-> Coding Exercise 2:Create a python script to perform operation of floating-point-> Coding Exercise 3:Write a python script to determine the length of a string-> Coding Exercise 4:Create a python script to convert a string to uppercase and lowercase-> Coding Exercise 5:Create a Simple python Script to replace a substring within a string-> Coding Exercise 6:Create a Simple python script to Split the text of a string-> Coding Exercise 7:Create a python script to define a Variable and assign it a list of five integersSection4: Regular Expression (regex) in Python-> Overview of Regular Expressions in Python-> Lab - Using re. match() to Match Patterns at the Start of a String-> Lab - Using re. search() to Find Matches Anywhere in a String-> Lab - Using re. findall() to Search for All Matches in a String-> Regex Use Cases from a DevOps Perspective-> Coding Exercise 8:Regular Expression in python-> Section5: Mastering Keywords in Python-> Overview of Keywords in Python-> Common Python keywords-> Mastering Control Flow Keywords - if, else, for, and break-> Lab: Mastering Control Flow Keywords - continue, def, return, class, import etc.Section6: Working with Variables in Python-> Overview of Variables with Example-> Lab: Working with Float Variables in Python-> Lab: Defining Lists as Variables in Python-> Lab: Working with Dictionary Variables in Python-> Python Variables: Local vs Global Scope-> Lab: Working with Local Variables in Python-> Lab: Working with Global Variables in PythonSection7: Return Statement in Python-> Return Statement: An Overview with Syntax-> Lab: Creating Functions That Return Values-> Lab: Functions That Return Multiple Values-> Lab: Function for Identifying Even and Odd ValuesSection8: Python Functions: Definition and Usage-> Introduction to Functions in Python-> Advantages of functions in Python-> Lab: Functions with Parameters-> Lab: Functions with Return Value-> Lab: Designing Functions for Basic Arithmetic Operations-> Comparing Scripts: Using Functions vs. Not Using FunctionsSection9: Utilizing Modules in Function Design-> Introduction to Python Modules-> An Overview of Built-in Modules-> An Overview of User-defined Modules-> Lab: Essential Built-in Modules in Python-> Lab: OS and Math Modules-> Lab: Building Your Own ModulesSection 10: Python Packages: Organizing Your Code-> Introduction to Python Packages-> Key Concepts of Packages-> Advantages of Using Packages-> Lab: Creating Package Structures and Modules-> Importing Modules for Easier Access using __init__. py-> Creating a Main Python File to Utilize Your Package-> Importing Functions from a PackageSection 11: Command Line Arguments in Python-> Command Line Arguments with Practical Examples-> Lab: Script to Add Two Numbers (No Command Line Arguments)-> Lab: Working with sys. argv for Command Line Arguments-> Lab: Passing Multiple Arguments to Python Scripts-> Lab: Pass Arguments to Add Two Numbers-> Lab: Conditional Arithmetic via Script Arguments-> Lab: Conditional Arithmetic Using Script ArgumentsSection 12: Operators in Python: Concepts and Examples-> The Basics of Arithmetic Operators in Python-> Lab: Exploring Comparison (Relational) Operators-> Lab: Comparison Operators (=, >, >=, ==)-> Logical Operators: and, or, not-> Lab: Using 'and' , 'or' for Logical Operations-> Lab: Using 'not' for Logical Operations-> Assignment Operators in Python-> Lab: Understanding Different Assignment Operators-> Membership Operators: 'in' and 'not in'-> Lab: Using 'not in' Membership Operators-> Operators in DevOps: Practical Use Cases-> Use Cases for Operators in the DevOps WorkflowSection 13: Conditional Statements in Python-> Understanding 'if' statement in Python-> Understanding 'else'..'elif' statement in Python-> Lab: Implementing if..else Statements-> Lab: DevOps Use Cases with if..else..elifSection 14: Understanding Loops in Python-> For Loops in Python: Syntax and Usage-> While Loops in Python: Syntax and Usage-> Lab: Implementing For Loops-> Lab: Printing Ranges and Strings with For Loops-> Lab: Implementing Infinite While Loops-> Lab: Exploring Break Statements in PythonSection 15: Real-time Use Case: Lists and Exception Handling in Python-> Introduction to the Real-Time Project-> Lab: User Input for List Creation-> Lab: Understanding split function text.split()-> Lab: Identify modules and their functions-> Lab: Utilize a for loop to list files-> Exception Handling with Try Statement-> Lab: Python Script for Handling Exceptions Using Try Statements-> Lab: Handling Error - FileNotFoundError-> Lab: Handling Known Error - PermissionErrorSection 16: Integrating Python with GitHub-> Integrating Python with GitHub Through the GitHub API-> Lab: Install PyGithub and Generate a GitHub Access Token-> Lab: Retrieve User Login and Public Repos with Python-> Lab: Retrieve GitHub Account Repository List-> Lab: Create a New Repository with PythonSection 17: Cloning a GitHub Repository with Python-> Clone a Repository Using the Subprocess Module-> Lab: Clone a Repository with the Subprocess Module-> Lab: Using GitPython Library-> Lab: Handle Git Errors with Exception HandlingSection 18: Boto3 Python Module-> Introduction to the Boto3 Python Module-> Lab: Install Boto3 and Create an AWS User Account-> Lab: Configure GitHub Access from Codespaces via AWS CLI-> Lab: List All Buckets with Boto3-1-> Lab: List All Buckets with Boto3-2-> Lab: List All Buckets with Boto3-3-> Lab: Upload a File to a Bucket Using Boto3-> Lab: Download a File to a Bucket Using Boto3Section 19: Launching an EC2 Instance using Boto3 Python Module-> Project Overview-> Setting Up a User Account in AWS with IAM-> Set Up AWS CLI in Codespaces-> Begin Python Script: Import Boto3-> Include EC2 Attributes in Python Script-> Add Tag Specifications in Python Script-> Debug the Python Script Before Execution-> Access the EC2 Instance Launched via Python Script-> Update the Python Script to Add 20GB EBS Volume-> Run Python Script to Confirm EBS Volume-> Update Python Script to Include UserData-> Update Python Script to Include Apache Package-> Run the Revised Python Script and Validate-> Access the Apache ServerSection 20: CI/CD Automation with Jenkins and Python-> Project Overview-> Set Up a GitHub Repository for Your Project-> Write the Source Code in Python and Push to GitHub Repository-> Provision a Jenkins Server Instance in AWS-> Connect to the Jenkins Server and Install Java-> Install the Jenkins Package on the Server-> Set Up Jenkins Configuration-> Install Necessary Plugins on the Jenkins Server-> Add GitHub Credentials to the Jenkins Server-> First Stage of the Pipeline: Checkout the Project-> Build the Job-> Add a Stage for Installing Python Dependencies-> Add a Stage to Execute the Python Script-> Setting Up a User Account in AWS with IAM-> Create Access Keys for Jenkins Credentials-> Set Up Access Keys in Jenkins Pipeline-> Export AWS Credentials in Jenkins Pipeline-> Build the Job and Verify EC2 Instance Creation in AWS-> Access the Web Server Using URLSection 21: Integrate GitHub Webhooks With Jenkins-> Setup GitHub Webhooks in Jenkins-> GitHub hook trigger for GITScm polling-> Add Jenkins Webhook to GitHub Repository-> Test the Webhook by Editing the Python ScriptSection 22: Develop Games in Python with PyCharm and ChatGPT Overview Section 1: Introduction Lecture 1 Introduction Lecture 2 An overview of Python Lecture 3 About Shell Scripting Lecture 4 Python vs. Shell Scripting Lecture 5 When to Use Python vs. Shell Scripting Section 2: How to Begin Practicing Python Coding Lecture 6 Begin Python Coding Practice Lecture 7 Visual Studio Code - Python Coding Practice Lecture 8 PyCharm - IDEs Lecture 9 Codespaces - Online Coding Platform Section 3: Python Data Types Lecture 10 About Data Types in Python Lecture 11 Lab - String Data Type Lecture 12 Lab - Integer Data Type Lecture 13 Lab - Float Data Type Lecture 14 Lab - len(), Length of a string Lecture 15 Lab - String upper(), lower() Lecture 16 Lab - String replace() Lecture 17 Lab - String split() Lecture 18 Lab - Print specific object in split() Lecture 19 About List in Python Lecture 20 Lab - List Data Type Lecture 21 Lab - Add and Modify in a List Data Type (Mutable) Lecture 22 About Tuples in Python Lecture 23 Lab - Tuples in Python Lecture 24 About Sets in Python Lecture 25 Lab - Sets in Python Lecture 26 Dictionary in Python Lecture 27 Lab - Dictionary in Python Lecture 28 Use Cases in DevOps Lecture 29 Boolean Data Types Lecture 30 Lab - Boolean in Python Section 4: Regular Expression (regex) in Python Lecture 31 Overview of Regular Expressions in Python Lecture 32 Lab - Using re.match() to Match Patterns at the Start of a String Lecture 33 Lab - Using re.search() to Find Matches Anywhere in a String Lecture 34 Lab - Using re.findall() to Search for All Matches in a String Lecture 35 Regex Use Cases from a DevOps Perspective Section 5: Mastering Keywords in Python Lecture 36 Overview of Keywords in Python Lecture 37 Common Python keywords Lecture 38 Mastering Control Flow Keywords - if, else, for, and break Lecture 39 Lab: Mastering Control Flow Keywords - continue, def, return, class, import etc. Section 6: Working with Variables in Python Lecture 40 Overview of Variables with Example Lecture 41 Lab: Working with Float Variables in Python Lecture 42 Lab: Defining Lists as Variables in Python Lecture 43 Lab: Working with Dictionary Variables in Python Lecture 44 Python Variables: Local vs Global Scope Lecture 45 Lab: Working with Local Variables in Python Lecture 46 Lab: Working with Global Variables in Python Section 7: Return Statement in Python Lecture 47 Return Statement: An Overview with Syntax Lecture 48 Lab: Creating Functions That Return Values Lecture 49 Lab: Functions That Return Multiple Values Lecture 50 Lab: Function for Identifying Even and Odd Values Section 8: Python Functions: Definition and Usage Lecture 51 Introduction to Functions in Python Lecture 52 Advantages of functions in Python Lecture 53 Lab: Functions with Parameters Lecture 54 Lab: Functions with Return Value Lecture 55 Lab: Designing Functions for Basic Arithmetic Operations Lecture 56 Comparing Scripts: Using Functions vs. Not Using Functions Section 9: Utilizing Modules in Function Design Lecture 57 Introduction to Python Modules Lecture 58 An Overview of Built-in Modules Lecture 59 An Overview of User-defined Modules Lecture 60 Lab: Essential Built-in Modules in Python Lecture 61 Lab: OS and Math Modules Lecture 62 Lab: Building Your Own Modules Section 10: Python Packages: Organizing Your Code Lecture 63 Introduction to Python Packages Lecture 64 Key Concepts of Packages Lecture 65 Advantages of Using Packages Lecture 66 Lab: Creating Package Structures and Modules Lecture 67 Importing Modules for Easier Access using __init__.py Lecture 68 Creating a Main Python File to Utilize Your Package Lecture 69 Importing Functions from a Package Section 11: Command Line Arguments in Python Lecture 70 Command Line Arguments with Practical Examples Lecture 71 Lab: Script to Add Two Numbers (No Command Line Arguments) Lecture 72 Lab: Working with sys.argv for Command Line Arguments Lecture 73 Lab: Passing Multiple Arguments to Python Scripts Lecture 74 Lab: Pass Arguments to Add Two Numbers Lecture 75 Lab: Conditional Arithmetic via Script Arguments Lecture 76 Lab: Conditional Arithmetic Using Script Arguments Section 12: Operators in Python: Concepts and Examples Lecture 77 The Basics of Arithmetic Operators in Python Lecture 78 Lab: Exploring Comparison (Relational) Operators Lecture 79 Lab: Comparison Operators (=, >, >=, ==) Lecture 80 Logical Operators: and, or, not Lecture 81 Lab: Using 'and' , 'or' for Logical Operations Lecture 82 Lab: Using 'not' for Logical Operations Lecture 83 Assignment Operators in Python Lecture 84 Lab: Understanding Different Assignment Operators Lecture 85 Membership Operators: 'in' and 'not in' Lecture 86 Lab: Using 'not in' Membership Operators Lecture 87 Operators in DevOps: Practical Use Cases Lecture 88 Use Cases for Operators in the DevOps Workflow Section 13: Conditional Statements in Python Lecture 89 Understanding 'if' statement in Python Lecture 90 Understanding 'else'..'elif' statement in Python Lecture 91 Lab: Implementing if..else Statements Lecture 92 Lab: DevOps Use Cases with if..else..elif Section 14: Understanding Loops in Python Lecture 93 For Loops in Python: Syntax and Usage Lecture 94 While Loops in Python: Syntax and Usage Lecture 95 Lab: Implementing For Loops Lecture 96 Lab: Printing Ranges and Strings with For Loops Lecture 97 Lab: Implementing Infinite While Loops Lecture 98 Lab: Exploring Break Statements in Python Section 15: Real-time Use Case: Lists and Exception Handling in Python Lecture 99 Introduction to the Real-Time Project Lecture 100 Lab: User Input for List Creation Lecture 101 Lab: Understanding split function text.split() Lecture 102 Lab: Identify modules and their functions Lecture 103 Lab: Utilize a for loop to list files Lecture 104 Exception Handling with Try Statement Lecture 105 Lab: Python Script for Handling Exceptions Using Try Statements Lecture 106 Lab: Handling Error - FileNotFoundError Lecture 107 Lab: Handling Known Error - PermissionError Section 16: Integrating Python with GitHub Lecture 108 Integrating Python with GitHub Through the GitHub API Lecture 109 Lab: Install PyGithub and Generate a GitHub Access Token Lecture 110 Lab: Retrieve User Login and Public Repos with Python Lecture 111 Lab: Retrieve GitHub Account Repository List Lecture 112 Lab: Create a New Repository with Python Section 17: Cloning a GitHub Repository with Python Lecture 113 Clone a Repository Using the Subprocess Module Lecture 114 Lab: Clone a Repository with the Subprocess Module Lecture 115 Lab: Using GitPython Library Lecture 116 Lab: Handle Git Errors with Exception Handling Section 18: Boto3 Python Module Lecture 117 Introduction to the Boto3 Python Module Lecture 118 Lab: Install Boto3 and Create an AWS User Account Lecture 119 Lab: Configure GitHub Access from Codespaces via AWS CLI Lecture 120 Lab: List All Buckets with Boto3-1 Lecture 121 Lab: List All Buckets with Boto3-2 Lecture 122 Lab: List All Buckets with Boto3-3 Lecture 123 Lab: Upload a File to a Bucket Using Boto3 Lecture 124 Lab: Download a File to a Bucket Using Boto3 Section 19: Launch EC2 Instance with Boto3 Python Module Lecture 125 Project Overview Lecture 126 Setting Up a User Account in AWS with IAM Lecture 127 Set Up AWS CLI in Codespaces Lecture 128 Begin Python Script: Import Boto3 Lecture 129 Include EC2 Attributes in Python Script Lecture 130 Add Tag Specifications in Python Script Lecture 131 Debug the Python Script Before Execution Lecture 132 Access the EC2 Instance Launched via Python Script Lecture 133 Update the Python Script to Add 20GB EBS Volume Lecture 134 Run Python Script to Confirm EBS Volume Lecture 135 Update Python Script to Include UserData Lecture 136 Update Python Script to Include Apache Package Lecture 137 Run the Revised Python Script and Validate Lecture 138 Access the Apache Server Section 20: CI/CD Automation with Jenkins and Python Lecture 139 Project Overview Lecture 140 Set Up a GitHub Repository for Your Project Lecture 141 Write the Source Code in Python and Push to GitHub Repository Lecture 142 Provision a Jenkins Server Instance in AWS Lecture 143 Connect to the Jenkins Server and Install Java Lecture 144 Install the Jenkins Package on the Server Lecture 145 Set Up Jenkins Configuration Lecture 146 Install Necessary Plugins on the Jenkins Server Lecture 147 Add GitHub Credentials to the Jenkins Server Lecture 148 First Stage of the Pipeline: Checkout the Project Lecture 149 Build the Job Lecture 150 Add a Stage for Installing Python Dependencies Lecture 151 Add a Stage to Execute the Python Script Lecture 152 Setting Up a User Account in AWS with IAM Lecture 153 Create Access Keys for Jenkins Credentials Lecture 154 Set Up Access Keys in Jenkins Pipeline Lecture 155 Export AWS Credentials in Jenkins Pipeline Lecture 156 Build the Job and Verify EC2 Instance Creation in AWS Lecture 157 Access the Web Server Using URL Section 21: Integrate GitHub Webhooks with Jenkins Lecture 158 Setup GitHub Webhooks in Jenkins Lecture 159 GitHub hook trigger for GITScm polling Lecture 160 Add Jenkins Webhook to GitHub Repository Lecture 161 Test the Webhook by Editing the Python Script Lecture 162 Last Lecture Individuals with little or no prior programming experience who want to learn Python from scratch.,DevOps Professionals: Anyone interested in automation, cloud computing, and using Python for DevOps practices.,Students and Professionals: Anyone seeking to enhance their resume or career prospects by adding Python programming to their skill set.,Overall, this course is suitable for anyone eager to learn Python and apply it in real-world scenarios. 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Free Download Python Guided Project - Building Tic-Tac-Toe from Scratch Raj Gaurav Mishra | Duration: 1:03 h | Video: HVC1 1280x720 | Audio: AAC 48 kHz 2ch | 108 MB | Language: English For beginner Python developers curious about developing a game in Python and a portfolio project for resume. This is an entry-level guided project and is about developing a game in Python. This course is designed for beginners who want to start their career journey in the field of IT and Software Engineering. This course is for beginner Python developers curious about developing a game in Python. In this guided project (course), we will implement a game (Tic-Tac-Toe) using Python programming. This will be an implementation of the Tic-Tac-Toe game using random numbers. To maintain simplicity, this game will be programmed to play automatically and no user input will be required. What is Tic-Tac-Toe? Tic-tac-toe, noughts and crosses, or Xs and Os is a paper-and-pencil game for two players who take turns marking the spaces in a three-by-three grid with X or O. The winner is the first player to get three of the same symbols in a row (up, down or diagonally). Homepage https://www.udemy.com/course/python-guided-project-building-tic-tac-toe-from-scratch/ Rapidgator https://rg.to/file/2b20d9c7541e5c98d3cc2bf2867693d3/zvcdo.Python.Guided.Project.Building.TicTacToe.from.Scratch.rar.html Fikper Free Download https://fikper.com/4KHNkSZgV8/zvcdo.Python.Guided.Project.Building.TicTacToe.from.Scratch.rar.html No Password - Links are Interchangeable

Free Download Python For Data Science Your Career Accelerator Published 10/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 3.83 GB | Duration: 10h 37m Master Python and Unlock Data Analysis, Visualization, and Machine Learning Skills What you'll learn Learn the basics of Python, including data types, variables, loops, conditionals, and string manipulation. Gain hands-on experience with essential libraries like Pandas, NumPy, and Matplotlib for data manipulation, analysis, and visualization. Learn to clean, transform, and preprocess datasets for analysis, preparing them for real-world data science tasks. Understand the concepts of object-oriented programming (OOP) and apply them to structure Python code efficiently. By the end of the course, students will have completed a data science capstone project, where they will collect, analyze, and present insights from a real-world Requirements No programming experience or knowledge of Data Science required. Just come with a passion to learn. Description Are you ready to embark on an exciting journey into the world of data science? "Python for Data Science: Your Career Accelerator" is meticulously designed to transform beginners into proficient data science professionals, equipping you with the essential skills and knowledge needed to thrive in today's rapidly evolving, data-driven landscape.This comprehensive Python for Data Science course covers:Comprehensive Python Course: Master Python programming from the basics to advanced data science applications, including essential libraries like Pandas and NumPy.Data Analysis: Learn essential techniques to manipulate, clean, and analyze real-world datasets, ensuring your data is ready for actionable insights.Data Visualization: Create impactful visualizations using libraries like Matplotlib and Seaborn to present data in a meaningful way and drive decision-making.Machine Learning: Explore core machine learning concepts and algorithms, from linear regression to classification models, and apply them to solve real-world problems.Hands-on Projects: Work on real-world projects to build practical skills and a strong portfolio for your data science career, preparing you to excel in the field.Career-Focused: Gain the skills to excel in roles like Data Analyst, Data Scientist, or Machine Learning Engineer with the confidence to tackle industry challenges.With a focus on practical, project-based learning, this course equips you with both theoretical knowledge and hands-on experience, ensuring you're ready to succeed in the fast-growing field of data science. Overview Section 1: Python Essentials: From Basics to Collaboration Lecture 1 Welcome Note & Intro to python Lecture 2 Introduction to Google Colab Notebook Lecture 3 Introduction to GitHub Lecture 4 Print & Comment Section 2: Python Basics: Fundamental Concepts and Operations Lecture 5 Variables & Assignment Operators Lecture 6 Understanding Data Types Lecture 7 Understanding Expressions Lecture 8 Arithmetic & Assignment Operators Lecture 9 Relational/Comparison Operators Lecture 10 Logical Operators Lecture 11 Identity & Membership Operators, Type Lecture 12 User Input Section 3: Mastering Conditional Branching in Python Lecture 13 Conditional Statements with Logical Operators Lecture 14 If-elif-else Statements Lecture 15 Switch Case Section 4: Mastering Loops in Python Lecture 16 For Loop Lecture 17 While Loops Lecture 18 Do-While Loop Lecture 19 Break and Continue Statements Section 5: Exploring Functions in Python Lecture 20 Introduction to Functions & Pass Statements in Python Lecture 21 Working with Function Arguments Lecture 22 Functions with Return Types Lecture 23 Understanding Local and Global Variables Lecture 24 Lambda Functions in Python Section 6: Mastering Strings in Python Lecture 25 Creating Strings Lecture 26 Understanding Strings as Arrays Lecture 27 Looping Through Strings Lecture 28 String Manipulation Lecture 29 Essential String Operations Lecture 30 Exploring Useful String Methods Section 7: Mastering Lists in Python Lecture 31 Introduction to Lists Lecture 32 Iterating Through List Items Lecture 33 Exploring List Properties Lecture 34 Mastering List Manipulation Lecture 35 Exploring List Methods in Python Section 8: Mastering Tuples in Python Lecture 36 Introduction to Tuples Lecture 37 Advanced Tuple Operations Lecture 38 Mastering Tuple Operations Lecture 39 Exploring Tuple Methods and Operations Section 9: Mastering Dictionaries in Python Lecture 40 Introduction to Dictionaries Lecture 41 Dictionary Operations Lecture 42 Looping through Dictionaries Lecture 43 Essential Dictionary Methods Section 10: Exploring Sets in Python Lecture 44 Understanding Sets Lecture 45 Exploring Set Operations and Looping Lecture 46 Set Operations Lecture 47 Exploring Set Methods Section 11: Machine Learning with K-Nearest Neighbors Lecture 48 KNN Theory Explained Lecture 49 KNN Regression from Scratch using Python Lecture 50 KNN Classification from Scratch using Python Section 12: Machine Learning with Support Vector Machine Lecture 51 SVM Theory Explained Lecture 52 SVM Regression using Python Lecture 53 SVM Classification using Python Section 13: Machine Learning with K-Means Clustering Lecture 54 Detailed Overview of K-Means Clustering Lecture 55 K-Means Clustering using Python Beginners,Career Switchers,Students,Data Enthusiasts Homepage https://www.udemy.com/course/python-for-data-science-your-career-accelerator/ Rapidgator https://rg.to/file/0b96396af360738b70f969c9f56645d7/rkpjb.Python.For.Data.Science.Your.Career.Accelerator.part3.rar.html https://rg.to/file/560bf988f4484f5d21009ea8a33aa391/rkpjb.Python.For.Data.Science.Your.Career.Accelerator.part2.rar.html https://rg.to/file/732b91242f1e89a3d5d627f9231d28c2/rkpjb.Python.For.Data.Science.Your.Career.Accelerator.part1.rar.html https://rg.to/file/aa873b7af3d02ebdac6ed3f2b635364d/rkpjb.Python.For.Data.Science.Your.Career.Accelerator.part4.rar.html Fikper Free Download https://fikper.com/A5VoQywqSj/rkpjb.Python.For.Data.Science.Your.Career.Accelerator.part1.rar.html https://fikper.com/ngsEG1P93X/rkpjb.Python.For.Data.Science.Your.Career.Accelerator.part2.rar.html https://fikper.com/ww0lblGIhg/rkpjb.Python.For.Data.Science.Your.Career.Accelerator.part4.rar.html https://fikper.com/yJgJBFN38T/rkpjb.Python.For.Data.Science.Your.Career.Accelerator.part3.rar.html No Password - Links are Interchangeable

Free Download Python Essentials Complete Beginner's Coding Journey Published 10/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 3h 52m | Size: 1.33 GB Master Python fundamentals from scratch: Variables, loops, functions, and more for absolute coding beginners What you'll learn Install Python and set up a programming environment. Understand basic Python concepts like variables, loops, and functions. Work with data structures: lists, dictionaries, sets, and tuples. Create and manage Python projects using modules and file handling. Have access to many practice exercises and solutions along with real world projects. Requirements There are no prerequisites for this course. It's designed for complete beginners. All you need is a computer, an internet connection, and a desire to learn Python programming. Description Embark on your coding journey with our comprehensive Python course, tailored specifically for absolute beginners. No prior programming experience? Perfect! This is where your adventure begins.From the ground up, we'll guide you through:Getting Started: • Installing Python on your system • Setting up your coding environmentPython Fundamentals: • Variables and data types • Basic arithmetic operations • Understanding and writing commentsUser Interaction: • Capturing user input • Type casting for data conversionControl Flow: • Mastering if statements • Implementing logical operators • Utilizing while loops for repetitionData Structures: • Working with lists and tuples • Exploring sets and their unique properties • Harnessing the power of for loops • Organizing data with dictionaries • Introduction to arraysFunctions and Scope: • Creating and using functions • Understanding variable scopeObject-Oriented Programming: • Introduction to classes and objectsModules and File Handling: • Importing and using modules • Reading from and writing to filesThrough hands-on exercises, real-world examples, and progressive challenges, you'll build a robust foundation in Python programming. We focus on practical applications, ensuring you can apply your new skills to real coding scenarios.By the end of this course, you'll transform from a complete novice to a confident Python programmer. You'll have the skills to write your own Python scripts, tackle more advanced programming concepts, and even start building your own applications.Join thousands of successful students who have launched their programming careers with this course. Whether you're looking to enhance your job prospects, automate your daily tasks, or simply explore the exciting world of coding, this course is your perfect starting point.No more feeling intimidated by code - it's time to demystify programming and unlock your potential as a Python developer. Enroll now and take the first step towards becoming a coding champion! Who this course is for This course is perfect for complete beginners with no programming experience, students, or professionals looking to learn Python for career growth, automation, or personal projects. Anyone interested in starting their programming journey will find this course valuable. Homepage https://www.udemy.com/course/python-essentials-complete-beginners-coding-journey/ Screenshot Rapidgator https://rg.to/file/6a0839f049e0a17de6c9fde61b7846a3/datkt.Python.Essentials.Complete.Beginners.Coding.Journey.part2.rar.html https://rg.to/file/82d7a1344414960633a9a79e470552c0/datkt.Python.Essentials.Complete.Beginners.Coding.Journey.part1.rar.html Fikper Free Download https://fikper.com/QXHRGyzXJd/datkt.Python.Essentials.Complete.Beginners.Coding.Journey.part2.rar.html https://fikper.com/Qf8mTD9jFt/datkt.Python.Essentials.Complete.Beginners.Coding.Journey.part1.rar.html No Password - Links are Interchangeable

Free Download Python Data Processing and Visualization Published 10/2024 Created by Studio 01 App MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 42 Lectures ( 1h 10m ) | Size: 471 MB Master Data Manipulation and Visualization with Python What you'll learn: Understand how to manipulate data using Python's core libraries, such as Pandas and NumPy. Create compelling visualizations to communicate insights effectively using Matplotlib and Plotly. Apply data processing techniques to clean and transform data into a usable format. Gain the ability to identify data patterns and present them clearly through visual storytelling. Requirements: Basic knowledge of Python programming is recommended but not required. A willingness to learn and experiment with new tools and techniques. Description: This comprehensive course is designed to take you on an in-depth journey through the world of data processing and visualization using Python.Starting from the basics, we will introduce you to the essential concepts of data manipulation, focusing on powerful libraries like Pandas, NumPy, and others.Throughout the course, we will provide hands-on exercises and real-world examples, ensuring that you gain practical skills to work with different types of data, including structured and unstructured formats.Our focus will then shift to the art of data visualization, where you will explore how to present your data in visually engaging formats using popular libraries such as Matplotlib, Seaborn, and Plotly.The course will cover various chart types, including line charts, bar charts, histograms, scatter plots, heatmaps, and more, helping you understand when and how to use each type effectively.Whether you are a beginner looking to develop core data processing skills or an experienced professional seeking to expand your visualization toolkit, this course provides everything you need to succeed in modern data analysis.By the end of this course, you will be fully equipped to clean, process, analyze, and visualize data, providing valuable insights and making informed decisions based on your analyses. Who this course is for: Aspiring data analysts, data scientists, and professionals interested in enhancing their data processing skills. Anyone looking to improve their ability to analyze and visualize data for better decision-making. Homepage https://www.udemy.com/course/python-data-processing-visualization/ Rapidgator https://rg.to/file/604a618fe4c8df591dd19b6b1574ee13/nlrwz.Python.Data.Processing.and.Visualization.rar.html Fikper Free Download https://fikper.com/2ddzPt6TDx/nlrwz.Python.Data.Processing.and.Visualization.rar.html No Password - Links are Interchangeable

Free Download Python Bootcamp and Introduction to Artificial Intelligence Last updated 8/2024 Duration: 5h47m | Video: .MP4, 1920x1080 30 fps | Audio: AAC, 44.1 kHz, 2ch | Size: 6.78 GB Genre: eLearning | Language: English Master Python Programming and Dive into the World of AI: A Beginner-Friendly Journey from Coding Basics to AI Concepts What you'll learn Gain a strong understanding of Python, including data types, operators, control structures, functions, and classes, enabling you to write efficient and organize Apply Python concepts to solve real-world problems, automate tasks, and create projects, enhancing your logical and algorithmic thinking. Learn foundational concepts of Artificial Intelligence and Machine Learning, including key topics like supervised and unsupervised learning. Use Python libraries like TensorFlow, Keras, and scikit-learn to build, train, and evaluate basic AI models, gaining hands-on experience in AI and ML. Requirements No Prior Programming Experience Needed: This course is designed for absolute beginners, so no previous programming experience is required. We'll start from the basics and guide you through each step. Basic Computer Skills: Familiarity with using a computer, including navigating files and installing software, will be helpful but not mandatory. A Willingness to Learn: Bring your enthusiasm and curiosity! A proactive attitude towards learning will help you get the most out of the course. Access to a Computer and Internet Connection: You'll need a computer (Windows, macOS, or Linux) with internet access to download and install Python, follow along with the lessons, and practice coding. Description Welcome to the Python Bootcamp and Introduction to Artificial Intelligence , your comprehensive guide to mastering Python programming and exploring the exciting world of Artificial Intelligence. This course is designed for beginners and those with little to no programming experience who want to build a strong foundation in Python and gain an introductory understanding of AI. Throughout this course, you will Learn Python from Scratch : Start with the basics of Python programming, including variables, data types, control flow, functions, and modules. You'll build your coding skills step by step, working on real-world projects and examples. Explore Advanced Python Concepts : As you progress, you'll dive into more advanced topics such as object-oriented programming (OOP), file handling, and data manipulation. These skills will prepare you for more complex coding challenges. Introduction to AI and Machine Learning : Transition from Python programming to understanding the fundamentals of AI and Machine Learning. Learn key concepts like supervised and unsupervised learning, and discover how AI is applied in various industries. Hands-On Projects : Apply your knowledge through hands-on projects that reinforce your learning. By the end of the course, you'll have a portfolio of projects that demonstrate your skills in both Python and AI. Capstone Project : Complete a final capstone project where you'll integrate everything you've learned to solve a real-world problem using Python and AI techniques. Whether you're aiming to start a career in tech, add programming to your skillset, or simply explore the fascinating world of AI, this course is the perfect starting point. By the end, you'll be confident in your Python programming abilities and have a solid understanding of how AI works, setting you up for future success in the field. Enroll now and start your journey into Python programming and Artificial Intelligence! Who this course is for Complete Beginners: If you've never programmed before and want to start with Python, this course is designed to guide you from the very basics to more advanced concepts. Aspiring Programmers: Those interested in developing a strong foundation in Python programming as a stepping stone towards a career in software development, data science, or web development. Students and Professionals: Whether you're a student exploring programming for the first time or a professional looking to add Python and AI skills to your toolkit, this course offers practical, hands-on experience. AI and Machine Learning Enthusiasts: If you're curious about Artificial Intelligence and Machine Learning but don't know where to start, this course provides an accessible introduction to key concepts and tools. 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Free Download Python BeautifulSoup Programming with Coding Exercises Published 10/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 1h 44m | Size: 304 MB Master Web Scraping and Data Extraction with BeautifulSoup Through Practical Coding Challenges What you'll learn How to use BeautifulSoup to extract data from HTML and XML documents. Techniques for navigating and parsing complex HTML structures. Methods for cleaning and organizing scraped data for analysis. Practical experience in scraping data from various websites and handling dynamic content. Requirements Basic knowledge of Python programming. Familiarity with HTML and XML concepts is helpful but not required. Description Welcome to Python BeautifulSoup Programming with Coding Exercises, a hands-on course designed to teach you the art of web scraping using the BeautifulSoup library. BeautifulSoup is a powerful Python tool that allows you to extract data from HTML and XML documents, making it invaluable for data collection, analysis, and automation.In an increasingly data-driven world, the ability to scrape and process web data is a crucial skill. Whether you're looking to gather data for research, automate data collection tasks, or build data-driven applications, understanding how to effectively use BeautifulSoup is essential. This course is tailored to equip you with the practical skills needed to harness the full potential of web scraping.Throughout this course, you'll dive into the core concepts and techniques of BeautifulSoup, complemented by coding exercises designed to solidify your understanding. The course covers:An introduction to web scraping and BeautifulSoup, including its role in data extraction and parsing.Basics of HTML and XML structure to better understand how to navigate and extract data.Techniques for finding and extracting information from HTML documents using BeautifulSoup.How to handle and process complex data structures, including nested tags and attributes.Methods for cleaning and organizing scraped data for further analysis or use.Practical exercises on scraping data from various websites, including handling dynamic content and form submissions.Strategies for respecting website terms of service and ethical considerations in web scraping.By the end of the course, you will have a strong grasp of web scraping fundamentals and practical experience with BeautifulSoup, empowering you to efficiently gather and analyze data from the web.Instructor Introduction: Your instructor, Faisal Zamir, brings over 7 years of experience in teaching Python and web scraping techniques. As an accomplished Python developer and educator, Faisal provides a clear and engaging approach to learning BeautifulSoup, ensuring you gain both theoretical knowledge and practical skills.Certificate at the End of Course: Upon successful completion of the course, you will receive a certificate that validates your skills in web scraping with BeautifulSoup, adding value to your professional credentials. Who this course is for Data enthusiasts and analysts looking to automate data collection from the web. Python developers interested in learning web scraping techniques. Individuals aiming to build skills in data extraction and processing for research or projects. Homepage https://www.udemy.com/course/python-beautifulsoup-programming-with-coding-exercises/ Screenshot Rapidgator https://rg.to/file/8b8a8b7ac4d63fa2212adfe7c234ba36/byrog.Python.BeautifulSoup.Programming.with.Coding.Exercises.rar.html Fikper Free Download https://fikper.com/DCNFcGv5pC/byrog.Python.BeautifulSoup.Programming.with.Coding.Exercises.rar.html No Password - Links are Interchangeable

Free Download Pluralsight - Playwright Foundations with Python Published 10/2024 Duration: 3h 35m | Video: .MP4, 1920x1080 30 fps | Audio: AAC, 48 kHz, 2ch | Size: 680 MB Genre: eLearning | Language: English Starting a new end-to-end test automation project? This course will teach you how to test web applications using the open-source tool Playwright with Python. Try it and never look back! Automated tests undeniably help protect the quality of software projects, and end-to-end tests are an important part of it. In this course, Playwright Foundations with Python, you will learn how to write automated tests for web applications. Homepage https://www.pluralsight.com/courses/playwright-foundations-python Screenshot Rapidgator https://rg.to/file/b0ef88083bed65e266dbf1ebf79ae414/rbngc.Playwright.Foundations.with.Python.rar.html Fikper Free Download https://fikper.com/rIciaAummc/rbngc.Playwright.Foundations.with.Python.rar.html No Password - Links are Interchangeable

Free Download Pivot Tables With Python Pandas Full Course Published 10/2024 Created by Kichere Magubu MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 8 Lectures ( 1h 39m ) | Size: 485 MB Master Data Analysis with Pivot Tables in Python Using Pandas. What you'll learn pivot() method in pandas pivot_table() method in pandas pivot_table() vs pivot() methods. Data analysis with pivot tables Requirements Desire to Learn: A strong willingness to engage with the course material and practice new skills in data analysis. Preferred Tools: A working installation of Python, preferably using Jupyter Lab or jupyter Notebook, for an interactive Description Learn how to use Pivot Tables in Python with Pandas to analyze and summarize data easily. This course is for anyone working with large datasets who wants to improve their data analysis skills. Whether you're a student, a data enthusiast, or a professional in the field, this course will provide you with the essential tools and techniques needed to unlock insights from your data.In this course, you will:Understand what pivot tables are and how they simplify data.Use Pandas' pivot() method for simple data reshaping.Use Pandas' pivot_table() to quickly summarize data.Group, filter, and organize data for better insights.Work with multi-level pivoting and large datasets.Practice with real-world examples to reinforce your learning.Additionally, you will learn best practices for data manipulation and visualization, ensuring you can present your findings effectively. The hands-on projects will enable you to apply the concepts learned throughout the course in practical scenarios, enhancing your understanding of data analytics. By the end, you'll know how to use pivot tables to make complex data easier to analyze, whether you're a beginner or an experienced analyst looking to refine your skills. Join us and take your data analysis expertise to the next level! Who this course is for Individuals new to data analysis and those with experience in Python. Aspiring data analysts and professionals seeking to enhance their data skills. Students and researchers looking to analyze datasets. Python enthusiasts interested in data manipulation and analysis. Homepage https://www.udemy.com/course/pivot-tables-with-python-pandas-full-course-o/ Screenshot Rapidgator https://rg.to/file/26cbadca1de6ce566e749b32b67125b3/bbkpa.Pivot.Tables.With.Python.Pandas.Full.Course.rar.html Fikper Free Download https://fikper.com/r24V41FJ4R/bbkpa.Pivot.Tables.With.Python.Pandas.Full.Course.rar.html No Password - Links are Interchangeable

Free Download Modern Web Scraping with Python using Scrapy Splash Selenium Last updated 5/2021 Created by Ahmed Rafik MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + subtitle | Duration: 128 Lectures ( 8h 50m ) | Size: 3.1 GB Become an expert in web scraping and web crawling using Python 3, Scrapy, Splash and Selenium 2nd EDITION (2021) What you'll learn Understand the fundamentals of Web Scraping Scrape websites using Scrapy Understand Xpath & CSS Selectors Build a complete Spider from A to Z Store the extracted Data in MongoDb & SQLite3 Scrape JavaScript websites using Splash & Selenium Build a CrawlSpider Understand the Crawling behavior Build a custom Middleware Web Scraping best practices Avoid getting banned while scraping websites Bypass cloudflare Scrape APIs Scrape infinite scroll websites Working with Cookies Deploy spiders locally and to the cloud Run spiders periodically Prevent storing duplicated data Build datasets Login to websites using Scrapy Download images and files using Scrapy Requirements Basics of Python Internet access Description Web Scraping nowadays has become one of the hottest topics, there are plenty of paid tools out there in the market that don't show you anything how things are done as you will be always limited to their functionalities as a consumer.In this course you won't be a consumer anymore, i'll teach you how you can build your own scraping tool ( spider ) using Scrapy.You will learn: The fundamentals of Web ScrapingHow to build a complete spiderThe fundamentals of XPath & CSS SelectorsHow to locate content/nodes from the DOM using XPath & CSSHow to store the data in JSON, CSV... and even to an external database(MongoDb & SQLite3)How to write your own custom PipelineFundamentals of SplashHow to scrape Javascript websites using Scrapy Splash & SeleniumThe Crawling behaviorHow to build a CrawlSpiderHow to avoid getting banned while scraping websitesHow to build a custom MiddlewareWeb Scraping best practicesHow to scrape APIsHow to use Request CookiesHow to scrape infinite scroll websitesHost spiders in Heroku for freeRun spiders periodically with a custom scriptPrevent storing duplicated dataDeploy Splash to Heroku Write data to Excel files Login to websites using ScrapyDownload Files & Images using ScrapyUse Proxies with Scrapy SpiderUse Crawlera with Scrapy & SplashUse Proxies with CrawlSpiderWhat makes this course different from the others, and why you should enroll ?First, this is the most updated course. You will be using Python 3.7, Scrapy 1.6 and Splash 3.0You will have an in-depth step by step guide on how to become a professional web scraper. You will learn how to use Splash & Selenium to scrape JavaScript websites and I can assure you, you won't find any tutorials out there that teaches how to really use Splash like I'll be doing in this course.You will learn how to host spiders in Heroku as well as Splash(Exclusive).You will learn how to create a custom script so spiders can run periodically without any intervention from you.30 days money back guarantee by Udemy So whether you are a data analyst who wants to add web scraping to his tool set or someone else who wants to learn how to extract unstructured data from unstructured HTML web pages and then store back that data in a structured way to apply some data analysis on it then you are welcome to join this course.**STUDENTS THOUGHTS ABOUT THIS COURSE **"I was particularly looking for web scraping using XPATHs and this course is addressing that. It also covers dynamic paging. A proper mix of theory and practical. A must-have for those who wants to do web scraping . GREAT learning experience !!! ". By Hiran Kumar"90% of what I was searching for!!! Great job!! Clear explanations and great communication with Ahmed". By Raylyson Estanista "Admed's Web scraping course is awesome . His approach using Python with scrapy and splash works well with all websites especially those that make heavy use of JavaScript. Ahmed is a gifted educator: expert communicator, passionate, conscientious and accessible to his students. I highly recommend this course and any of Ahmed Rafik's Udemy courses. ". By Richard Blackmon"Great course, and a nice introduction to Scrapy (I'm someone with no Python experience whatsoever).". By I S"Excellent course. Quick and thorough at the same time. Ahmed is incredibly responsive to the students and often replies to questions within minutes! Highest recommendation." By Robert Nolte"That course is very good and explanation is crystal clear! The instructor is very supportive in case of questions. Highly recommended." By Shubina Ekaterina "I like the course. Clear explanations and good comunication with Ahmed. All topics is interesting and full of information. I improved my skils in Scrapy. Author update course content by new videos. It's a big bonus) Explained more advance topics I never see in other courses. Thank you, Ahmed. Waiting for new videos)". 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