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Free Download Python For Beginners - Learn The Fundamentals (2024) Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 247.87 MB | Duration: 1h 0m Discover Python fundamentals, including variables, control flow, functions, and lists. What you'll learn Python Basics Detail understanding of fundamentals Google Colab Programming Practical Examples, Quizes and Assignments Requirements No previous programming experience needed Description Hello! Have you ever wondered why Python has become one of the most popular programming languages today? Many students dive into Python but struggle with concepts and practical applications due to gaps in their understanding. You're in the right place to master the complete Python programming language!Why Python?Python is in high demand in the job market. Companies like Google, Facebook, NASA, and IBM offer attractive salaries to skilled Python developers. Choosing Python means you're stepping into a powerful and versatile programming world!Why This Course?This course is designed by an instructor with over five years of experience in Python programming and freelancing. The curriculum is structured to cover every essential aspect of Python thoroughly, ensuring you grasp the language completely. By the end of this course, you'll be well on your way to becoming a professional Python programmer!What Can You Achieve After Learning Python?Become an AI ExpertExplore Ethical HackingWork as a Data ScientistDevelop SoftwareCreate Mobile AppsBuild Web ApplicationsFreelance in techWhat Will You Learn in This Course?Master Python 3Gain professional skills necessary for jobs and freelance opportunitiesUnderstand how to create your own programs and softwareWrite Python programs that take user input, process it, and provide outputUtilize loops, conditionals, and functions effectivelyDevelop a solid understanding of Python codeSo, what are you waiting for? Let's start your Python journey together! Join our coding community, and I can't wait to see you in the first video lecture!Happy Coding! Overview Section 1: Introduction Lecture 1 Introduction Lecture 2 Why Google Colab? Section 2: Building Basics Lecture 3 Variables Lecture 4 Commenting your code Lecture 5 Lists Lecture 6 Sets Lecture 7 Tuples Lecture 8 Dictionaries Section 3: Logic Building Lecture 9 Flow Control Statements Lecture 10 For Loop Lecture 11 While Loop Section 4: Functions Lecture 12 Functions in Python Everyone Homepage https://www.udemy.com/course/python-for-beginners-learn-the-fundamentals/ Rapidgator https://rg.to/file/b1000d0ea52dc9807472970a5afa0e51/hfovo.Python.For.Beginners..Learn.The.Fundamentals.2024.rar.html Fikper Free Download https://fikper.com/gTZoG2IH6J/hfovo.Python.For.Beginners..Learn.The.Fundamentals.2024.rar.html No Password - Links are Interchangeable

Free Download Python & Gen AI Basics Transition from Java in Just 15 days Published 9/2024 Created by Arul Benjamin Chandru Ebenezer Vedanayagam MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 15 Lectures ( 16h 48m ) | Size: 7.2 GB Unlock Python and Generative AI Basics with Java Concepts in Just 15 Days What you'll learn: Key comparisons between Java and Python: Syntax, variables, loops, and data structures How to transition your Java skills to Python programming Building Python projects with real-world applications Fundamentals of Generative AI and how to apply them in everyday tasks Practical coding challenges with a focus on Python's simplicity compared to Java Requirements: Basic Java knowledge is helpful but not required. If you're familiar with Java, you'll appreciate the comparisons that make transitioning to Python easier. No prior experience with Python or Generative AI is needed-we'll cover everything from the ground up. A computer with internet access to follow along and run Python code (preferably using Google Colab). Curiosity and a willingness to learn Python and AI in a storytelling, engaging format! Description: Curious about Python programming and Generative AI but not sure where to start? This 15-day beginner-friendly course is designed to take you from zero to confidently building AI-powered projects-all through a practical, storytelling approach! If you're familiar with Java, we'll make it even easier by comparing concepts between the two languages, helping you transition smoothly.From mastering Python fundamentals to exploring popular AI tools like ChatGPT and DALL-E, this course covers everything you need to start working with AI without writing complex code. 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Free Download Complete Data Science With Python Course From Iibm Institute Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 7.76 GB | Duration: 12h 20m Data Science with Python Course for Beginners | Online Course What you'll learn Proficient Data Handling. Effective Data Visualization. Learner's Gain a solid understanding of key statistical concepts and techniques. End-to-End Project Execution. Requirements Good programming knowledge, introductory statistics, a computer, and Python with relevant libraries installed. Description The Data Science with Python course is an extensive program designed to provide a solid foundation in the essential concepts and techniques of data science. This course is perfect for beginners and those with some programming experience looking to deepen their understanding of data analysis and visualization.Throughout the course, you will engage with powerful Python libraries such as Pandas and NumPy, which are crucial for data manipulation and analysis. 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Join us to embark on your journey into the fascinating world of data science and unlock its potential!IIBM Institute of Business Management Overview Section 1: Data Science With Python Lecture 1 Introduction Lecture 2 Data Science Application Across Multiple Domain and Business Function Lecture 3 Data Science Project LifeCycle Lecture 4 Multiple Predictive Model Using Python Lecture 5 Python - Simple and Multiple Predictive Model in Practical Lecture 6 Assignment - Real Estate Predictive Analysis Lecture 7 Python Correlation Analysis Lecture 8 Data Science - Questionnaire Design Process Lecture 9 Python Classification Model Building Lecture 10 Data Science - Experimental Design Analysis Lecture 11 Classification Technique - Discriminant Analysis Lecture 12 Data Science - Association Rule - Apriori Algorithm Lecture 0 Data Science - Building Recommendation System - Market Basket Analysis(MBA) Lecture 13 Data Architecture Design, Data Warehousing and it's Schema Design Aspiring data scientists, analysts, students, and business professionals interested in data. 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Free Download Udemy - Python for SEO & Content Marketing Published 9/2024 Created by Emmanuel Dan-Awoh MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + subtitle | Duration: 29 Lectures ( 3h 5m ) | Size: 1.71 GB Python Scripts For SEO and Content Marketing Automation What you'll learn: How to use Python to interact with the Google Indexing API for faster website crawls and indexing. Automation tips to simplify repetitive SEO tasks Techniques to leverage Python for SEO analytics, Content marketing and reporting. Use various APIs (Wikipedia, Copyscape, Wayback Machine, PageSpeed Insights) with Python for marketing and content tasks. Detecting and resolving keyword cannibalization and rendering issues at scale. Execute Python scripts for complex SEO tasks such as internal linking, crawl budget management, and content clustering. Requirements: No Programming Experience Required. You wlll learn everything you need to know Description: Are you ready to revolutionize your SEO strategy? Welcome to this course on SEO Automation with Python Scripts, where you will learn to harness the full potential of Python to automate your SEO and content tasks, improve efficiency, and achieve superior results.In the fast-paced world of digital marketing, staying ahead of the competition is vital. With this course on SEO Automation with Python Scripts, you will:Automate repetitive SEO tasks and save valuable time.Master advanced Python scripts specifically designed for SEO.Enhance your website's performance and visibility on search engines.Stay competitive with the latest SEO automation techniques.The course is structured into modules, each focusing on specific SEO automation techniques using Python.This course is perfect for:SEO Professionals looking to streamline their workflows.Python Enthusiasts eager to apply their skills to SEO.Marketers and Website Owners aiming to boost their search engine rankings.By the end of this course, parti[beeep]nts will be able to:Automate the creation and management of meta descriptions.Use various APIs (Wikipedia, Copyscape, Wayback Machine, PageSpeed Insights) with Python for SEO tasks.Detecting and resolving keyword cannibalization and rendering issues at scale.Analyze and optimize website performance using Python scripts.Develop and execute Python scripts for complex SEO tasks such as internal linking, crawl budget management, and content clustering.Don't miss this opportunity to transform your SEO strategy with Python automation Who this course is for: SEO Professionals looking to automate their workflows and save time Marketers and Website Owners aiming to boost their search engine rankings. Content Marketers & Writers who want to keep up, standout and deliver results faster Homepage https://www.udemy.com/course/python-for-seo-and-content-automation/ Rapidgator https://rg.to/file/dfde3306836f87b4a9f9d638a3ffdba5/znzdy.Python.for.SEO..Content.Marketing.part1.rar.html https://rg.to/file/8800edb4e8ccdea62152a0392d3a0a03/znzdy.Python.for.SEO..Content.Marketing.part2.rar.html Fikper Free Download https://fikper.com/u0EsrCgB6Q/znzdy.Python.for.SEO..Content.Marketing.part1.rar.html https://fikper.com/JjiMLdiGKC/znzdy.Python.for.SEO..Content.Marketing.part2.rar.html No Password - Links are Interchangeable

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Free Download Python For Data Science - A Comprehensive Journey To Mastery Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 898.02 MB | Duration: 4h 55m Mastering Python, Data Analysis, and Machine Learning What you'll learn Python syntax, data structures, and libraries essential for data science, such as NumPy and Pandas. Learn how to clean, organize, and transform raw data into usable formats for analysis and visualization. Understand how to explore datasets to identify patterns, trends, and relationships. Build predictive models using Scikit-learn, covering supervised learning algorithms. Develop critical thinking and analytical skills to solve complex data challenges. Requirements Students should be comfortable using a computer, navigating files, and installing software. This course is designed for absolute beginners, so no prior experience in Python or programming is necessary. A positive attitude, curiosity, and the drive to learn new concepts and solve problems are essential. Description Unlock the power of data with our comprehensive Python for Data Science course!Expertly crafted to suit both beginners and experienced professionals, this course will guide you from the basics to advanced mastery in Python, a programming language that continues to dominate the data science landscape. Starting with fundamental concepts, you'll become proficient in Python's syntax and core libraries, and gradually progress to more advanced topics such as data manipulation, visualization, machine learning, and predictive modeling.Our course is rooted in practical, hands-on learning, allowing you to work with real-world datasets and develop models that can drive meaningful decision-making. 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Overview Section 1: Introduction Lecture 1 Introduction Section 2: Data types, operators and data structures in Python Lecture 2 Python Data Types Lecture 3 Operators Lecture 4 Arithmatic Operators Lecture 5 Assignment Operators Lecture 6 Comparison Operators Lecture 7 More on Strings Lecture 8 String Methods Lecture 9 Lists Lecture 10 Tuples Lecture 11 Sets Lecture 12 Dictionaries Lecture 13 Identity Operators Lecture 14 Compound Data Structures Section 3: Python Loops and Comprehensions Lecture 15 Python loops Lecture 16 Range Understanding Lecture 17 Creating and Modifying Lists Lecture 18 Looping Through Dictionaries Lecture 19 Enumerate Function Lecture 20 List Comprehentions Lecture 21 Adding Conditionals to List Comprehentions Section 4: Comprehensive Guide to Python Functions Lecture 22 Python Functions Lecture 23 Functions Parameters Lecture 24 Return values Lecture 25 Default Parameters Lecture 26 Variable-Length Arguments Lecture 27 Lambda Functions Lecture 28 Higher Order Functions Lecture 29 Recursive Functions Lecture 30 Docstrings Lecture 31 Functions Annotations Lecture 32 Nested Functions Lecture 33 Decorators Section 5: NumPy for Efficient Numerical Computations Lecture 34 Introduction to numpy Lecture 35 Array Attributes Lecture 36 Array Indexing and Slicing Lecture 37 Array Operations Lecture 38 Reshaping Arrays Lecture 39 Stacking and Splitting Arrays Lecture 40 Splitting Arrays Lecture 41 Broadcasting Lecture 42 Boolean Indexing and Filtering Lecture 43 Advanced Array Manipulations Section 6: Data Manipulation with Pandas: A Comprehensive Guide Lecture 44 Introduction to Pandas Lecture 45 Pandas Series Lecture 46 Pandas DataFames Lecture 47 Loading Data Into a DataFrame Lecture 48 Handling Missing Data (NaN Values) Lecture 49 Basic DataFrame Operations Lecture 50 Grouping Data in Pandas Lecture 51 Merging and Joining DataFrames Lecture 52 Data Cleaning Section 7: Hands-On Machine Learning: Exploring Scikit-Learn Lecture 53 Introduction to Machine Learning and Scikit-learn Lecture 54 Data Preprocessing Lecture 55 Handling Missing Values Lecture 56 Features Scaling Lecture 57 Encoding Categorical Variables Lecture 58 Decision Trees Lecture 59 Support Vector Machine Beginners: Individuals with no prior programming or data science experience who want to learn Python and data science from scratch.,Aspiring Data Scientists: Those looking to break into the data science field and build foundational skills needed for a successful career.,Software Engineers: Programmers or engineers who want to expand their knowledge into data analysis, machine learning, and data science techniques.,Data Analysts: Professionals looking to upgrade their Python skills to analyze and visualize data more efficiently.,College Students: Students pursuing degrees in fields such as computer science, statistics, or economics who want to strengthen their data science and Python skills.,Business Analysts: Professionals seeking to use data to drive better decision-making and extract actionable insights from datasets.,Professionals from Other Fields: Individuals from various industries (marketing, finance, healthcare, etc.) who want to enhance their analytical abilities and leverage data science in their work.,Entrepreneurs & Freelancers: Those who want to utilize data science to grow their business, gain insights into customer behavior, or enhance their services. 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Free Download Python For Beginners - Master The Basics In 1 Hour Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 194.47 MB | Duration: 1h 7m Python Essentials: Learn the Basics of Programming in Just 1 Hour What you'll learn Students will grasp the core concepts of Python, including variables, data types, loops, and conditionals, enabling them to write basic Python programs. Learners will be able to define and use functions to create reusable blocks of code, enhancing the modularity and efficiency of their programs. Students will gain proficiency in using Python's list data structure to store, access and manipulate collections of data, allowing them to handle multiple value By working on practical exercises and real-world projects, learners will sharpen their problem-solving abilities, applying Python to create a simple game. Requirements No Prior Programming Experience Needed Basic Computer Skills A Computer (PC or Mac) Internet Access Willingness to Learn Description Welcome to "Python for Beginners: Master the Basics in 1 Hour"! This course is designed to help absolute beginners kickstart their journey into the world of programming using Python, one of the most powerful and versatile programming languages available today.Whether you're completely new to coding or have a little experience, this course will teach you Python step-by-step with clear explanations and hands-on exercises. By the end of this course, you'll have a solid understanding of Python basics, allowing you to write your own simple programs and tackle real-world problems.What You'll Learn:Understand fundamental programming concepts like variables, data types, and control flow.Use Python lists to store and manipulate data.Create and use functions to write clean and reusable code.Build basic programs, including a To-Do List and Guess the Number game.Handle user input, loops, and conditions to add logic to your programs.Why Take This Course?Beginner-Friendly: No prior coding experience required.Practical Learning: Work on real-world examples and projects.Clear, Easy-to-Follow Explanations: Learn at your own pace with guided tutorials.Short, Concise Content: Gain essential Python skills in just 1 hour.Who This Course is For:Absolute beginners with no programming experience.Aspiring developers who want to start learning Python.Students and professionals looking to add Python to their skill set.Anyone interested in using Python to automate tasks or solve problems.What You'll Need:A computer (PC or Mac) and internet access to download Python.A passion for learning and problem-solving! Overview Section 1: Introduction Lecture 1 Introduction Lecture 2 What is Covered in this Course? Section 2: Getting Started Lecture 3 Online Compiler Lecture 4 Syntax: Variables and Comments Lecture 5 Mathematical Operations Section 3: Control Flow Lecture 6 If Statement Lecture 7 Loops Lecture 8 Functions Section 4: Data Structures Lecture 9 Lists Section 5: Error Handling Lecture 10 Handling Errors in the code and fixing it Section 6: Practice Lecture 11 Create Guess the number game Complete Beginners to Programming,Aspiring Developers,Students or Professionals Switching to Python Homepage https://www.udemy.com/course/python-for-beginners-master-the-basics-in-1-hour/ Rapidgator https://rg.to/file/14aa9b7f560d30b7c6ab95545e604028/uizjp.Python.For.Beginners.Master.The.Basics.In.1.Hour.rar.html Fikper Free Download https://fikper.com/1hkjVqbDEz/uizjp.Python.For.Beginners.Master.The.Basics.In.1.Hour.rar.html No Password - Links are Interchangeable

Free Download Data Wrangling with Python 3 Duration: 1h 20m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 48 kHz, 2ch | Size: 304 MB Genre: eLearning | Language: English In this course, Data Wrangling with Python 3, you'll learn about various functions and procedures that will help you get your data in order, providing a clean and well-constructed dataset for further data analysis and machine learning. Machine Learning and Data analytics in general follows the garbage-in/garbage-out principle. If you want to learn from or predict based on your data, you need to make sure that data is well constructed and cleaned. This course, Data Wrangling with Python 3, is aimed at helping you do exactly that. First, you'll see how to merge data from different sources using the methods concat, append, and merge. Next, you'll discover how to combine data into groups. The primary function used here is groupby. In the next two sections, you'll explore how to transform and normalize data. You'll learn why these processes are necessary, and then proceed to see how they work in practice. Finally, you'll examine important processes such as One Hot Encoding, which enables further processing during data analysis. When you're finished with this course, you'll have thorough knowledge of data wrangling which will help you immensely during your data analysis and machine learning projects. Homepage https://www.pluralsight.com/courses/data-wrangling-python TakeFile https://takefile.link/zoqwpe8g9sed/ddmsr.Data.Wrangling.with.Python.3.rar.html Rapidgator https://rg.to/file/0f131e085d285eaaefc22e2e2132ba4c/ddmsr.Data.Wrangling.with.Python.3.rar.html Fikper Free Download https://fikper.com/7HgUFd95ix/ddmsr.Data.Wrangling.with.Python.3.rar.html No Password - Links are Interchangeable

Free Download Coursera - Python 3 Programming Specialization Last updated 9/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + subtitle | Duration: 295 lessons ( 28h 36m ) | Size: 4.7 GB Become a Fluent Python Programmer. Learn the fundamentals and become an independent programmer. What you'll learn Learn Python 3 basics, from the basics to more advanced concepts like lists and functions. Practice and become skilled at solving problems and fixing errors in your code. Gain the ability to write programs that fetch data from internet APIs and extract useful information. Skills you'll gain Json Computer Programming Python Programming Sorting This specialization teaches the fundamentals of programming in Python 3. We will begin at the beginning, with variables, conditionals, and loops, and get to some intermediate material like keyword parameters, list comprehensions, lambda expressions, and class inheritance. You will have lots of opportunities to practice. You will also learn ways to reason about program execution, so that it is no longer mysterious and you are able to debug programs when they don't work. By the end of the specialization, you'll be writing programs that query Internet APIs for data and extract useful information from them. And you'll be able to learn to use new modules and APIs on your own by reading the documentation. That will give you a great launch toward being an independent Python programmer. This specialization is a good next step for you if you have completed Python for Everybody but want a more in-depth treatment of Python fundamentals and more practice, so that you can proceed with confidence to specializations like Applied Data Science with Python . But it is also appropriate as a first set of courses in Python if you are already familiar with some other programming language, or if you are up for the challenge of diving in head-first. Applied Learning Project By the end of the second course, you will create a simple sentiment analyzer that counts the number of positive and negative words in tweets. In the third course, you will mash up two APIs to create a movie recommender. The final course, Python Project: pillow, tesseract, and opencv (Course 5), is an extended project in which you'll perform optical character recognition (OCR) and object detection in images. Homepage https://www.coursera.org/specializations/python-3-programming TakeFile https://takefile.link/a3img3ofabso/xzeyn.Coursera..Python.3.Programming.Specialization.part1.rar.html https://takefile.link/44y9daqqjz3k/xzeyn.Coursera..Python.3.Programming.Specialization.part2.rar.html https://takefile.link/mrsg1jo7dgae/xzeyn.Coursera..Python.3.Programming.Specialization.part3.rar.html https://takefile.link/2tqkyo592jim/xzeyn.Coursera..Python.3.Programming.Specialization.part4.rar.html https://takefile.link/yu96g8419owr/xzeyn.Coursera..Python.3.Programming.Specialization.part5.rar.html Rapidgator http://peeplink.in/fbc05f03b5e0 Fikper Free Download https://fikper.com/go81yCruWf/xzeyn.Coursera..Python.3.Programming.Specialization.part1.rar.html https://fikper.com/ytoWgjAWhb/xzeyn.Coursera..Python.3.Programming.Specialization.part2.rar.html https://fikper.com/ZNcV0hpXz3/xzeyn.Coursera..Python.3.Programming.Specialization.part3.rar.html https://fikper.com/XiWlyHe18v/xzeyn.Coursera..Python.3.Programming.Specialization.part4.rar.html https://fikper.com/uil1sbmN1e/xzeyn.Coursera..Python.3.Programming.Specialization.part5.rar.html No Password - Links are Interchangeable

Free Download Complete Python With DSA Bootcamp + LEETCODE Exercises Published 9/2024 Created by Krish Naik,Mayank Aggarwal,KRISHAI Technologies Private Limited MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 171 Lectures ( 41h 47m ) | Size: 19.7 GB Master Python and Data Structures with Hands-on Projects and Coding Challenges for Tech Interviews and Beyond! What you'll learn: Develop a solid foundation in Python, including syntax, data structures, and libraries, enabling learners to write efficient and clean code. Gain a comprehensive understanding of fundamental data structures (such as arrays, linked lists, stacks, queues, trees, and graphs) and algorithms Learn how to apply data structures and algorithms to solve practical problems, enhancing coding skills and preparing learners for technical interviews Build confidence in solving coding challenges and improve problem-solving skills through hands-on exercises and interview-style questions Requirements: Basic understanding of programming concepts (variables, loops, and conditionals). Familiarity with Python syntax (data types, functions, and modules). No prior knowledge of data structures or algorithms is required; eagerness to learn is essential. Description: Welcome to the "Complete Python with DSA Bootcamp"! This comprehensive course is designed to take you from a beginner to a confident programmer, mastering both Python and essential data structures and algorithms (DSA) needed for technical interviews and real-world applications.What You Will LearnIn this bootcamp, you will start with the fundamentals of Python programming. You will become familiar with Python syntax, data types, control structures, and functions. As you progress, you will dive into more advanced topics, including object-oriented programming and error handling, ensuring you have a solid foundation before moving on to data structures.Next, we will explore various data structures in detail. You will learn about arrays, lists, stacks, queues, linked lists, trees, and graphs. For each data structure, you will understand its use cases, advantages, and limitations. 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Free Download Advanced Analysis Using Python in Excel Copilot Released 9/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill Level: Intermediate | Genre: eLearning | Language: English + srt | Duration: 18m | Size: 48 MB The advanced analysis capabilities of Copilot in Excel allow you to leverage the power of the Microsoft Copilot generative AI assistant to build Python code and solutions right within Excel. With Python and Excel Copilot, you can ask questions about your data in a conversational manner, allowing you to shape outputs and insights to meet your specific needs. Join instructor Scott Simpson in this quick look at the new capabilities introduced with Excel Copilot, including how to use it for advanced analysis, analyzing real-world data, and transforming and plotting geodata. Homepage https://www.linkedin.com/learning/advanced-analysis-using-python-in-excel-copilot TakeFile https://takefile.link/c7s17j45uzxi/iukpf.Advanced.Analysis.Using.Python.in.Excel.Copilot.rar.html Rapidgator https://rg.to/file/45cdc0d25dac7a1197deef65f0ae0bd6/iukpf.Advanced.Analysis.Using.Python.in.Excel.Copilot.rar.html Fikper Free Download https://fikper.com/HupEZT7Y4C/iukpf.Advanced.Analysis.Using.Python.in.Excel.Copilot.rar.html No Password - Links are Interchangeable

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Free Download Python for Engineers, Scientists and Analysts Published 9/2024 Created by Harry Munro MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 11 Lectures ( 1h 36m ) | Size: 789 MB Introduction to Data Analysis, Statistics, Modelling and Visualisation What you'll learn: Learn how to install and run Python on your computer Write and execute basic Python scripts. Import data from CSV files and other formats. Utilise libraries such as Pandas for data manipulation and exploration. Apply statistical methods to analyse data (e.g., mean, median, standard deviation). Calculate and interpret descriptive statistics using Python libraries. Apply advanced statistical measures such as percentiles and interquartile range to gain deeper insights into data variability. Create new data using mathematical and statistical models. Simulate real-world scenarios using models in Python. 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The lessons are concise and focused, ensuring you can acquire the knowledge and skills you need efficiently.While covering fundamental Python programming and data analysis techniques, this course is intentionally designed to avoid more advanced topics such as machine learning, object-oriented programming, and complex Boolean operations-allowing you to focus on practical skills that can be applied immediately.What You'll Learn:How to install Python and set up your programming environment efficientlyImporting, cleaning, and manipulating datasets using libraries such as PandasPerforming advanced statistical analysis, including outlier detection, percentiles, and interquartile rangesVisualising data using professional charts and graphs with Matplotlib and SeabornBuilding mathematical models for data simulation and predictionWriting efficient, reusable Python code to solve real-world problemsApplying Python to fields such as engineering, finance, manufacturing, and scientific researchWhy Take This Course?Practical and Immediate Value: The course is designed to deliver skills that can be applied immediately in your professional or academic work.Hands-on Learning: Engage with interactive coding exercises, downloadable code, and real-world projects that enable you to apply what you learn.Accessible for All Levels: Whether you are new to Python or seeking to refine your skills, this course is structured to accommodate learners at all levels.High-Quality Content: Enjoy well-organised lessons, quizzes, and downloadable resources that facilitate effective learning.What This Course Does NOT Cover: This course provides a strong foundation in Python for data analysis, modelling, and visualisation, but it does not cover the following advanced topics:Iterables and GeneratorsAdvanced Boolean OperationsObject-Oriented Programming (OOP)Machine Learning or Deep LearningAdvanced Big Data Libraries such as Dask or PySparkConcurrency and ParallelismAdvanced simulation techniques such as discrete-event simulation or agent-based modellingThis course is designed to equip you with immediate, actionable skills that can be applied directly to real-world challenges. 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Free Download Build a Modern Contact Form with Python ,Flask and Oracle Last updated 8/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 2h 1m | Size: 511 MB Create Responsive, Data-Driven Web Applications Using Pthon,Flask,HTML.CSS,JavaScript and Oracle What you'll learn Understand Flask Framework: Describe the basic architecture and design philosophy of the Flask web framework. Install and configure the Flask development environment Implement URL routing in a Flask application, including the use of dynamic routes. Handle web forms, process form data, and validate user input in Flask applications. Connect Flask applications to databases using SQLAlchemy Develop API endpoints with Flask to handle form submissions and database interactions. Integrate JavaScript to handle dynamic behaviors and interactions on the frontend. Build a user-friendly and responsive web form using HTML, CSS, and Bootstrap. Build the backend for the app with Python and Flask Requirements Understanding of Python syntax and programming concepts Basic knowledge of HTML for structuring web content. Understanding of CSS for styling web pages. Familiarity with JavaScript basics, including syntax, variables, and functions. Understanding of how to use JavaScript for simple client-side interactions. A computer (Windows, macOS, or Linux) A stable internet connection for downloading necessary software A code editor such as Visual Studio Code, Sublime Text, or an integrated development environment (IDE) like PyCharm. Description Welcome to "Build a Modern Contact Form with Python ,Flask and Oracle." This course is designed for aspiring web developers, software engineers, and anyone interested in building dynamic, scalable, and efficient web applications using the Flask framework. Whether you are new to web development or looking to enhance your skills, this course will guide you through the essentials of Flask, helping you to create powerful, user-friendly web applications.Flask, a lightweight and flexible Python web framework, is known for its simplicity and ease of use. It offers developers the freedom to design web applications with minimal overhead, making it an excellent choice for both beginners and professionals. Throughout this course, you'll dive deep into Flask's core concepts, from setting up your development environment to deploying your application in a production environment.We begin with the fundamentals of Flask, covering essential topics such as routing, handling HTTP requests, and using Jinja2 for dynamic content rendering. You'll learn how to manage user sessions, work with forms, and validate input to ensure robust application security. As you progress, the course will introduce you to more advanced concepts, including database integration with SQLAlchemy, building RESTful APIs, and implementing user authentication and role management.The application will interact with a backend Oracle database . Oracle 21c is a cutting-edge version of Oracle's database management system that introduces a wide range of new features and enhancements, focusing on automation, performance, and support for modern data types and workloads. Whether used in the cloud or on-premises, Oracle 21c provides a robust platform for enterprises looking to leverage the latest database technologies.By the end of this course, you will have the knowledge and skills to build and deploy full-featured web applications. Join us on this journey to becoming proficient in Flask. By mastering this powerful framework, you'll be well-equipped to create sophisticated web applications that meet modern development standards and provide value to users and clients alike. Who this course is for Aspiring Web Developers Tech Enthusiasts Frontend developers who want to gain a better understanding of backend processes and how to connect their frontend code to a backend server Individuals with a passion for technology and web development who enjoy learning new skills and building personal projects Hobbyists who want to create their own web applications and understand the full development lifecycle. Students studying computer science or related fields who want to supplement their academic learning with practical, real-world projects. Homepage https://www.udemy.com/course/build-a-modern-contact-form-with-python-flask-and-oracle/ Rapidgator https://rg.to/file/e2d012699c53e92ee43a624c273ce020/yydye.Build.a.Modern.Contact.Form.with.Python.Flask.and.Oracle.rar.html Fikper Free Download https://fikper.com/34e5QxmxBM/yydye.Build.a.Modern.Contact.Form.with.Python.Flask.and.Oracle.rar.html No Password - Links are Interchangeable

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Free Download Ultimate Python Pro Bootcamp-Job Ready Training Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 7.83 GB | Duration: 24h 15m Become a master in Python and gain hands-on experience and level up your career In Tech What you'll learn You will be able and capable to program in Python professionally You will master how Build GUI and Desktop applications with Python You will able to use advanced Python features. Ability to understand how to use and implement Jupyter Notebook You will create a portfolio of a Python based project and how to share with others You will have advance understanding of OOP, APIs, SQL, Git, GUIs, Flask, Django, Bootstrap, and many more You will learn practical programming skills and tricks, and use tools to be job ready You will be Program fluently in Python You will learn Machine Learning Model Learn Python best practices Requirements A computer / laptop / PC / Windows or Mac Internet Access Python Learner Proficiency in English language No previous knowledge of Python programming is needed We will walk you through how to get software installed and setup. Description This Python course is designed to equip you with the essential skills required to become a proficient Python programmer, preparing you for job-ready roles in the tech industry. Guided by a certified trainer, you'll start with the basics of Python programming and progress to advanced topics such as data structures, object-oriented programming, web development, and data analysis.Our hands-on, project-based approach ensures you not only learn the theory but also apply Python to real-world scenarios. The course emphasizes problem-solving and practical coding exercises, making sure you're prepared for the demands of the workplace. By the end of the course, you'll have built a portfolio of projects, demonstrating your capabilities to future employers.Key Features:Led by a certified Python trainer with industry experienceReal-world projects to build your portfolioJob-ready training focused on industry-relevant skillsGet certified upon course completionAccess to career support and networking opportunitiesFollow along with real-world projects designed to help you build practical coding skills and a portfolio to showcase to potential employersGain hands-on experience with interactive coding challenges and quizzes to reinforce key concepts.Revisit the course content and resources anytime in the future to refresh your knowledge or catch up on new updates.Tools & Technologies:Python Scripting and AutomationPython Game DevelopmentWeb ScrapingHTML 5CSS 3Bootstrap 4Bash Command LineDatabasesSQLAuthenticationWeb Design Overview Section 1: Introduction Lecture 1 Python Topics Introduction Lecture 2 Instructor Introduction Section 2: Python Introduction Lecture 3 Intro To Python Lecture 4 Features of Python Lecture 5 Python Compilation Section 3: Python Installation Lecture 6 Python Installation Session 1 Lecture 7 Python Installation Session 2 Section 4: Handling Module Lecture 8 Understanding Module Session Lecture 9 Methods of Importing Module Lecture 10 Types of Packages Section 5: Simple Python Program Lecture 11 Simple Python Program Section 6: Variables, Constants and Literals Lecture 12 Variables, Constants and Literals Section 7: Writing Comments and Docstrings Lecture 13 Writing Comments Lecture 14 Writing Docstrings Section 8: Object Types Lecture 15 Object Type Session 1 Lecture 16 Numeric Object Type Lecture 17 Sequence Object Type Lecture 18 Sets Lecture 19 Mapping Type Lecture 20 Boolean Type Lecture 21 Other Object Type Lecture 22 Checking Object Type Lecture 23 Type Casting Section 9: Operator Lecture 24 Operator in Python Lecture 25 Arithmatic Operator Lecture 26 Assignment Operator Lecture 27 Comparison Operator Lecture 28 Logical Operator Lecture 29 Identity Operator Lecture 30 Membership Operator Lecture 31 Bitwise Operator Lecture 32 Operator Precedence Section 10: Control Flow Statements Lecture 33 Control Flow Statements Lecture 34 Conditional Statements Lecture 35 Conditional Statement Session 2 Lecture 36 Conditional Statement Elif Lecture 37 Conditional Statement Else Lecture 38 Conditional Statement Nested If, Elif and Else Section 11: Looping Lecture 39 Looping Statement Lecture 40 Looping Statement While Lecture 41 Looping Statement For Lecture 42 Looping Statement Else Lecture 43 Looping Statement Nested Section 12: Jumpt Lecture 44 Jump Statements Lecture 45 Jump Statement Break Lecture 46 Jump Statement Continue Lecture 47 Jump Statement Pass Section 13: String Lecture 48 String Lecture 49 Accessing String Lecture 50 String Methods Lecture 51 String Slicing Section 14: List Lecture 52 List Session Lecture 53 Accessing List Elements Lecture 54 Looping List Elements Lecture 55 List Slicing Lecture 56 List Comprehension Lecture 57 List Methods Section 15: Tuple Lecture 58 Tuple Session Lecture 59 Accessing Tuple Elements Lecture 60 Looping Tuple Element Lecture 61 Tuple Slicing Lecture 62 Tuple Method Section 16: Dictionary Lecture 63 Dictionary Session Lecture 64 Accessing Dictionary Elements Lecture 65 Looping Over Dictionary Lecture 66 Dictionary Methods Section 17: Function Lecture 67 Function Session Lecture 68 Defining a Function Lecture 69 Calling a Function Lecture 70 Returning Result from Function Lecture 71 Returning Multiple Result from Function Lecture 72 Formal and Actual Arguments Lecture 73 Positional Argument Lecture 74 Keyword Argument Lecture 75 Default Argument Lecture 76 Variable Length Argument Section 18: Input and Output Lecture 77 Inputs and Outputs Lecture 78 Input Session Lecture 79 Output Session Section 19: Introduction to OOPs Lecture 80 Intro to OOPs Lecture 81 Features of OOPs Section 20: Classes and Objects Lecture 82 Classes and Objects Lecture 83 Types of Variables Lecture 84 Types of Methods Section 21: Inheritance and Polymorphism Lecture 85 Inheritance Lecture 86 Super Method Lecture 87 Types of Inheritance Lecture 88 Polymorphism Lecture 89 Operator Overloading Lecture 90 Method Overloading Lecture 91 Method Overriding Section 22: Abstract Classes and Interfaces Lecture 92 Abstract Class Lecture 93 Interfaces Section 23: Exception Handling Lecture 94 Types of Error Lecture 95 Exceptions Lecture 96 Exception Handling Lecture 97 User Defined Exception Section 24: File Handling Lecture 98 File Handling Lecture 99 Text File Handling Lecture 100 Write and Read Data Lecture 101 Using With Statement Lecture 102 Binary File Handling Section 25: Regular Expression Lecture 103 Regular Expression Lecture 104 Using Single Step Lecture 105 Find All Lecture 106 Match Method Lecture 107 Split Method Lecture 108 Using Sub Method Lecture 109 Special Character Section 26: Date and Time 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Free Download Python Programming - The Complete Course For Success Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.11 GB | Duration: 4h 53m Become a Python Expert: Comprehensive Course Covering Fundamentals, Advanced Techniques & Practical Success Strategies What you'll learn Overview of algorithms and their applications Basic Python programming refresher Operations on lists and tuples Use cases and applications Applications of stacks (e.g., backtracking, browser history) Introduction to queues and types (FIFO, priority queues) Implementing linked lists in Python Binary trees, binary search trees, AVL trees Basics of graph theory and types of graphs Applications of hash tables Bubble sort, selection sort, insertion sort Merge sort, quicksort, heap sort Implementing linear and binary search algorithms Principles of dynamic programming Heaps, tries, and segment trees Implementing and using advanced data structures Requirements No prior programming experience is required. Description Unlock your full potential with Python Programming: The Complete Course for Success! Whether you're a beginner or looking to sharpen your skills, this comprehensive course will guide you through the fundamentals of Python, one of the most popular and versatile programming languages. Learn to write clean, efficient code from scratch and build practical projects that reinforce your knowledge.What You'll Learn:Python fundamentals: variables, data types, loops, and functionsObject-Oriented Programming (OOP) conceptsHow to work with libraries like NumPy, Pandas, and MatplotlibWeb scraping, data analysis, and automation techniquesBest practices for debugging, testing, and writing efficient codeWhy This Course?This course is designed with real-world applications in mind. You'll not only master Python syntax but also learn how to apply it in real-life scenarios like web development, data analysis, and automation. With hands-on exercises and interactive coding challenges, you'll gain the confidence to tackle complex projects and prepare for your career in tech.Step-by-step lessons, practical examples, and engaging challenges ensure you stay motivated throughout the learning process. By the end of this course, you'll have a deep understanding of Python and the ability to solve problems with creativity and efficiency.Start your journey to success in Python programming today! Overview Section 1: Module 1: Introduction to Data Structures and Algorithms Lecture 1 Definition and importance of data structures Lecture 2 Overview of algorithms and their applications Lecture 3 Basic Python programming refresher Section 2: Module 2: Basic Data Structures in Python Lecture 4 Operations on lists and tuples Lecture 5 Use cases and applications Lecture 6 Understanding stack data structure Lecture 7 Implementing stacks using lists Lecture 8 Applications of stacks (e.g., backtracking, browser history) Lecture 9 Introduction to queues and types (FIFO, priority queues) Lecture 10 Implementing queues using lists and deque Section 3: Module 3: Advanced Data Structures Lecture 11 Implementing linked lists in Python Lecture 12 Use cases and applications of linked lists Lecture 13 Binary trees, binary search trees, AVL trees Lecture 14 Tree traversal techniques (in-order, pre-order, post-order) Lecture 15 Basics of graph theory and types of graphs Lecture 16 Graph traversal algorithms (BFS, DFS) Lecture 17 Understanding hash functions and hash tables Lecture 18 Applications of hash tables (e.g., caching, indexing) Section 4: Module 4: Algorithmic Techniques and Sorting Algorithms Lecture 19 Divide and conquer, greedy algorithms, dynamic programming Lecture 20 Bubble sort, selection sort, insertion sort Lecture 21 Merge sort, quicksort, heap sort Lecture 22 Comparing the efficiency of different sorting algorithms Section 5: Module 5: Searching Algorithms Lecture 23 Implementing linear and binary search algorithms Lecture 24 Understanding algorithm efficiency and use cases Lecture 25 Dijkstra's algorithm for shortest paths Section 6: Module 6: Recursion and Dynamic Programming Lecture 26 Principles of dynamic programming Section 7: Module 7: Advanced Topics and Optimization Techniques Lecture 27 Heaps, tries, and segment trees Lecture 28 Techniques to optimize algorithms for better performance Lecture 29 Memory and space optimization strategies Anyone interested in Python Programming Complete Course for Success,Anyone interested in automating tasks or diving into data analysis Homepage https://www.udemy.com/course/python-programming-the-complete-course-for-success/ Rapidgator https://rg.to/file/260571ddc45d26052dff1585c04ec16b/psqch.Python.Programming.The.Complete.Course.For.Success.part1.rar.html https://rg.to/file/8212e4aedefc32c4541573365900d5a4/psqch.Python.Programming.The.Complete.Course.For.Success.part2.rar.html Fikper Free Download https://fikper.com/bIkmGvnOtA/psqch.Python.Programming.The.Complete.Course.For.Success.part1.rar.html https://fikper.com/fCINRGMW9x/psqch.Python.Programming.The.Complete.Course.For.Success.part2.rar.html No Password - Links are Interchangeable

Free Download Java & Python Programming Mastery - Learn To Code Like A Pro Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 653.27 MB | Duration: 3h 7m Master Java and Python programming from the ground up and gain the skills to build real world applications like a pro. What you'll learn Understanding Java & Python Syntax Comments Data Type Variables Operators Booleans If...Else For Loop While Loop Arrays Strings Constants Requirements No Programming Experience Needed Description Ready to elevate your programming skills and unlock new career opportunities? Welcome to "Java & Python Programming Mastery: Learn to Code Like a Pro," the ultimate Udemy course designed to turn you into a proficient coder in two of the most influential programming languages: Java and Python.This course begins by laying a strong foundation in programming fundamentals. You will start with Python, learning the essentials such as syntax, data types, and control structures. As you advance, you'll explore advanced topics like file handling, object-oriented programming, and modules. Python's versatility will be showcased through practical applications such as web scraping, data analysis, and automation scripts.Java Fundamentals:Core concepts: Grasp the basics of Java, including variables, data types, operators, and control flow.Object-oriented programming (OOP): Master OOP principles like inheritance, polymorphism, and encapsulation.Exception handling: Learn to handle errors gracefully and prevent crashes.Collections framework: Utilize collections like ArrayLists, HashMaps, and Sets to efficiently store and manipulate data.JavaFX: Create visually appealing and interactive user interfaces.Python Fundamentals:Syntax and structure: Understand Python's clean and readable syntax.Data structures: Work with lists, tuples, dictionaries, and sets.Functions and modules: Build reusable code and organize your projects effectively.File I/O: Learn to read, write, and manipulate files.Regular expressions: Use regular expressions to search and manipulate text patterns.Advanced Topics:Multithreading: Create concurrent programs to improve performance.Networking: Develop network applications using sockets and HTTP.Database integration: Connect to databases like MySQL and PostgreSQL.Web development: Build web applications using frameworks like Spring Boot (Java) and Django (Python).Data analysis: Explore data analysis techniques using libraries like NumPy and Pandas.Key benefits of this course:Cover a wide range of topics, from fundamentals to advanced concepts.Apply your knowledge through practical exercises and real-world projects.Learn from experienced instructors with industry expertise.Access the course materials at your own pace and convenience.In addition to coding, the course covers best practices in software development, including debugging techniques, version control with Git, and writing clean, maintainable code. You'll also gain insights into the latest trends and tools in the programming world, ensuring your skills remain relevant and cutting-edge.Whether you're aiming to advance your career, switch fields, or start a new project, this course provides the comprehensive training you need to excel in both Java and Python. Join today and unlock the full potential of programming with two of the most sought-after languages in the industry. Overview Section 1: Started with Java Lecture 1 Syntax Lecture 2 Comments Lecture 3 Data Type Lecture 4 Variables Lecture 5 Operators Lecture 6 Booleans Lecture 7 If...Else Lecture 8 For Loop Lecture 9 While Loop Lecture 10 Arrays Lecture 11 Strings Lecture 12 Constants Section 2: Started with Python Lecture 13 Syntax Lecture 14 Comments Lecture 15 Data Type Lecture 16 Variables Lecture 17 Operators Lecture 18 Booleans Lecture 19 If...Else Lecture 20 For Loop Lecture 21 While Loop Lecture 22 Arrays Lecture 23 Strings Lecture 24 Constants Anyone looking to build the Java and Python programming skills.,People interested in programming who have no prior programming experience Homepage https://www.udemy.com/course/java-python-programming-mastery-learn-to-code-like-a-pro/ Rapidgator https://rg.to/file/453be6e6d8c798c459e6fbe5b48a5d0c/egmsk.Java..Python.Programming.Mastery.Learn.To.Code.Like.A.Pro.rar.html Fikper Free Download https://fikper.com/Ifw7ezJnQC/egmsk.Java..Python.Programming.Mastery.Learn.To.Code.Like.A.Pro.rar.html No Password - Links are Interchangeable

Free Download Dane Hillard - Publishing Python Packages, Video Edition Released 2/2023 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 6h 36m | Size: 1 GB Create masterful, maintainable Python packages! This book includes pro tips for design, automation, testing, deployment, and even release as an open source project! In Publishing Python Packages you will learn how to Build extensions and console script commands Use tox to automate packaging, installing, and testing Build a continuous integration pipeline using GitHub Actions Improve code quality and reduce manual review using black, mypy, and flake8 Create published documentation for your packages Keep packages up to date with pyupgrade and Dependabot Foster an open source community using GitHub features Publishing Python Packages teaches you how to easily share your Python code with your team and the outside world. Learn a repeatable and highly automated process for package maintenance that's based on the best practices, tools, and standards of Python packaging. This book walks you through creating a complete package, including a C extension, and guides you all the way to publishing on the Python Package Index. Whether you're entirely new to Python packaging or looking for optimal ways to maintain and scale your packages, this fast-paced and engaging guide is for you. About the Technology Successful Python packages install easily, run flawlessly, and stay reliably up to date. Publishing perfect Python packages requires a rigorous process that supports systematic testing and review, along with excellent documentation. Fortunately, the Python ecosystem includes tools and techniques to automate package creation and publishing. About the Book Publishing Python Packages presents a practical process for sharing Python code in an automated and scalable way. Get hands-on experience with the latest packaging tools, and learn the ins and outs of package testing and continuous integration. You'll even get pro tips for setting up a maintainable open source project, including licensing, documentation, and nurturing a community of contributors. What's Inside Build extensions and console script commands Improve code quality with automated review and testing Create excellent documentation Keep packages up to date with pyupgrade and Dependabot About the Reader For intermediate Python programmers. About the Author Dane Hillard has spent the majority of his development career using Python to build web application https://www.oreilly.com/library/view/publishing-python-packages/9781617299919VE/ Rapidgator https://rg.to/file/8456eeef876f5b93bfe63938fea96913/nkwhk.Publishing.Python.Packages.Video.Edition.part1.rar.html https://rg.to/file/dfca3a32e0795814966263a99c97991d/nkwhk.Publishing.Python.Packages.Video.Edition.part2.rar.html Fikper Free Download https://fikper.com/fJs79xG436/nkwhk.Publishing.Python.Packages.Video.Edition.part1.rar.html https://fikper.com/Ictssyxqvv/nkwhk.Publishing.Python.Packages.Video.Edition.part2.rar.html No Password - Links are Interchangeable

Free Download Twisted Python Projects By Daniel Aldred Released 9/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 33m | Size: 111 MB Join Dan as he guides you through a live coding session to build a soundboard app using Python and guizero, based on his book "12 Twisted Python Projects for Young Coders." https://www.oreilly.com/library/view/twisted-python-projects/10000MNCS202425/ TakeFile https://takefile.link/1k4hxse986g4/wwgwi.Twisted.Python.Projects.rar.html Rapidgator https://rg.to/file/f64b9136551869a153876efd82a2b9be/wwgwi.Twisted.Python.Projects.rar.html Fikper Free Download https://fikper.com/4oO8H8N56z/wwgwi.Twisted.Python.Projects.rar.html No Password - Links are Interchangeable

Free Download The Python For Technical Analysis Crash Course Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 911.48 MB | Duration: 2h 35m An Engaging and Focused Course for Learning Financial Analysis in Python What you'll learn Set up a Python coding environment Download stock, forex, futures, or crypto data directly from Python Clean and organize your table of financial data using Python Add new columns of data to your table Analyze financial data with built-in Python functions and methods Code various financial indicators, including Bollinger Bands and Fibonacci Retracement Levels Explore the basics of financial data visualization using the Matplotlib and Plotly libraries Requirements The Anaconda distribution of Python. This can be downloaded for free, and I show you how to do so in one of the course's earliest lessons A basic understanding of data tables Previous experience in Excel or SQL is helpful but not necessary Description Learn all the techniques necessary to begin undertaking financial analysis in PythonThis course teaches you everything need to know to begin using Python for financial and technical analysis. The course is designed to limit unnecessary theoretical digressions and focus on what's useful for beginners who are eager to start applying their knowledge as soon as possible.After several years of using Excel for stock analysis, I began studying Python as a potential alternative. I found that Python offered a much faster and more flexible approach to stock analysis, but I struggled to find learning material that didn't quickly get bogged down in excessive detail. So I essentially ended piecing together my own course by drawing on various articles, videos, and passages from books that I'd bought. The Python for Technical Analysis Crash Course is a distillation of all the months I spent gathering the information that ended up being helpful to me. It's the kind of course I wish I'd been able to find when I started studying Python myself.The course is organized as follows:-In the first part of the course, we'll set up your Python coding environment and go over some Python basics.-After that, we'll see how to download and display stock data in Python, as well as how to remove and reformat data.-Once our table of stock data has been cleaned, we'll start using that data to add new columns to the table (for example, we'll see how to create a column containing a stock's 20-Day Moving Average).-With our table complete, we'll look at various methods for analyzing and visualizing the table's data.-Finally, in the course's Extra Credit section, I'll show you some techniques that didn't quite fit into the main body of the course but that still might be useful for you. Overview Section 1: Introduction Lecture 1 Introduction to Course Lecture 2 Accessing Python Lecture 3 Python Primer Section 2: Getting and Cleaning the Stock Data Lecture 4 Importing Libraries Lecture 5 Getting Stock Data, Pt. 1 Lecture 6 Getting Stock Data, Pt. 2 Lecture 7 A Closer Look at the Table Lecture 8 Deleting and Referencing Columns Lecture 9 Resetting the Index and Reformatting the Date Column Lecture 10 Cleaning up the Index and Expanding the Table Lecture 11 Rounding Lecture 12 Recap 1 Section 3: Adding New Columns to the Table Lecture 13 Day-to-Day Price Percentage Change Lecture 14 20-Day Moving Average Lecture 15 The np.where() Function Lecture 16 Bollinger Bands, Pt. 1 Lecture 17 Bollinger Bands, Pt. 2 Lecture 18 Recap 2 Section 4: Analyzing and Visualizing the Data Lecture 19 The describe() Method, Pt. 1 Lecture 20 The describe() Method, Pt. 2 Lecture 21 The corr() Method Lecture 22 The groupby() Method Lecture 23 Matplotlib, Pt. 1 Lecture 24 Matplotlib, Pt. 2 Lecture 25 Plotly Lecture 26 Exporting the Data to Excel Section 5: Extra Credit Lecture 27 A Few Words on the Extra Credit Lessons Lecture 28 Getting Data for Forex, Futures, and Crypto Lecture 29 Getting Fundamental Data Lecture 30 yf.download() Lecture 31 Data Types Lecture 32 pd.DataFrame() Lecture 33 The assign() Method Lecture 34 Troubleshooting Lecture 35 Fibonacci Retracement Levels Section 6: Farewell Lecture 36 Farewell Students interested in an efficient approach to learning the fundamentals of financial analysis in Python,Excel users looking for a faster and more flexible financial analysis environment,Anyone interested in the learned the basics of data analysis in Python,NOTE: This is a coding and data analytics course, not an investment course. If you're looking for direct trading advice, this is probably not the course for you. Homepage https://www.udemy.com/course/the-python-for-technical-analysis-crash-course/ Rapidgator https://rg.to/file/efdd62e871490f837574a365a9e14e16/winsq.The.Python.For.Technical.Analysis.Crash.Course.rar.html Fikper Free Download https://fikper.com/BqDMNdp4W7/winsq.The.Python.For.Technical.Analysis.Crash.Course.rar.html No Password - Links are Interchangeable

Free Download Python TensorFlow Programming with Coding Exercises Published 9/2024 Created by Python AI ML DL DS Quiz Maker MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 30 Lectures ( 1h 39m ) | Size: 305 MB Master Deep Learning with TensorFlow through Practical Coding Exercises What you'll learn: How to build and train neural networks using TensorFlow. Techniques for implementing CNNs and RNNs for specific tasks. Methods for fine-tuning and optimizing deep learning models. Practical skills in deploying TensorFlow models in real-world applications. Requirements: Basic understanding of Python programming. Familiarity with fundamental machine learning concepts. Description: Welcome to Python TensorFlow Practices with Coding Exercises, a course designed to guide you through the essential concepts and techniques needed to excel in deep learning using TensorFlow. TensorFlow is one of the most powerful and widely used libraries for building machine learning and deep learning models. This course is crafted to help you gain hands-on experience in developing, training, and deploying neural networks with TensorFlow, providing you with the skills required to tackle real-world challenges in AI and data science.Why is learning TensorFlow necessary? As the demand for AI and machine learning continues to rise, the ability to build and implement deep learning models is becoming increasingly valuable. TensorFlow, developed by Google, is the go-to tool for professionals aiming to create scalable and efficient machine learning models. Whether you are an aspiring data scientist, a software engineer looking to specialize in AI, or a researcher aiming to incorporate deep learning into your work, this course is designed to meet your needs.Throughout the course, you will engage in coding exercises that cover a variety of topics, including:Introduction to TensorFlow and its ecosystemBuilding basic neural networks with TensorFlowImplementing convolutional neural networks (CNNs) for image recognitionDeveloping recurrent neural networks (RNNs) for sequence predictionTraining models using TensorFlow's Keras APIFine-tuning and optimizing models for better performanceDeploying TensorFlow models in production environmentsEach exercise is carefully structured to reinforce your understanding of TensorFlow and deep learning, ensuring that you can confidently apply these skills in practical scenarios.Instructor Introduction: Your instructor, Faisal Zamir, is a seasoned Python developer with over 7 years of teaching experience. Faisal's deep expertise in Python programming and machine learning, combined with his practical teaching approach, will guide you through the complexities of TensorFlow with ease.30 Days Money-Back Guarantee: We believe in the effectiveness of our course, which is why we offer a 30-day money-back guarantee. If you're not completely satisfied, you can request a full refund, no questions asked.Certificate at the End of the Course: Upon completing the course, you will receive a certificate that recognizes your proficiency in TensorFlow and deep learning, making it a valuable addition to your professional portfolio. Who this course is for: Aspiring data scientists and AI professionals who want to specialize in deep learning. Python developers looking to enhance their skills with TensorFlow. Researchers and professionals aiming to integrate deep learning into their work. Homepage https://www.udemy.com/course/python-tensorflow-programming-with-coding-exercises/ Rapidgator https://rg.to/file/b621e929dfdebb7407ee5ee3930ebc4a/khsag.Python.TensorFlow.Programming.with.Coding.Exercises.rar.html Fikper Free Download https://fikper.com/gYTchBWsFY/khsag.Python.TensorFlow.Programming.with.Coding.Exercises.rar.html No Password - Links are Interchangeable

Free Download Python Scikit Learn Programming With Coding Exercises Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 299.09 MB | Duration: 2h 0m Master Machine Learning with Scikit-learn Through Practical Coding Challenges What you'll learn How to preprocess data and perform feature engineering for machine learning models. Techniques for implementing both supervised and unsupervised learning algorithms using Scikit-learn. Methods for evaluating, fine-tuning, and deploying machine learning models. Practical skills in building machine learning pipelines and using cross-validation techniques. Requirements Basic knowledge of Python programming. Familiarity with basic statistical concepts and linear algebra. Description Welcome to Python Scikit-learn Programming with Coding Exercises, a course designed to take you from a beginner to an advanced level in machine learning using Scikit-learn, the go-to library for machine learning in Python. Scikit-learn is a powerful and easy-to-use library that provides simple and efficient tools for data analysis and machine learning. Whether you are a data enthusiast, a Python developer, or a professional looking to break into the field of machine learning, this course will equip you with the necessary skills to excel in building predictive models.Why is learning Scikit-learn necessary? As the demand for data-driven decision-making continues to grow, the ability to build and deploy machine learning models is becoming increasingly essential. Scikit-learn offers a wide range of algorithms and tools that are crucial for implementing machine learning solutions in various domains, such as finance, healthcare, marketing, and more. This course is structured to help you gain hands-on experience with Scikit-learn, enabling you to apply machine learning techniques to solve real-world problems.Throughout this course, you will engage in a series of coding exercises that cover a wide array of topics, including:Introduction to Scikit-learn and its ecosystemData preprocessing and feature engineeringSupervised learning algorithms such as linear regression, decision trees, and support vector machinesUnsupervised learning algorithms like k-means clustering and prin[beeep]l component analysis (PCA)Model evaluation and hyperparameter tuningImplementing cross-validation techniquesBuilding and deploying machine learning pipelinesEach exercise is designed to reinforce your understanding of the concepts and techniques, ensuring that you gain practical experience in implementing machine learning models with Scikit-learn.Instructor Introduction: Your instructor, Faisal Zamir, is an experienced Python developer and educator with over 7 years of experience in teaching and software development. 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