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Free Download Using AI to Generate Business Analysis Deliverables Released 10/2024 With Jamie Champagne MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill level: Beginner | Genre: eLearning | Language: English + subtitle | Duration: 1h 2m 48s | Size: 167 MB Learn how to use various generative AI technologies to facilitate business analysis work. Course details AI is quickly becoming a competitive advantage, and those who know how to take advantage of these capabilities in their daily work will not only succeed but will far surpass their competition. In this course, Jamie Champagne-business analysis professional speaker and trainer-will walk you through various generative AI technologies showing you the approach to take to have these emerging technologies facilitate business analysis work. Explore how AI apps can streamline your communications, enhance productivity, and help you verify and validate business analysis work while speeding the delivery of business analysis deliverables. Learn how to articulate the breadth and depth of generative AI applications, not only in areas of your work, but also in generating curiosity and motivation to include various applications in your business analysis work. Homepage https://www.linkedin.com/learning/using-ai-to-generate-business-analysis-deliverables Screenshot Rapidgator https://rg.to/file/ab73b47022f631ca7c58dbbd5691d7f6/xjnvs.Using.AI.to.Generate.Business.Analysis.Deliverables.rar.html Fikper Free Download https://fikper.com/chcUhMRyJa/xjnvs.Using.AI.to.Generate.Business.Analysis.Deliverables.rar.html No Password - Links are Interchangeable

Free Download Univariate analysis using R programming Published 10/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 4h 18m | Size: 2.32 GB Calculate summary statistics of different data types, present them as tables, and create many plots from data. What you'll learn Install R and Rstudio Calculate summary statistics for numerical and categorical data using R Convert the results to readable tables using R Plot numerical data as histograms and box plots using R Plot categorical data as bar plots and tree maps using R Apply the above concepts on freely available datasets Requirements No programming language experience is needed. You will learn R and data analysis from scratch. Description Install R and R studio.Use R studio to explore data and present the results as tables with captions.Use R studio for calculating summary statistics for the location of numerical data (mean, median, and percentiles).Learn how to use the mean and median to deduce the data distribution.Use R studio for calculating summary statistics for the spread of numerical data (range, variance, standard deviation, and interquartile range). Learn how to interpret the measures of spread to identify your risk.Learn how to present the results of summary statistics as tables with captions.Use R studio for plotting histograms of numerical data. Learn how to interpret the data histogram to deduce the data distribution.Use R studio for plotting box plots of numerical data. Learn how to interpret the data box plot to deduce the data distribution and the different quantiles.Use R studio for calculating summary statistics of categorical data (count, proportion, and percentage).Use R studio for plotting bar plots of categorical data.Use R studio for plotting tree maps of categorical data.Learn how to use the bar plots and tree map to identify the most and least frequent categories.Learn how to customize the plots to produce different versions of the plot for the same data.Learn how to export the created plots to PDF or image or copy them to your clipboard to be included in your reports. Who this course is for Laymen persons who want to understand statistics and data analysis Students or fresh graduates who want to learn R and data analysis Academic professionals who want to learn statistics to understand the statistical part of published papers Homepage https://www.udemy.com/course/univariate-analysis-using-r-programming/ Screenshot Rapidgator https://rg.to/file/309cd2c8d5c14b1f84c70bd22923f531/lvqwm.Univariate.analysis.using.R.programming.part2.rar.html https://rg.to/file/771cb8faee1829021547733e1a8d9e9f/lvqwm.Univariate.analysis.using.R.programming.part1.rar.html https://rg.to/file/fac9de7db98fdb05349e84caff496db5/lvqwm.Univariate.analysis.using.R.programming.part3.rar.html Fikper Free Download https://fikper.com/SldCHQmlXH/lvqwm.Univariate.analysis.using.R.programming.part1.rar.html https://fikper.com/nN7NlgL6nA/lvqwm.Univariate.analysis.using.R.programming.part2.rar.html https://fikper.com/uv4JqNVKS7/lvqwm.Univariate.analysis.using.R.programming.part3.rar.html No Password - Links are Interchangeable

Free Download Udemy - Data Science Using R (2024) Published 10/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 17.31 GB | Duration: 19h 22m "Data Science Using R: Comprehensive Training in Data Analysis, Visualization, and Machine Learning Techniques . What you'll learn Proficient R Programming: Develop a solid foundation in R programming for data manipulation, analysis, and visualization. Statistical Analysis Skills: Apply statistical methods and machine learning algorithms to derive meaningful insights from datasets. Data Visualization Mastery: Create compelling visualizations using ggplot2 to effectively communicate data findings and trends. Practical Application: Complete real-world projects that enhance problem-solving abilities and demonstrate proficiency in data science concepts. Requirements To enroll in the Data Science Using R course, parti[beeep]nts should have a basic understanding of programming concepts, as familiarity with any programming language will facilitate the learning process. A foundational knowledge of statistics is also beneficial, as it will help students grasp essential data analysis techniques more effectively. Additionally, proficiency in general computer literacy and software applications is required to navigate R and its associated tools. Most importantly, a strong eagerness to learn and a curiosity about data science are crucial for success in this course. These prerequisites will ensure that all students are well-prepared to dive into the exciting world of data science. Description This course, "Data Science with R," is designed for aspiring data scientists and analysts seeking to harness the power of R for data manipulation, analysis, and visualization. Parti[beeep]nts will begin by gaining a solid foundation in R programming, covering key concepts such as data types, structures, and essential functions.As the course progresses, students will delve into data wrangling techniques using packages like dplyr and tidyr, enabling them to clean and prepare datasets for analysis. The curriculum emphasizes statistical analysis, including hypothesis testing, regression models, and machine learning algorithms, empowering parti[beeep]nts to draw meaningful insights from their data.Visualization is a key focus, with instruction on using ggplot2 to create informative and engaging graphics that communicate results effectively. Real-world case studies and hands-on projects will provide practical experience, allowing students to apply their skills to actual data challenges.By the end of the course, parti[beeep]nts will have developed a comprehensive toolkit for data science, including proficiency in R, an understanding of statistical methodologies, and the ability to present their findings clearly. This course is perfect for those looking to kickstart a career in data science or enhance their analytical capabilities in any field and sorroundings.IIBM Institute of Business Management. Overview Section 1: R Introduction Lecture 1 R Introduction Section 2: R Implementation, R Data Structures, R Interfaces, R Interfaces Lecture 2 R Implementation, R Data Structures, R Interfaces, R Interfaces Section 3: Data Visualization Using R Software Lecture 3 Introduction to Visualisation - Line Plots and Bar Charts - Pie Chart and Histog Section 4: Predictive Customer Analytics using R - Linear Regression using R Software Lecture 4 Predictive Customer Analytics using R - Linear Regression using R Software-Part1 Lecture 5 Predictive Customer Analytics using R - Linear Regression using R Software-Part2 Section 5: Bank Loan Modelling using R Lecture 6 Logistic Function - Single Predictor Model. Section 6: Sales Promotion Effectiveness -Dimension Reduction using R Software. Lecture 7 Sales Promotion Effectiveness -Dimension Reduction using R Software - Part 1 Lecture 8 Sales Promotion Effectiveness -Dimension Reduction using R Software - Part 2 Section 7: Customer and Market Segmentation - Cluster Analysis using R Lecture 9 Customer and Market Segmentation - Cluster Analysis using R Software-Part 1 Lecture 10 Customer and Market Segmentation - Cluster Analysis using R Software-Part 2 Section 8: Retail Analytics: Market Basket Analysis (MBA) - Association Rule using R. Lecture 11 Association Rule Introduction - Apriori Algorithm - Multiple Association Rules Section 9: Customer Loyalty Analytics- Naïve Bayes Classification using R Software. Lecture 12 Naïve Bayes Introduction - Probabilistic Basics and Probabilistic Classification Section 10: K - Nearest Neighbour (KNN) Using R Software Lecture 13 K - Nearest Neighbour Introduction - K - Nearest Neighbour Algorithm. Section 11: Decision Trees using R Software Lecture 14 What is a Decision Tree? - How to create Decision Tree Section 12: Random Forest using R Software Lecture 15 Ensample of Decision Tree. Section 13: Support Vector Machine - SVM Lecture 16 Linear SVM using Hyperplane - Non-Linear Hyperplane using Kernal Trick. Section 14: Real Time Project - Customer Loyalty Analytics and its Application. Lecture 17 RFM Segmentation and Analysis - Propensity Modelling and its application. Lecture 18 Real Time Project - Customer Loyalty Analytics and its Application Section 15: Real Time Project - Finance Analytics and its Application using R Lecture 19 Credit Risk Analytics using Logistic Regression. Section 16: Course Complete Revision Lecture 20 Course Complete This course is for aspiring data scientists, analysts, and researchers seeking to enhance their R programming skills, gain insights from data, and apply analytical techniques in real-world scenarios. 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Free Download Sustainability Reporting Using The Issb Standards Published 10/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 539.32 MB | Duration: 1h 44m Understand the requirements of IFRS S1 and S2. Learn to draft a ESG report using our step-by-step guided template. What you'll learn Key concepts and terminology behind the ISSB Standards Understand financial materiality and choose the relevant ESG topics and metrics to report for your company. Collect and present data correctly with the required breakdown Align your company's ESG governance structure and strategic planning with the ISSB requirements Set performance targets and monitor progress in accordance with the ISSB Standards Identify gaps in your company's current sustainability report and strategy Requirements Basic knowledge of corporate ESG Familiarity with sustainability reports Description This course will help you to:Appreciate the history & context behind the ISSB Standards so that you can use it correctly.Understand the key concepts and terminology behind the IFRS S1 and S2 disclosure requirements.Draft a compliant report using our template with step-by-step guidance.By the end of this course, you will gain the knowledge needed to use the ISSB Standards. It includes video lessons, knowledge review quizzes, and a downloadable copy of our reporting template with guidance notes.The new ISSB Standards is fast becoming a global standard for sustainability reporting around the world. Countries such as Singapore, Hong Kong, Canada, Australia, South Korea, Japan, India, Brazil, the UK and many others have announced plans to use it for mandatory corporate reporting. In this course, we will explain concepts in simple language, recommend best practices, and provide the template for drafting a full report. The ISSB Standards gives a high degree of flexibility and various options for the required disclosures. However, users must read and understand many detailed requirements, as well as a large number of application rules. Our course is designed to help you bypass all that. We've put in a lot of time and effort to connect, explain and summarize all the requirements so that you can use it without reading the documentation!Everything in this course is designed to be implementation-oriented. After completion, industry practitioners will be able to use the knowledge immediately to help them plan their sustainability strategies, workflow and data collection to ensure compliance with the ISSB Standards. Overview Section 1: Course Introduction Lecture 1 Course introduction Section 2: History of the ISSB Standards Lecture 2 Overview Lecture 3 The Alphabet Soup of standards and frameworks Lecture 4 Impact vs financial materiality Lecture 5 Industry-based vs topic-based standards Lecture 6 IFRS Foundation takes up the consolidation baton Lecture 7 Release of IFRS S1 and S2 and early adoption by jurisdictions Lecture 8 Summary Section 3: Understanding the Requirements of the IFRS S1 Lecture 9 Overview Lecture 10 General requirements for drafting and publishing reports Lecture 11 Requirements for the content of your report Lecture 12 Sources of guidance for choosing topics and metrics Lecture 13 Summary Section 4: Climate-related Disclosures Using the IFRS S2 Lecture 14 Overview Lecture 15 Introduction to the IFRS S2 Lecture 16 Core content differences versus IFRS S1 Lecture 17 Switching from TCFD Framework to IFRS S2 Lecture 18 Governance & Risk Management Lecture 19 Strategy - Climate-related Risks & Opportunities Lecture 20 Strategy - Climate Resilience & Scenario Analysis Lecture 21 Metrics - Cross-industry & Industry-based Lecture 22 Targets - Climate-related Targets Lecture 23 Summary Section 5: Report Template with Step-by-Step Guidance Lecture 24 Overview Lecture 25 IFRS S1 Disclosures Lecture 26 IFRS S2 Disclosures Lecture 27 Final comments Executives involved in sustainability management or those looking to do so,C-suite of listed companies subjected to mandatory reporting by law,Company directors with fiduciary and governance duties for sustainability,Investors, fund managers and credit analysts,Consultants, auditors, entrepreneurs, regulators and software providers for sustainability reporting Screenshot Homepage https://www.udemy.com/course/sustainability-reporting-using-the-issb-standards/ Rapidgator https://rg.to/file/3d40bc5d9f1f40a4b3dfa349755b613d/mxlvd.Sustainability.Reporting.Using.The.Issb.Standards.rar.html Fikper Free Download https://fikper.com/VNKe8Ngs0A/mxlvd.Sustainability.Reporting.Using.The.Issb.Standards.rar.html No Password - Links are Interchangeable

Free Download Quantitative Analysis of Data Using SPSS V29 Published 10/2024 Created by Alain Tannous MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 21 Lectures ( 4h 19m ) | Size: 1.93 GB Quantitative Analysis, SPSS Software, Tests and Conclusions What you'll learn Explain the six SPSS windows and their specific uses. Calculate the mean, sum, standard deviation, variance, and more. Examine relationships using Scatter Plot and Scatter Plot Matrices. Test for Normality and Homoscedasticity. Explain numerical measures such as Central Location, Dispersion, Skewness, Kurtosis and Linearity. Identify and differentiate between the different forms of outcomes. Differentiate between the statistical types I and II errors. Construct a multiple regression model, identify its elements and list its assumptions. Learn to use the Ordinary Least Squares (OLS) regression method to estimate the coefficients. Define the Standard Error of Estimates (SEE), explain its role in regression model and understand its visual representation. Relate SEE to R-squared and the overall performance of the regression model. Define ANOVA, explain its assumptions and significance in regression analysis, set its hypotheses, conduct ANOVA analysis using SPSS and explain its outcomes. Formulate the null and alternative hypotheses. Conduct a statistical T-test to assess and interpret the significance of the coefficients. Define autocorrelation, identify its impact on regression models and test for autocorrelation using Durbin-Watson Test. Explain the importance of forecasting time series data and perform a forecast seasonal time series data using SPSS V29. Define MANOVA, explain its assumptions and significance in regression analysis, set its hypotheses, conduct MANOVA test using SPSS and explain its outcomes. Generate different tests related to MANOVA such as: Box's M Test, Hotelling's T Squared, Pillai's Trace Test and Wilk's Lambda Test. Formulate and test the hypotheses of all MANOVA tests using SPSS. Compose and test the hypotheses for Levene's Test of homogeneity of variances. Define Discriminant analysis and identify its variables, assumptions and hypotheses. Test for Multivariate Normality, Equality of Covariances and Vectors of Means. Perform a stepwise discriminant analysis and analyze its outcomes using the cross-validation method. Define logistic regression, identify its variables and assumptions, compose its hypotheses, perform a stepwise logistic regression test and analyze its outputs. Define the Prin[beeep]l Component Analysis (PCA), identify its key variables and assumptions, and conduct a PCA analysis following a detailed procedure on SPSS. Define Factor Analysis (FA), identify its assumptions, variables and hypotheses, and conduct all FA tests and analyze their outcomes. Define Cluster Analysis, identify its assumptions, variables and hypotheses, and conduct all FA tests and analyze their outcomes. Apply all tests using practical exercises on SPSS Requirements No prerequisites are required. You will learn all steps in this course. Description This course offers a detailed exploration of quantitative data analysis using SPSS V29, a powerful software tool widely used in research fields such as social sciences, business, healthcare, and education. Designed for both beginners and intermediate users, the course covers essential statistical techniques and guides learners through the process of managing, analyzing, and interpreting quantitative data. Over 4 hours and 20 minutes of recorded lectures, accompanied by PDF notes for each session, will introduce you to core concepts in data analysis, such as:Data entry, management, and cleaning techniques using SPSS V29Descriptive statistics, including measures of central tendency and variabilityInferential statistics such as t-tests, ANOVA, regression analysis, and chi-square testsMultivariate analysis techniques, including factor analysis, discriminant analysis, and cluster analysisReporting and interpreting statistical outputs effectivelyUsing visual tools like graphs and charts for data presentationThe course also includes SPSS data files for hands-on practice, ensuring that students gain practical experience working with real datasets.Additionally, a quiz at the end of each lesson allows students to assess their understanding and apply the skills learned. By the end of this course, parti[beeep]nts will be able to effectively use SPSS V29 to perform complex statistical analyses, create meaningful data visualizations, and report results professionally and clearly, equipping them with the tools needed for academic research or professional projects. Who this course is for Graduate and Postgraduate students who are engaged in writing their thesis or dissertation which is based on a quantitative analysis of data. Beginner researchers who require a tool to analyze their findings. 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Free Download No Code Conversational Chatbots Using Dialogflow Cx Published 10/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 4.28 GB | Duration: 9h 9m Why Dialogflow CX is the best alternative to ChatGPT (LLM) for stateful chatbots What you'll learn How to build "stateful" chatbots using Dialogflow CX How Dialogflow CX is better than LLM (GPT) bots When LLM (GPT) bots are better than Dialogflow CX When to use Dialogflow CX Why it is not a good idea to use generative AI inside stateful chatbots Requirements Basic technical skills - e.g. ability to work with an Excel spreadsheet Description This course, which was originally intended for my website audience, evolved over time from the date Dialogflow CX was first released (second half of 2021) and updated over the next two years. I stopped updating the course once ChatGPT started dominating the chatbot landscape (please watch the Introduction chapter to see why).PLEASE NOTE1 Many lessons are based on questions and feedback from course students, and you will see that some of the chapters are (unfortunately) a little redundant - for example the free Heroku tier is no longer available. 2 You should be able to follow the whole course just by watching the videos. The downloadable resources like agent ZIP files are not always available in the lesson, but that should not affect your learning. Similarly, some of the videos are based on articles from my old website which are now expired, but again you should be able to follow that material just by watching the full video.3 There are a couple of chapters which are quite code heavy. If you are not a programmer, you should be able to skip those chapters and still understand the rest of the material quite easily. Most of the chapters are self contained, although you MUST first go through the Beginner tutorial (which explains the concept of the state machine) as a prerequisite for the rest of the material. Testimonials from my website audience (note: all of these were provided between 2021 to 2023)"It is very hard find a complete course about DialogFlow CX""Actually is very hard find a complete course about DialogFlow CX, so I did not find any obstacle to buy this course. I managed to implement a chatbot for a website by creating my own webhook in PHP.What I liked the most about this course was the clear way in which how to create a webhook was explained.1. You can possibility learn how to implement custom integration using anymore framework.2. You can understand the difference between dialogflow ES and dialogflow CX.3. You can observe and prevent some bugs that the application has.I recommend this course because actually is very hard find a complete course about this technology and Aravind simplify the way to explain this topic."Adonis T"The course breaks things down into "bite-sized morsels" without using lingo that leaves many behind""There are precious few courses and tutorials for Dialogflow CX given its recent release. For that reason, I wondered if I should wait until the product matured some more before looking for a course. I bought the course after watching a few of the previews of this and other courses. I like Aravind's approach to teaching. He breaks things down into "bite-sized morsels" without using lingo that leaves many behind. I like the discussion on state machines. I was distantly familiar with the term but Aravind brought it up close.Other benefits of the course:an understanding of the terminology used in Dialogflow, an understanding of entities and parameters, an overall view of the process of building a bot in CXI would recommend this course to anyone that has a need to learn the process of creating a bot, either for cost savings or for extending your existing call center functionality."Paul R"it was one of the most up-to-date materials on Dialogflow""Watching the free videos on the differences between Dialogflow ES and CX was enough for me to make the decision and move forward with the purchase. The videos actually helped me decide which course to take. I found that Dialogflow is a very powerful tool, which should help me with my project quite a bit.(I liked) The short classes and ease to navigate across classes.(Other benefits of the course) Good content, good didactics and fast pace of learning.I'd recommend this course, because it was one of the most up-to-date materials on Dialogflow. I started by purchasing a course from Udemy, but I was very frustrated that it never even mentioned the existence of Dialogflow CX and all of the materials were based on Dialogflow webpages and references that no longer exist."Daniel B"Just the difference between parameters in CX and the pitfalls of contexts and slot filling in ES was golden.""I have learned so much from this website and the CX course. I find these courses much more informative than the official documentation. Just the difference between parameters in CX and the pitfalls of contexts and slot filling in ES was golden."Shahrukh S Overview Section 1: Introduction Lecture 1 Why I created this course Lecture 2 How Dialogflow CX is better than LLM bots Lecture 3 How LLM bots are better than Dialogflow CX Lecture 4 When to use Dialogflow CX Lecture 5 Integrating ChatGPT with Dialogflow CX Section 2: Dialogflow CX Beginner Tutorial Lecture 6 What is a state machine? Lecture 7 What we are building Lecture 8 Initial Demo Lecture 9 Terminology Lecture 10 Initial View Lecture 11 User asks for balance Lecture 12 Testing it in the simulator Lecture 13 No state transition Lecture 14 Add state transition Lecture 15 Ask for balance after transition Lecture 16 Assignment 1 Lecture 17 Assignment 2 Lecture 18 Assignment 3 Lecture 19 Assignment Hints Section 3: CX vs ES: Get user first and last names Lecture 20 Can you build this bot in Dialogflow ES? Lecture 21 Flowchart for the ES Bot Lecture 22 Defining the intents Lecture 23 ES Bot Demo Lecture 24 Extending the name system entity Lecture 25 A note about entity annotation Lecture 26 Building the bot in Dialogflow CX Lecture 27 Testing the bot in the simulator Lecture 28 Pros and Cons of Dialogflow CX for this bot Lecture 29 Understanding scope in Dialogflow CX Part 1 Lecture 30 Understanding scope in Dialogflow CX Part 2 Section 4: Flowcharts and test cases Lecture 31 Why ES First Lecture 32 Decision Tree Flowchart Lecture 33 Initial Flow Lecture 34 Some Housekeeping Tips Lecture 35 Building the remaining pages Lecture 36 Identifying test Cases Lecture 37 Naming test cases Lecture 38 Running Test cases Section 5: Entities and Parameters Lecture 39 Planets Bot: Introduction Lecture 40 Entity Definitions Lecture 41 Original vs Resolved value Lecture 42 Intent vs Session parameters Lecture 43 Session Parameters Intro Lecture 44 Using session params Lecture 45 Keeping track of session parameters Section 6: CX Webooks using Python Lecture 46 Before you start: Ngrok Tutorial Lecture 47 Handling multiple intents in ES Webhooks Lecture 48 Skeletal Code Lecture 49 Webhook Response Object Lecture 50 ngrok setup Lecture 51 Webhook Request Object Lecture 52 Handling getplanetattribute Lecture 53 Handling changesplanet Lecture 54 Handling changesattribute Lecture 55 Sample Code Lecture 56 A bug in Dialogflow CX webhooks Lecture 57 Reroute conversation flow based on webhook response Section 7: Dialogflow CX Slot Filling Lecture 58 What is slot filling? Lecture 59 Defining the slots Lecture 60 Demo of simple slot filling bot Lecture 61 Adding phrase variants Lecture 62 Reprompts Lecture 63 Reprompts with no-match-default Lecture 64 Reprompt to selection Lecture 65 Exiting the slot filling loop on first retry Lecture 66 Exiting the slot filling loop after second retry Section 8: Conditional Routes with Expressions Lecture 67 Introduction to the quiz bot Lecture 68 Start quiz intent Lecture 69 Question 1 Page Lecture 70 Question 2 Page Lecture 71 Question 3 Page Lecture 72 Display Score Page Lecture 73 Scope and the flow start page Section 9: Building a Dialogflow CX Custom Integration Lecture 74 4 Layers of a Dialogflow Bot Lecture 75 Set up the bot Lecture 76 Download service account credentials file Lecture 77 Code walkthrough Lecture 78 Why I don't recommend the client library Lecture 79 Defining the custom payload inside Dialogflow CX Lecture 80 Rich responses supported by Zoho SalesIQ Lecture 81 Hosting the middleware code on PythonAnywhere Lecture 82 Hosting the middleware code on Heroku Lecture 83 Hosting the middleware code on Google Cloud Section 10: Exception Handling Lecture 84 DF Chooser Bot Demo Lecture 85 Does a flowchart help when creating a Dialogflow CX bot? Lecture 86 Bot Design Part 1 Lecture 87 Bot Design Part 2 Lecture 88 Bot Design Part 3 Section 11: Changing conversation topic Lecture 89 CCAI Vaccine Bot Demo Lecture 90 Start Page Routes Lecture 91 Simple FAQ Routes Lecture 92 Eligibility Flow Lecture 93 Eligibility Flow Conflict Part 1 Lecture 94 Eligibility Flow Conflict Part 2 Lecture 95 Vaccine Location Flow Lecture 96 Vaccine Location Flow - Testing the agent Section 12: System Functions Lecture 97 Introduction Lecture 98 The quiz bot Lecture 99 Text response Lecture 100 Conditional response Lecture 101 Custom Payload Lecture 102 Parameter Presets Lecture 103 Condition Routes Section 13: Dialogflow CX Quickstart Templates Lecture 104 Getting a list of inputs from user Lecture 105 Save data to Airtable Lecture 106 Basic slot filling Lecture 107 Confirm or update user input after slot filling Lecture 108 Advanced slot filling Lecture 109 Advanced Slot Filling Part 2 Lecture 110 List and composite entities Lecture 111 Get user date of birth Lecture 112 Decision Tree Bot Lecture 113 Quiz Bot Lecture 114 Use Google Sheets as a database Technical non-programmers who want to learn about conversational chatbots in the era of large language models Screenshot Homepage https://www.udemy.com/course/no-code-conversational-chatbots-using-dialogflow-cx/ Rapidgator https://rg.to/file/98acf91a92aee67a30adaee48d4af4a4/fjplb.No.Code.Conversational.Chatbots.Using.Dialogflow.Cx.part4.rar.html https://rg.to/file/a05c20d3ec8cc07ebfea1bffeac6b0fc/fjplb.No.Code.Conversational.Chatbots.Using.Dialogflow.Cx.part3.rar.html https://rg.to/file/cd829efae3bcb4da5a4e3c66b34a9fc1/fjplb.No.Code.Conversational.Chatbots.Using.Dialogflow.Cx.part1.rar.html https://rg.to/file/d0351cb9a57a87e0ad4fe50f138b3d93/fjplb.No.Code.Conversational.Chatbots.Using.Dialogflow.Cx.part2.rar.html https://rg.to/file/f008ed18aeffbbe178b04745e5ef37cc/fjplb.No.Code.Conversational.Chatbots.Using.Dialogflow.Cx.part5.rar.html Fikper Free Download https://fikper.com/IP5HnNsqzl/fjplb.No.Code.Conversational.Chatbots.Using.Dialogflow.Cx.part1.rar.html https://fikper.com/Il570w7l97/fjplb.No.Code.Conversational.Chatbots.Using.Dialogflow.Cx.part5.rar.html https://fikper.com/KqICJhJ0M4/fjplb.No.Code.Conversational.Chatbots.Using.Dialogflow.Cx.part4.rar.html https://fikper.com/fqm8lngDNs/fjplb.No.Code.Conversational.Chatbots.Using.Dialogflow.Cx.part3.rar.html https://fikper.com/kewy0SAUGs/fjplb.No.Code.Conversational.Chatbots.Using.Dialogflow.Cx.part2.rar.html No Password - Links are Interchangeable

Free Download Nano Tips for Using Chat GPT to 10x Your Productivity at Work with Gianluca Mauro Released 10/2024 With Gianluca Mauro MP4 | Video: h264, 720x1280 | Audio: AAC, 44.1 KHz, 2 Ch Skill level: Beginner | Genre: eLearning | Language: English + subtitle | Duration: 13m 6s | Size: 81 MB Get quick, bite-sized tips on using ChatGPT to boost your productivity. Each video is less than two minutes long, so you can make learning fit into even your busiest days. Course details Welcome to our Nano Tips series, where LinkedIn Learning creators deliver impactful lessons in literally seconds. In this installment, join Gianluca Mauro-AI entrepreneur, public speaker, and troublemaker-as he explores ways to leverage the power of AI to boost your productivity and get more done at work.Learn how to utilize ChatGPT for enhanced productivity by crafting prompts that deliver consistent results. Gianluca covers the fundamentals of the CIDI framework for prompt engineering-context, instructions, details, and input-and how to get the most out of CIDI prompts in practice for social media copywriting, expert feedback, data structuring, and more. Along the way, gather insights for building and maintaining your prompt library and applying your new AI skills across your entire organization. Homepage https://www.linkedin.com/learning/nano-tips-for-using-chat-gpt-to-10x-your-productivity-at-work-with-gianluca-mauro Screenshot Rapidgator https://rg.to/file/566d659050b52312d2d8cdaff283915a/acesy.Nano.Tips.for.Using.Chat.GPT.to.10x.Your.Productivity.at.Work.with.Gianluca.Mauro.rar.html Fikper Free Download https://fikper.com/jHuUqHEJYP/acesy.Nano.Tips.for.Using.Chat.GPT.to.10x.Your.Productivity.at.Work.with.Gianluca.Mauro.rar.html No Password - Links are Interchangeable

Free Download Mood Tracker App Using React and Flask Published 10/2024 Created by Pegah Flashgary MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 6 Lectures ( 1h 40m ) | Size: 454 MB Combine React and Flask to Create Your Own Mood Journal What you'll learn Gain hands-on experience by building a fully functional Mood Tracker app using React, laying a strong foundation in web development. Learn how to effectively use React hooks like useState and useEffect to manage state and handle side effects, creating interactive and responsive applications. Learn how to integrate data tracking features into the app, enabling users to analyze their mood, diet, and physical activities. Discover how to leverage Generative AI tools in coding projects, enhancing creativity and efficiency in app development. Requirements No programming experience needed. Description In this hands-on course, you'll learn how to build your very own Mood Tracker App using React for the frontend and Flask for the backend. This project-based approach will not only enhance your coding skills but also help you create a practical tool to monitor your mood and wellbeing.What You'll Learn:Setting Up Your Development Environment: Get started by setting up your tools and frameworks for both React and Flask.Building a Dynamic Frontend: Use React to create an intuitive and responsive user interface for your Mood Tracker app, complete with mood selection and data visualization.Creating a Robust Backend: Learn how to use Flask to set up a RESTful API that handles mood data, user authentication, and storage in a database.Connecting Frontend and Backend: Discover how to seamlessly integrate your React frontend with your Flask backend, ensuring smooth communication between the two.Data Analysis and Visualization: Implement features that allow users to view and analyze their mood trends over time, promoting self-reflection and personal growth.This course is perfect for beginners who want to get hands-on experience in full-stack development. You'll gain valuable skills in React and Flask while creating a functional application that can truly impact users' lives. Plus, it's a fun way to combine coding with personal wellbeing! Who this course is for This course is for anyone keen to whip up their first web app while building a handy mood tracker! Homepage https://www.udemy.com/course/mood-tracker-app-using-react-and-flask/ Screenshot Rapidgator https://rg.to/file/6bb7d83ec210f80fa8c62442f4f0a8c3/rksmi.Mood.Tracker.App.Using.React.and.Flask.rar.html Fikper Free Download https://fikper.com/2g4VGLpQMK/rksmi.Mood.Tracker.App.Using.React.and.Flask.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)". By Ruslan Romanenko Who this course is for Anyone who wants to scrape data from any website Anyone who wants to learn Scrapy Anyone who wants to automate the task of copying contents from websites Anyone who wants to learn how to scrape Javascript websites using Scrapy-Splash & Selenium Homepage https://www.udemy.com/course/web-scraping-in-python-using-scrapy-and-splash/ Screenshot TakeFile https://takefile.link/6byhykd0s6rg/dkxur.Python.using.Scrapy.Splash.Selenium.rar.html Rapidgator https://rg.to/file/1e49f1b25f6e582345d33e85f36ee794/dkxur.Modern.Web.rar.html https://rg.to/file/7232d4d3aa4f0528c31a9b524e96c5de/dkxur.Python.using.Scrapy.Splash.Selenium.rar.html Fikper Free Download https://fikper.com/0mKBIuX3eY/dkxur.Modern.Web.Scraping.with.Python.using.Scrapy.Splash.Selenium.part3.rar.html https://fikper.com/3s5rvP92WU/dkxur.Modern.Web.Scraping.with.Python.using.Scrapy.Splash.Selenium.part3.rar.html https://fikper.com/4klLZPDsmx/dkxur.Modern.Web.rar.html https://fikper.com/DP52ALYBL9/dkxur.Python.using.Scrapy.Splash.Selenium.rar.html https://fikper.com/DQDRYk7XY1/dkxur.Modern.Web.Scraping.with.Python.using.Scrapy.Splash.Selenium.part2.rar.html https://fikper.com/JGILkwZc5f/dkxur.Modern.Web.Scraping.with.Python.using.Scrapy.Splash.Selenium.part3.rar.html https://fikper.com/f1XvpUVQGi/dkxur.Modern.Web.Scraping.with.Python.using.Scrapy.Splash.Selenium.part1.rar.html https://fikper.com/g6jNhvDkjm/dkxur.Modern.Web.Scraping.with.Python.using.Scrapy.Splash.Selenium.part4.rar.html https://fikper.com/ja4hV8mmfV/dkxur.Modern.Web.Scraping.with.Python.using.Scrapy.Splash.Selenium.part4.rar.html https://fikper.com/kKrBQ13J23/dkxur.Modern.Web.Scraping.with.Python.using.Scrapy.Splash.Selenium.part2.rar.html https://fikper.com/ldCqqvcWIG/dkxur.Modern.Web.Scraping.with.Python.using.Scrapy.Splash.Selenium.part2.rar.html https://fikper.com/p6x54TQc1s/dkxur.Modern.Web.Scraping.with.Python.using.Scrapy.Splash.Selenium.part4.rar.html https://fikper.com/tihJr2p9JL/dkxur.Modern.Web.Scraping.with.Python.using.Scrapy.Splash.Selenium.part1.rar.html https://fikper.com/uGGeYRI9Ok/dkxur.Modern.Web.Scraping.with.Python.using.Scrapy.Splash.Selenium.part1.rar.html No Password - Links are Interchangeable

Free Download Master Simulations Using Geometry Nodes in Blender Published 10/2024 Created by Yassine Larayedh MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 16 Lectures ( 1h 21m ) | Size: 928 MB Think like an engineer by Building your own physics engine using Geometry Nodes. What you'll learn: Learn to create advanced simulations using Blender's Geometry Nodes with a focus on real-world physics. Step-by-step guidance on building a fully functioning physics engine from scratch using Geometry Nodes. Understand Key Physics Concepts: Gain deep insights into fundamental concepts like gravity, velocity, acceleration, and collisions. Simulate Real-World Forces: Learn how to simulate real-world forces like friction and gravity in Blender for more realistic animations. Handle Dynamic Collisions: Discover how to create complex collision interactions between objects in your Blender simulations. Create Custom Constraints: Learn to add constraints like floors, walls, and object boundaries to control simulations precisely. Work with Attributes in Geometry Nodes: Understand how to manipulate attributes in Blender to create powerful simulation behaviors. Requirements: Basic knowledge of Blender Description: Course DescriptionIn this course, you will learn how to create simulations using Geometry Nodes in Blender, by building your own physics engine.This course is not just another "click-this-button" tutorial - It's a deep dive into the world of simulations in Blender.You won't simply learn to think like an artist, but also like an engineer.You will explore the technical side of creating realistic simulations.We'll cover essential physics concepts such asGravityVelocityAccelerationCollision, and moreAll of that will allow you to master simulations with a solid understanding of the science behind them.By the end, you'll be equipped to design complex, dynamic scenes with confidence.Project DescriptionThroughout this course you'll build your own simulation physics engine using geometry nodes in Blender.Each video builds on the last, guiding you step-by-step through the creation of the physics engine while deepening your understanding of simulation principles.Here's a full breakdown of the project you'll be working onVideo 01: Repeating ZonesThis is the backbone of simulations in Blender. In this video, you will learn the concepts behind repeating zones and how they work.Video 02: Simulation ZonesIn this video, you will learn the core concepts behind simulation zones and how they work.Video 03: What is a Simulation?There are a lot of way to think about simulations, in this video you learn the main concept behind simulations.Video 04: What is Velocity?Velocity and acceleration are the backbone of physic simulations. In this video, you will learn about velocity, and more importantly How to think of velocity!Video 05: What is Acceleration?The 2nd most important force in simulations is the acceleration. In this video, you will learn about acceleration and how it relates to velocity.The velocity and acceleration videos will equip you with a solid understanding of the different components of simulations that's: Change in position and Change in Velocity.Video 06: What is an Attribute?The concept of Attributes in Blender is one of the core components of simulations, and geometry nodes in general but It is hard to wrap your head around.In this video, you will learn the philosophy behind attributes, how the work, and how to harness their power in your own work.Video 07: The Acceleration AttributeIn this video, you will learn how to program (using nodes ofc) Acceleration in your physics engine.Video 08: The problem of Delta-timeTrouble shooting is an important skill, and this video is all about thatBecause of the way simulation zones work in Blender, that will cause some inconsistencies in the results when we change the framerate.In this video, you will learn how to make your physics engine function based on real-life timing. We'll transform acceleration to the most fundamental force on earth. Gravity!Video 09: Adding Constraints pt.1: The FloorUp until this point of the course, we still didn't talk about constraints. Basically how to make things collide with other objects.In this video, you will learn the philosophy behind building constraints, by making points bounce off the floor.Video 10: Adding Constraints pt.2: The Side WallsIn this video, you'll learn how to make the balls bounce of the side walls. This is a slightly more challenging exercise but it will solidify your understanding of how to build constraints.Video 11: The RadiusYour physics engine right now functions based on points, and points are just imaginary things that allows us to perform different operations. More on the video.In this video, you will learn how to transform those virtual points into an actual geometry (Spheres)Also, you will learn creative ways to solve different problems in this video.Also, you will learn creative ways to solve different problems in this video.Video 12: CollisionThis is the last technical video of the course.At this point, you made the balls bounce of the floor and the side walls, but an important component of any physics engine is the collision between the different balls, and in this video, you will learn exactly how to program that into your physics engine.Video 13: Particle's SpawningIn this video, you will make the balls spawn over time, instead of having them all at once from the beginning of the simulation which can cause Blender to go Boom!This technique helps prevent Blender from crashing by controlling when objects are introduced into the simulation.Video 14: FrictionWithout friction the balls will keep bouncing forever. Sadly, that's not how real life works. As long as you're on earth, objects loses energy gradually.In this video, you will learn different ways to implement friction in your physics engine, with some helpful quality life improvements to make it easier to change different parameters of the physics engine.Video 15: Final OverviewIn this final video, we'll organize our node tree, and we'll take a bird's eye view on the physics engine we built. Who this course is for: This course is for Blender users who want to master simulations with Geometry Nodes. Whether you're new to physics or looking to build your own physics engine, this course provides a step-by-step guide to understanding and creating realistic simulations. Perfect for those ready to level up their skills. 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Free Download Linux Process Monitoring & Diagnostics using proc interface Published 10/2024 Created by Chandrashekar Babu MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 23 Lectures ( 14h 1m ) | Size: 14.4 GB Unlock the Power of Linux Process Monitoring and Optimization via /proc and Build Custom Automation Scripts For The Same What you'll learn: Learn about the significance of the procfs (/proc) interface on Linux Learn how to gather process information via procfs Learn how to monitor / track memory, CPU and I/O usage of a process via procfs Learn how to check if a process is CPU-bound or I/O bound Learn how to gather major fault / minor fault statistics, process priority, last CPU executing the process and scheduler statistics Learn how to get details of files open by the process, shared libraries mapped into process memory, and process memory map Learn about OOM score of a process and how to adjust them for specific use-case requirements Learn how to gather CGroup and Namespace details of a process Learn how to gather kernel stack info for a process, process physical memory mapping and thread information Learn how to build custom scripts / tools for monitor processes Requirements: Basic knowledge of Linux command-line that includes the shell, basic linux command for managing files and processes Knowledge of OS concepts and the Linux architecture covered in my course "Introduction to Linux Kernel Development" is preferred A working Linux environment with command-line interface using the bash shell or equivalent with administrative access ('root' user / sudo access) Description: Linux Process Monitoring and Diagnostics using the /proc Interface is a comprehensive course designed for system administrators, developers, and anyone looking to gain a deeper understanding of Linux process management. This course focuses on the /proc filesystem (procfs), an essential interface for monitoring, diagnosing, and analyzing Linux processes and system performance.Throughout the course, you'll learn how to explore and utilize procfs to gather critical process-specific information, including CPU and memory usage, file descriptors, I/O statistics, and thread details. We'll also cover system-wide statistics like CPU load, memory allocation, disk I/O, and network performance, all accessible via the /proc interface.Beyond monitoring, you'll dive into advanced topics like resource limits, scheduler statistics, and how to troubleshoot stuck processes using procfs. Real-time monitoring tools like top, slabtop, htop, ps, lsof, fuser, and many more command-line tools will be integrated into your workflow to give you hands-on experience with dynamic system diagnostics.By the end of the course, you'll have the skills to write custom scripts for process monitoring and diagnostics, automate system monitoring tasks, and interpret complex process data. Whether you're managing servers, debugging applications, or optimizing system performance, this course equips you with essential tools and knowledge for mastering Linux process internals. 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Free Download Linkedin - Using Generative AI in Public Relations Released 10/2024 With Martin Waxman MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill level: Beginner | Genre: eLearning | Language: English + subtitle | Duration: 42m 58s | Size: 61 MB Learn how to use AI for communication, brainstorming, content creation, and social sentiment analysis, reshaping your approach to PR in the digital age. Course details Discover the ever-evolving interface between generative AI and PR, focusing on strategic communication that forges meaningful relationships and achieves long-term organizational goals. Instructor Martin Waxman shows you how to conceptualize words as data by using generative AI for enhanced brainstorming, writing, editing, visual content creation, and more. Explore frameworks and approaches to prompt engineering uniquely tailored for PR professionals, as well as how to leverage AI for research, message testing, social listening, and policy development. Whether your role has you dealing with media, influencers, or stakeholders, this course offers practical insights you can apply on the job to leverage AI for efficient communication both internally and externally. By the end of this course, you'll be prepared to navigate the AI-driven landscape of PR with confidence and ease. Homepage https://www.linkedin.com/learning/using-generative-ai-in-public-relations Welcome to Check it Every Days Rapidgator https://rg.to/file/fc3b32fae8bf65d2068d22c02828e327/ngcat.Using.Generative.AI.in.Public.Relations.rar.html Fikper Free Download https://fikper.com/uP0HqVP8Y1/ngcat.Using.Generative.AI.in.Public.Relations.rar.html No Password - Links are Interchangeable

Free Download Linkedin - Using AI to Develop Buyer Personas Released: 10/2024 Duration: 31m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 75 MB Level: General | Genre: eLearning | Language: English Explore AI-driven marketing with Sherehan Ross, an accomplished marketer. This course covers the integration of AI to develop precise buyer personas, guides through the selection and use of AI tools, and examines the optimization and future trends of AI in marketing. Gain the skills to craft and implement targeted marketing strategies using AI insights. Homepage https://www.linkedin.com/learning/using-ai-to-develop-buyer-personas Rapidgator https://rg.to/file/8f6686afa041c6349e3a0ffb0d559dfb/kmtkj.Using.AI.to.Develop.Buyer.Personas.rar.html Fikper Free Download https://fikper.com/EfwrsYKtyh/kmtkj.Using.AI.to.Develop.Buyer.Personas.rar.html No Password - Links are Interchangeable

Free Download Linkedin - Negotiate a Raise Using Salary Data Released: 10/2024 Duration: 39m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 92 MB Level: General | Genre: eLearning | Language: English Ever felt undervalued at work? Grasp how to bridge that gap with Justin Sun, a global compensation advisor. This course demystifies the process of negotiating a raise using solid salary data. Justin shows you how to assess your market value and use salary surveys and research to your advantage. Gain the confidence to negotiate your worth effectively, backed by data and a deep understanding of the negotiation landscape. After this course, you'll be ready to negotiate for the pay you deserve. Homepage https://www.linkedin.com/learning/negotiate-a-raise-using-salary-data Rapidgator https://rg.to/file/7b9bc4bc97f5192c658c31eb6943f1c5/vomeq.Negotiate.a.Raise.Using.Salary.Data.rar.html Fikper Free Download https://fikper.com/zDs9jWegQo/vomeq.Negotiate.a.Raise.Using.Salary.Data.rar.html No Password - Links are Interchangeable

Free Download Learn Technical Drawings using Layouts in Rhino 3D Published 10/2024 Created by Agata Kycia MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 15 Lectures ( 1h 25m ) | Size: 741 MB Generating 2D Drawings from 3D Models with easy to follow videos in Rhinoceros 3D What you'll learn Architectural representation strategies: top views, sections, elevations Extracting technical drawings from 3D models 2D drawings in scale, linetypes and lineweights weights Exporting layouts Requirements No prior experience of the software is required. This class is intended for beginners Rhinoceros 5, 6 or 7 Installed in your PC Description In this course you will learn how to extract technical drawings from 3D models in Rhinoceros 3D. Technical drawings are essential for communicating ideas in industry, design and engineering. You will learn here how to adjust scale, dimensions, descriptions, lineweights and linetypes - all of it to present 3D models in an understandable way. I have been working with Rhinoceros 3D for over 18 years, using it as the main tool for design and fabrication in various fields and scales, and I aim to show you fast and easy ways to learn its functionality.Content of the course:Firstly, we will create a 3D model of a bottle. Then you will get to know how to use Layouts in Rhino and extract different 2D drawings: plans, sections, elevations and perspective views. Secondly, we will subdivide the 3D model into smaller parts and extract from it cutaway sections and exploded-view drawings. These drawings are very useful to explain more complex three-dimensional objects, thus used a lot in architecture and design fields.Whether you're an architect, designer, engineer or a hobbyist, you will learn here very useful skills of generating 2D drawings to clearly communicate your ideas. My tutorials are done with v5 version, but you can follow them without problems if you use higher versions such as v6 or v7. Thanks for your attention! Who this course is for Anyone interested in 3D modelling Architects Architecture students Designers Design students Engineers Homepage https://www.udemy.com/course/learn-technical-drawings-using-layouts-in-rhino-3d/ Screenshot Rapidgator https://rg.to/file/3e78225f87802280aa9c077ceaa8b8b1/trmdz.Learn.Technical.Drawings.using.Layouts.in.Rhino.3D.rar.html Fikper Free Download https://fikper.com/iSyAK3VGoa/trmdz.Learn.Technical.Drawings.using.Layouts.in.Rhino.3D.rar.html No Password - Links are Interchangeable

Free Download Learn Android App Development Using Kotlin From Zero to Hero Published 10/2024 Created by Jejji Singh Arora MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 31 Lectures ( 7h 17m ) | Size: 4 GB Android, Kotlin, Data Binding, Rest API Retrofit, Json Parsing What you'll learn Fundamental of Android Programming Hands on Projects Working with Complex Json Connecting with REST API Client Retrofit Requirements No Programming experienced needed Description Dive into the world of mobile app development with our comprehensive course on Android App Development using Kotlin. This course is designed for both beginners and those with some programming experience who want to learn how to create robust, user-friendly applications for the Android platform.What You Will Learn:Introduction to Kotlin:Understand the basics of Kotlin, its syntax, and features that make it a modern programming language.Learn about data types, control structures, functions, and object-oriented programming principles.Android Studio Setup:Get familiar with Android Studio, the official IDE for Android development.Learn how to set up your development environment, create new projects, and navigate the interface.Android Fundamentals:Explore the Android architecture, components, and the activity lifecycle.Understand how to manage resources, layouts, and views.User Interface Design:Design engaging user interfaces using XML and Kotlin.Learn about responsive design and best practices for creating intuitive layouts.Working with Data:Understand how to handle data storage using Shared Preferences, SQLite, and Room database.Learn how to make network requests and parse JSON data using Retrofit.Advanced Topics:Implement background tasks using Kotlin Coroutines.Explore the use of APIs, integrating third-party libraries, and using tools like Firebase for cloud storage and authentication.Testing and Debugging:Learn best practices for testing your applications, including unit tests and UI tests.Understand debugging techniques and how to optimize your app for performance.Publishing Your App:Gain insights into the app release process, including signing your app and publishing it on the Google Play Store.Course Format:Duration: 8-10 weeks, with weekly lectures and hands-on projects.Delivery Method: Online, with interactive sessions, coding exercises, and a capstone project.Who Should Enroll:Aspiring mobile developers.Software engineers looking to expand their skill set.Anyone interested in creating Android applications for personal or professional use.Prerequisites:Basic understanding of programming concepts. No prior experience with Kotlin or Android development is required.Join us on this journey to become a skilled Android developer and bring your app ideas to life!4o mini Who this course is for This Android Application Development course is designed for individuals who are looking to expand their programming skills, particularly in the context of Android app development and modern backend systems. It is suitable for: Beginner Programmers: Those with little to no prior experience in programming who want to start with a modern and versatile language like Kotlin. Experienced Programmers: Developers proficient in other languages (such as Java, Python, or C++) who want to enhance their skill set with Kotlin, especially for Android development. Android Developers: Professionals or enthusiasts aiming to transition to Kotlin for Android app development or to improve their existing Kotlin skills. Backend Developers: Engineers interested in using Kotlin for backend development using frameworks like Spring Boot or Ktor. Programming Enthusiasts: Individuals passionate about exploring new programming languages and paradigms, particularly those interested in learning Kotlin's concise syntax and powerful features. 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Free Download How to connect to ChatGPT using C# Last updated 8/2024 Created by Tom Liao MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + subtitle | Duration: 29 Lectures ( 2h 50m ) | Size: 1.7 GB Using ASP .Net Core Blazor server app to connect to OpenAI API What you'll learn Understand the concept of GPT and ChatGPT Know how to access OpenAI API using C# Learn the usage of parameters required by OpenAI API Develop a working GPT-enabled Blazor Server App Create your own C# library to access OpenAI API Requirements The enthusiasm for learning GenAI using C# (MUST) Basic knowledge of C# programming (MUST) Basic knowledge of ASP .Net Core web development (nice to have) Description Why should you subscribe to this course?Nowadays, almost all AI technologies' SDK or API start with Python. Support for C# comes second. Some don't even support C#. However, we C#ers (pronounced as CSharpers) know that C# is a powerful computing language that can create almost anything. It should be on the top of the list of AI development. As a programming tutor focusing primarily on C#-related technologies, I must contribute my knowledge to help anyone interested in using C# to develop AI-related applications. We don't need to be forced to switch to Python or other languages to learn AI, C# is just as good as the others. Sometimes, even better, in my own opinion! Therefore, this course focuses on using C# to bring ChatGPT to your applications by interacting with OpenAI's APIs. Grow with the giant!Bring Generative AI (GenAI) functionality, such as ChatGPT, to your application, is not as hard as a couple of years ago. With the emergence of ChatGPT and the APIs provided by OpenAI, we can stand on the giant's shoulder and grow with the giant. Accessing OpenAI API is all about accessing RESTful web API, and is easier than you might think. Firstly, you find out what data structure the API you want to connect to expects. Secondly, you learn the way C# is used to interact with sending and receiving data to and from those APIs. And finally, you develop a user interface for users to send prompts to those APIs and then display the responses to users.Pretty easy, right?I like to make everybody's life easier by making things easy to understand. The most efficient way to learn new things is not to learn too many "fundamentals" or "theories" at the beginning, but to learn how to build something useful with minimum pieces of knowledge. Then dive deeper later when you have a total picture of what's going on in your head. This is also how this course is organized. What will you learn?The following lists the main topics of this course. 1. A GPT course for C# developers - The brief introduction of the course and the tutor.2. Intro of GPT, ChatGPT and OpenAI API - The brief introduction of what GPT is, the evolution of ChatGPT, and what kinds of API you can use.3. Preparing the prerequisites - Introductions on creating an OpenAI account, setting up a payment method, and creating a secret API key.4. Quick Start - Work with ChatGPT to create the first Blazor Server App that accesses OpenAI API. (gpt-3.5-turbo)5. Chat Completion API - Explain the definition and usage of parameters required by OpenAI API. And also to modify the Blazor Server App created earlier to make it work better and look better. 6. Chat Completion API - Streaming mode - Learn how to activate the streaming mode and receive chat completion chunk objects from the chat completion API.7. What's next? - A brief introduction of what to learn after completing this course.Prerequisites:I set this course level to "all levels", that's for anybody new to using C# to develop GenAI applications' point of view. But it does need some prerequisites as follows:The enthusiasm for learning GenAI using C# (MUST)Basic knowledge of C# programming (MUST)Basic knowledge of ASP .Net Core web development (nice to have)Who is this course for?Anyone who wants to bring ChatGPT capability to C# applications.All C#ers (CSharpers) or C#ers wanna be! Who this course is for Anyone who wants to bring ChatGPT capability to C# applications. All C#ers (CSharpers) or C#ers wanna be! Homepage https://www.udemy.com/course/how-to-connect-to-chatgpt-using-csharp/ Screenshot Rapidgator https://rg.to/file/bb6348aa867db73f2eb4474ca55259a8/ctjhj.How.to.connect.to.ChatGPT.using.C.part2.rar.html https://rg.to/file/cedc337108f5b1bac4e3e341c751d725/ctjhj.How.to.connect.to.ChatGPT.using.C.part1.rar.html Fikper Free Download https://fikper.com/liHYPnaGgj/ctjhj.How.to.connect.to.ChatGPT.using.C.part2.rar.html https://fikper.com/mIuPpvU5le/ctjhj.How.to.connect.to.ChatGPT.using.C.part1.rar.html No Password - Links are Interchangeable

Free Download Gym Workout Using Machines And Cables Only Last updated 5/2022 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 930.91 MB | Duration: 0h 55m Build muscles at the gym without lifting free weights, straight forward exercises nothing complicated What you'll learn You will learn how to train your whole body effectively without using free weights Straight forward exercises nothing complicated, simple but very effective Directed to beginners and intermediate people Build muscles without lifting free weights Requirements Having access to a gym Description Good day everybody,I am coach Ramzi and in this course description I am going to tell you about this perfect machines and cables only workout program.This program is directed to beginners and intermediate people, or in fact anybody who want to build muscle without lifting free weights.The program structure will be as follow:Every three working out days we are going to take one day rest. We are going to start with Chest and tri chest focused workout, Back and biceps back focused workout, Shoulders and legs shoulders focused workout.then we will take one day Rest and we get back Triceps and chest triceps focused workout. Biceps and back biceps focused workout. Legs and shoulders legs focused workout. Then we are going to take another day Rest.Stick to this program for at least 8 weeks and you will see great results.Free weights verses machines, every option have it's benefits, one of the crucial benefits of using machine is Safety:Safety:When used properly, free-weight equipment like barbells, dumbbells, kettlebells and medicine balls can be extremely effective. However, if an individual lacks a base level of strength or basic movement skills, using this equipment could increase the risk of injury. Even if an individual is strong, the ego is sometimes stronger, causing him to lift a weight that is heavier than his existing level of strength. While overloading a barbell for a squat or bench press could cause serious injury, machines allow a user to lift with maximal loads with a minimal risk of injury from falling weights. Wish you all the best have a nice day. Overview Section 1: Warm up Lecture 1 10 min warm up routine Section 2: Day 1 - Day 8 Lecture 2 Day 1 Lecture 3 Day 2 Lecture 4 Day 3 Lecture 5 Day 4 Lecture 6 Day 5 Lecture 7 Day 6 Lecture 8 Day 7 Lecture 9 Day 8 beginners and intermediate people, and anybody who want to build muscles without lifting free weights Screenshot Homepage https://www.udemy.com/course/machines-cables/ Rapidgator https://rg.to/file/49f4d7b0062acb8bb5a3fc36d20709c7/aebit.Gym.Workout.Using.Machines.And.Cables.Only.rar.html Fikper Free Download https://fikper.com/wr1fGs3hyK/aebit.Gym.Workout.Using.Machines.And.Cables.Only.rar.html No Password - Links are Interchangeable

Free Download Generate Data Insights Using the Analyze Data Feature in Microsoft Excel Released 10/2024 By Matt Stenzel MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 14m 4s | Size: 42 MB Are you looking to save time and unlock the power of your data by using familiar data analysis tools? This course will teach you how to use the analyze data feature in Microsoft Excel to gain insights from your data. Are you looking to save time and unlock the power of your data by using familiar data analysis tools? This course will teach you how to use the analyze data feature in Microsoft Excel to gain insights from your data. In today's world, there are many amazing tools that can help make you more productive and give you insights over large amounts of data. In this course, Generate Data Insights Using the Analyze Data Feature in Microsoft Excel, you'll gain knowledge of this tool and experience it firsthand. You will see how you can use natural language and have the tool suggest questions and fields that could be valuable for data analysis. When you're finished with this course, you'll have a better understanding of the benefits and limitations of the analyze data feature in Microsoft Excel. Homepage https://www.pluralsight.com/courses/microsoft-excel-generate-insights-analyze-data-feature Rapidgator https://rg.to/file/d61d2424ddcc8068455fa246398d641c/xaeqn.Generate.Data.Insights.Using.the.Analyze.Data.Feature.in.Microsoft.Excel.rar.html Fikper Free Download https://fikper.com/GKt9iaZQw0/xaeqn.Generate.Data.Insights.Using.the.Analyze.Data.Feature.in.Microsoft.Excel.rar.html No Password - Links are Interchangeable

Free Download Exploring Data Science with .NET using Polyglot Notebooks & ML.NET Released 10/2024 With Matt Eland MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 2h 1m 11s | Size: 220 MB Learn to conduct data analytics and data science experiments using Polyglot Notebooks. Explore core concepts, language support, data ingestion, exploratory analysis, and more. Course details In this course, Matt Eland-an AI specialist, Microsoft MVP, and author-equips experienced .NET developers with the skills to conduct data analytics and data science experiments using Polyglot Notebooks. Dive into the core of Polyglot Notebooks, its relationship to Jupyter Notebooks, and language support for C#, F#, PowerShell, SQL, and Mermaid diagrams. Learn data ingestion, sharing between kernels, exploratory data analysis with descriptive statistics, and data visualization using libraries like Microsoft.Data.Analysis, ScottPlot, and Plotly.NET. Explore basic machine learning concepts, model training, train/test splits, evaluation, and beginner classification/regression experiments with ML.NET's AutoML capabilities. Plus, cover advanced Polyglot Notebooks integrations like Azure OpenAI, Semantic Kernel, Sequence Diagram Generation, and Azure AI Services. Homepage https://www.linkedin.com/learning/exploring-data-science-with-dot-net-using-polyglot-notebooks-ml-dot-net Screenshot Rapidgator https://rg.to/file/40359c14c04405724635b2026176eab2/ncxwf.Exploring.Data.Science.with..NET.using.Polyglot.Notebooks..ML.NET.rar.html Fikper Free Download https://fikper.com/gSCMb4kosU/ncxwf.Exploring.Data.Science.with..NET.using.Polyglot.Notebooks..ML.NET.rar.html No Password - Links are Interchangeable

Free Download Elevate Employer Branding Using Employee Value Proposition Published 10/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 119.28 MB | Duration: 0h 49m Masterclass- Strategies to Attract, Engage, and Retain top talents. Align employee and company goals for maximum impact What you'll learn Learn what an EVP is and why it's a critical part of your overall business strategy. Gain a deep understanding of the key components. Discover how to assess your current EVP through audits and employee feedback. Identify gaps and opportunities to improve. Identify and manage organisational risks Learn how to integrate your EVP into recruitment, onboarding, and retention strategies. Be able to clearly define your EVP and align it with your organizational goals and culture. Know how to measure and refine your EVP to ensure it continuously meets the needs of your workforce and the evolving job market. Requirements You will learn everything you need to know about this topic. No need of previous experience conducting EVP Description In today's competitive job market, a strong Employee Value Proposition (EVP) is your secret weapon for attracting, engaging, and retaining top talent. Employees are no longer just seeking high salaries-they want meaningful work, development opportunities, and a workplace that aligns with their values and goals. This comprehensive course will teach you how to create a compelling EVP that resonates with the modern workforce and sets your organisation apart.Designed for HR professionals, leaders, business owners, and anyone involved in talent management, this course will guide you step-by-step through the fundamentals of EVP. You'll learn how to assess your current offerings, define your organization's unique value, and communicate it effectively to employees and candidates alike.Throughout this masterclass, you will gain a deeper understanding of what truly drives employee satisfaction and how you can leverage your EVP to foster a high-performing, motivated workforce. You will discover practical techniques to create an EVP that reflects your organization's core values and long-term vision.During this masterclass, you will learn what the Components of EVP are, how to define Your Organization's EVP, and how to implement EVP strategies effectively.Enroll today and start building an EVP that attracts, engages, and retains the very best talent for your organisation! Overview Section 1: Introduction to Employee Value Proposition (EVP) Lecture 1 Induction Lecture 2 Defining EVP Lecture 3 Why EVP Matters? Lecture 4 Key Components of EVP Section 2: Defining Your Organization's EVP Lecture 5 Induction Lecture 6 Conducting an EVP Audit Lecture 7 Crafting a Compelling EVP Statement and conclusion Section 3: Components of EVP Lecture 8 Compensation and Benefits Lecture 9 Career Development and Growth Opportunities Lecture 10 Work Environment and Culture Lecture 11 Work-Life Balance and Well-being Lecture 12 Conclusion and Materials Section 4: Implementing EVP Strategies Lecture 13 Induction Lecture 14 Communicating EVP Effectively to Internal and External Stakeholders Lecture 15 Case Studies Lecture 16 Integrating EVP into Recruitment, Onboarding, and Retention Strategies Lecture 17 Measuring the Effectiveness of EVP Initiatives and Making Adjustments as Needed Lecture 18 Conclusion Section 5: Recap of key learning and takeaways Lecture 19 Recap of Key Learning and Takeaways Beginner HR and People and Culture professionals, Employee branding professionals https://www.udemy.com/course/elevate-employer-branding-using-employee-value-proposition/ Rapidgator https://rg.to/file/829a654c2295e54c8199053ab7e97c0d/jwido.Elevate.Employer.Branding.Using.Employee.Value.Proposition.rar.html Fikper Free Download https://fikper.com/7V4gLtYdcu/jwido.Elevate.Employer.Branding.Using.Employee.Value.Proposition.rar.html No Password - Links are Interchangeable

Free Download Data Visualization Using Tableau by IIBM Institute Published 10/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 5.63 GB | Duration: 12h 46m "Data Visualization Using Tableau : Data Visualization ,Tableau ,Dashboard, Data Analysis ,Interactive Reporting." What you'll learn Data Visualization Techniques: Learn to create and interpret various graph types, including bar and line graphs, for effective data representation. Geographic Mapping and Data Integration: Utilize geographic location mapping and understand different join types and data blending for comprehensive analysis. Dashboard Design and Interactivity: Develop interactive dashboards using grouping, highlighting, and tooltips to enhance data presentation. Advanced Analytics: Implement clustering and regression analysis to uncover insights and relationships within the data. Practical Application and Storytelling: Apply learned concepts through hands-on exercises, creating compelling data stories that communicate insights effectivel Requirements To enroll in this Tableau course, parti[beeep]nts should have basic computer skills and a foundational understanding of data concepts. Access to Tableau Desktop or Tableau Public is necessary for practical exercises. An analytical mindset and curiosity about data visualization will enhance the learning experience, enabling parti[beeep]nts to effectively explore and communicate insights through data storytelling. Description In the "Data Visualization Using Tableau" course, you'll embark on a comprehensive journey to master one of the leading tools for data visualization. This course is designed for individuals who want to transform complex data into insightful and engaging visual stories. Starting with the basics, you'll learn how to navigate Tableau's interface and utilize its powerful features to create a variety of visualizations, including charts, graphs, and maps. The curriculum covers essential topics such as data connection, preparation, and cleaning, ensuring you can work with diverse datasets effectively.You'll delve into the principles of effective dashboard design, creating interactive dashboards that allow users to explore data dynamically. Advanced analytics techniques, such as calculated fields and forecasting, will empower you to derive deeper insights from your data.Through hands-on exercises and real-world projects, you'll develop the skills needed to communicate your findings clearly and effectively. By the end of this course, you'll be equipped to make data-driven decisions and present compelling narratives that influence your audience, making you a valuable asset in any data-driven organization. Join us to unlock the full potential of your data.Learn to create impactful data visualizations using Tableau for effective storytelling.IIBM Institute of Business Management Overview Section 1: Introduction Lecture 1 Tableau- Introduction to Graphs Section 2: Tableau-Geographic Location Mapping Lecture 2 Tableau-Geographic Location Mapping Section 3: Tableau-Bar Graph Line Graph and Filters Lecture 3 Tableau-Bar Graph Line Graph and Filters Section 4: Tableau-Different Types of Joins Lecture 4 Tableau-Different Types of Joins Section 5: Tableau Data Blending Lecture 5 Tableau Data Blending Section 6: Tableau Storyline Creation Lecture 6 Tableau Storyline Creation Section 7: Tableau Data Interpreters and Cleaning Lecture 7 Tableau Data Interpreters and Cleaning Section 8: Tableau Dashboard Concepts Lecture 8 Tableau Dashboard Concepts Section 9: Tableau Grouping and Highlighters Lecture 9 Tableau Grouping and Highlighters Section 10: Tableau Cluster Creation and Modelling Lecture 10 Tableau Cluster Creation and Modelling Section 11: Tableau Regression Analysis Lecture 11 Tableau Regression Analysis Section 12: Tableau Step Up, Tool Tip Analysis and Grouping Lecture 12 Tableau Step Up, Tool Tip Analysis and Grouping Section 13: Project- Attrition Analysis and Bank Loan Modelling Lecture 13 Project- Attrition Analysis and Bank Loan Modelling Lecture 0 Solution-HR Analytics-Attrition Analysis Lecture 0 Bank Loan Modelling and Complete Revision This course is for data analysts, business professionals, and beginners eager to enhance their data visualization skills in Tableau for effective decision-making and insights presentation. 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Free Download Data Engineering using AWS Data Analytics Last updated 2/2023 Created by Durga Viswanatha Raju Gadiraju,Pratik Kumar,Sathvika Dandu,Madhuri Gadiraju,Sai Varma,Phani Bhushan Bozzam MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + subtitle | Duration: 434 Lectures ( 26h 15m ) | Size: 7.77 GB Build Data Engineering Pipelines on AWS using Data Analytics Services - Glue, EMR, Athena, Kinesis, Lambda, Redshift What you'll learn Data Engineering leveraging Services under AWS Data Analytics AWS Essentials such as s3, IAM, EC2, etc Understanding AWS s3 for cloud based storage Understanding details related to virtual machines on AWS known as EC2 Managing AWS IAM users, groups, roles and policies for RBAC (Role Based Access Control) Managing Tables using AWS Glue Catalog Engineering Batch Data Pipelines using AWS Glue Jobs Orchestrating Batch Data Pipelines using AWS Glue Workflows Running Queries using AWS Athena - Server less query engine service Using AWS Elastic Map Reduce (EMR) Clusters for building Data Pipelines Using AWS Elastic Map Reduce (EMR) Clusters for reports and dashboards Data Ingestion using AWS Lambda Functions Scheduling using AWS Events Bridge Engineering Streaming Pipelines using AWS Kinesis Streaming Web Server logs using AWS Kinesis Firehose Overview of data processing using AWS Athena Running AWS Athena queries or commands using CLI Running AWS Athena queries using Python boto3 Creating AWS Redshift Cluster, Create tables and perform CRUD Operations Copy data from s3 to AWS Redshift Tables Understanding Distribution Styles and creating tables using Distkeys Running queries on external RDBMS Tables using AWS Redshift Federated Queries Running queries on Glue or Athena Catalog tables using AWS Redshift Spectrum Requirements A Computer with at least 8 GB RAM Programming Experience using Python is highly desired as some of the topics are demonstrated using Python SQL Experience is highly desired as some of the topics are demonstrated using SQL Nice to have Data Engineering Experience using Pandas or Pyspark This course is ideal for experienced data engineers to add AWS Analytics Services as key skills to their profile Description Data Engineering is all about building Data Pipelines to get data from multiple sources into Data Lakes or Data Warehouses and then from Data Lakes or Data Warehouses to downstream systems. As part of this course, I will walk you through how to build Data Engineering Pipelines using AWS Data Analytics Stack. It includes services such as Glue, Elastic Map Reduce (EMR), Lambda Functions, Athena, EMR, Kinesis, and many more.Here are the high-level steps which you will follow as part of the course.Setup Development EnvironmentGetting Started with AWSStorage - All about AWS s3 (Simple Storage Service)User Level Security - Managing Users, Roles, and Policies using IAMInfrastructure - AWS EC2 (Elastic Cloud Compute)Data Ingestion using AWS Lambda FunctionsOverview of AWS Glue ComponentsSetup Spark History Server for AWS Glue JobsDeep Dive into AWS Glue CatalogExploring AWS Glue Job APIsAWS Glue Job BookmarksDevelopment Life Cycle of PysparkGetting Started with AWS EMRDeploying Spark Applications using AWS EMRStreaming Pipeline using AWS KinesisConsuming Data from AWS s3 using boto3 ingested using AWS KinesisPopulating GitHub Data to AWS DynamodbOverview of Amazon AWS AthenaAmazon AWS Athena using AWS CLIAmazon AWS Athena using Python boto3Getting Started with Amazon AWS RedshiftCopy Data from AWS s3 into AWS Redshift TablesDevelop Applications using AWS Redshift ClusterAWS Redshift Tables with Distkeys and SortkeysAWS Redshift Federated Queries and SpectrumHere are the details about what you will be learning as part of this course. We will cover most of the commonly used services with hands-on practice which are available under AWS Data Analytics.Getting Started with AWSAs part of this section, you will be going through the details related to getting started with AWS.Introduction - AWS Getting StartedCreate s3 BucketCreate AWS IAM Group and AWS IAM User to have required access on s3 Bucket and other servicesOverview of AWS IAM RolesCreate and Attach Custom AWS IAM Policy to both AWS IAM Groups as well as UsersConfigure and Validate AWS CLI to access AWS Services using AWS CLI CommandsStorage - All about AWS s3 (Simple Storage Service)AWS s3 is one of the most prominent fully managed AWS services. All IT professionals who would like to work on AWS should be familiar with it. We will get into quite a few common features related to AWS s3 in this section.Getting Started with AWS S3Setup Data Set locally to upload to AWS s3Adding AWS S3 Buckets and Managing Objects (files and folders) in AWS s3 bucketsVersion Control for AWS S3 BucketsCross-Region Replication for AWS S3 BucketsOverview of AWS S3 Storage ClassesOverview of AWS S3 GlacierManaging AWS S3 using AWS CLI CommandsManaging Objects in AWS S3 using CLI - LabUser Level Security - Managing Users, Roles, and Policies using IAMOnce you start working on AWS, you need to understand the permissions you have as a non-admin user. As part of this section, you will understand the details related to AWS IAM users, groups, roles as well as policies.Creating AWS IAM UsersLogging into AWS Management Console using AWS IAM UserValidate Programmatic Access to AWS IAM UserAWS IAM Identity-based PoliciesManaging AWS IAM GroupsManaging AWS IAM RolesOverview of Custom AWS IAM PoliciesManaging AWS IAM users, groups, roles as well as policies using AWS CLI CommandsInfrastructure - AWS EC2 (Elastic Cloud Compute) BasicsAWS EC2 Instances are nothing but virtual machines on AWS. As part of this section, we will go through some of the basics related to AWS EC2 Basics.Getting Started with AWS EC2Create AWS EC2 Key PairLaunch AWS EC2 InstanceConnecting to AWS EC2 InstanceAWS EC2 Security Groups BasicsAWS EC2 Public and Private IP AddressesAWS EC2 Life CycleAllocating and Assigning AWS Elastic IP AddressManaging AWS EC2 Using AWS CLIUpgrade or Downgrade AWS EC2 InstancesInfrastructure - AWS EC2 AdvancedIn this section, we will continue with AWS EC2 to understand how we can manage EC2 instances using AWS Commands and also how to install additional OS modules leveraging bootstrap scripts.Getting Started with AWS EC2Understanding AWS EC2 MetadataQuerying on AWS EC2 MetadataFitering on AWS EC2 MetadataUsing Bootstrapping Scripts with AWS EC2 Instances to install additional softwares on AWS EC2 instancesCreate an AWS AMI using AWS EC2 InstancesValidate AWS AMI - LabData Ingestion using Lambda FunctionsAWS Lambda functions are nothing but serverless functions. In this section, we will understand how we can develop and deploy Lambda functions using Python as a programming language. We will also see how to maintain a bookmark or checkpoint using s3.Hello World using AWS LambdaSetup Project for local development of AWS Lambda FunctionsDeploy Project to AWS Lambda consoleDevelop download functionality using requests for AWS Lambda FunctionsUsing 3rd party libraries in AWS Lambda FunctionsValidating AWS s3 access for local development of AWS Lambda FunctionsDevelop upload functionality to s3 using AWS Lambda FunctionsValidating AWS Lambda Functions using AWS Lambda ConsoleRun AWS Lambda Functions using AWS Lambda ConsoleValidating files incrementally downloaded using AWS Lambda FunctionsReading and Writing Bookmark to s3 using AWS Lambda FunctionsMaintaining Bookmark on s3 using AWS Lambda FunctionsReview the incremental upload logic developed using AWS Lambda FunctionsDeploying AWS Lambda FunctionsSchedule AWS Lambda Functions using AWS Event BridgeOverview of AWS Glue ComponentsIn this section, we will get a broad overview of all important Glue Components such as Glue Crawler, Glue Databases, Glue Tables, etc. We will also understand how to validate Glue tables using AWS Athena. AWS Glue (especially Glue Catalog) is one of the key components in the realm of AWS Data Analytics Services.Introduction - Overview of AWS Glue ComponentsCreate AWS Glue Crawler and AWS Glue Catalog Database as well as TableAnalyze Data using AWS AthenaCreating AWS S3 Bucket and Role to create AWS Glue Catalog Tables using Crawler on the s3 locationCreate and Run the AWS Glue Job to process data in AWS Glue Catalog TablesValidate using AWS Glue Catalog Table and by running queries using AWS AthenaCreate and Run AWS Glue TriggerCreate AWS Glue WorkflowRun AWS Glue Workflow and ValidateSetup Spark History Server for AWS Glue JobsAWS Glue uses Apache Spark under the hood to process the data. It is important we setup Spark History Server for AWS Glue Jobs to troubleshoot any issues.Introduction - Spark History Server for AWS GlueSetup Spark History Server on AWSClone AWS Glue Samples repositoryBuild AWS Glue Spark UI ContainerUpdate AWS IAM Policy PermissionsStart AWS Glue Spark UI ContainerDeep Dive into AWS Glue CatalogAWS Glue has several components, but the most important ones are nothing but AWS Glue Crawlers, Databases as well as Catalog Tables. In this section, we will go through some of the most important and commonly used features of the AWS Glue Catalog.Prerequisites for AWS Glue Catalog TablesSteps for Creating AWS Glue Catalog TablesDownload Data Set to use to create AWS Glue Catalog TablesUpload data to s3 to crawl using AWS Glue Crawler to create required AWS Glue Catalog TablesCreate AWS Glue Catalog Database - itvghlandingdbCreate AWS Glue Catalog Table - ghactivityRunning Queries using AWS Athena - ghactivityCrawling Multiple Folders using AWS Glue CrawlersManaging AWS Glue Catalog using AWS CLIManaging AWS Glue Catalog using Python Boto3Exploring AWS Glue Job APIsOnce we deploy AWS Glue jobs, we can manage them using AWS Glue Job APIs. In this section we will get overview of AWS Glue Job APIs to run and manage the jobs.Update AWS IAM Role for AWS Glue JobGenerate baseline AWS Glue JobRunning baseline AWS Glue JobAWS Glue Script for Partitioning DataValidating using AWS AthenaUnderstanding AWS Glue Job BookmarksAWS Glue Job Bookmarks can be leveraged to maintain the bookmarks or checkpoints for incremental loads. In this section, we will go through the details related to AWS Glue Job Bookmarks.Introduction to AWS Glue Job BookmarksCleaning up the data to run AWS Glue JobsOverview of AWS Glue CLI and CommandsRun AWS Glue Job using AWS Glue BookmarkValidate AWS Glue Bookmark using AWS CLIAdd new data to the landing zone to run AWS Glue Jobs using BookmarksRerun AWS Glue Job using BookmarkValidate AWS Glue Job Bookmark and Files for Incremental runRecrawl the AWS Glue Catalog Table using AWS CLI CommandsRun AWS Athena Queries for Data ValidationDevelopment Lifecycle for PysparkIn this section, we will focus on the development of Spark applications using Pyspark. We will use this application later while exploring EMR in detail.Setup Virtual Environment and Install PysparkGetting Started with PycharmPassing Run Time ArgumentsAccessing OS Environment VariablesGetting Started with SparkCreate Function for Spark SessionSetup Sample DataRead data from filesProcess data using Spark APIsWrite data to filesValidating Writing Data to FilesProductionizing the CodeGetting Started with AWS EMR (Elastic Map Reduce)As part of this section, we will understand how to get started with AWS EMR Cluster. We will primarily focus on AWS EMR Web Console. Elastic Map Reduce is one of the key service in AWS Data Analytics Services which provide capability to run applications which process large scale data leveraging distributed computing frameworks such as Spark.Planning for AWS EMR ClusterCreate AWS EC2 Key Pair for AWS EMR ClusterSetup AWS EMR Cluster with Apache SparkUnderstanding Summary of AWS EMR ClusterReview AWS EMR Cluster Application User InterfacesReview AWS EMR Cluster MonitoringReview AWS EMR Cluster Hardware and Cluster Scaling PolicyReview AWS EMR Cluster ConfigurationsReview AWS EMR Cluster EventsReview AWS EMR Cluster StepsReview AWS EMR Cluster Bootstrap ActionsConnecting to AWS EMR Master Node using SSHDisabling Termination Protection for AWS EMR Cluster and Terminating the AWS EMR ClusterClone and Create a New AWS EMR ClusterListing AWS S3 Buckets and Objects using AWS CLI on AWS EMR ClusterListing AWS S3 Buckets and Objects using HDFS CLI on AWS EMR ClusterManaging Files in AWS S3 using HDFS CLI on AWS EMR ClusterReview AWS Glue Catalog Databases and TablesAccessing AWS Glue Catalog Databases and Tables using AWS EMR ClusterAccessing spark-sql CLI of AWS EMR ClusterAccessing pyspark CLI of AWS EMR ClusterAccessing spark-shell CLI of AWS EMR ClusterCreate AWS EMR Cluster for NotebooksDeploying Spark Applications using AWS EMRAs part of this section, we will understand how we typically deploy Spark Applications using AWS EMR. We will be using the Spark Application we deployed earlier.Deploying Applications using AWS EMR - IntroductionSetup AWS EMR Cluster to deploy applicationsValidate SSH Connectivity to Master node of AWS EMR ClusterSetup Jupyter Notebook Environment on AWS EMR ClusterCreate required AWS s3 Bucket for AWS EMR ClusterUpload GHActivity Data to s3 so that we can process using Spark Application deployed on AWS EMR ClusterValidate Application using AWS EMR Compatible Versions of Python and SparkDeploy Spark Application to AWS EMR Master NodeCreate user space for ec2-user on AWS EMR ClusterRun Spark Application using spark-submit on AWS EMR Master NodeValidate Data using Jupyter Notebooks on AWS EMR ClusterClone and Start Auto Terminated AWS EMR ClusterDelete Data Populated by GHAcitivity Application using AWS EMR ClusterDifferences between Spark Client and Cluster Deployment Modes on AWS EMR ClusterRunning Spark Application using Cluster Mode on AWS EMR ClusterOverview of Adding Pyspark Application as Step to AWS EMR ClusterDeploy Spark Application to AWS S3 to run using AWS EMR StepsRunning Spark Applications as AWS EMR Steps in client modeRunning Spark Applications as AWS EMR Steps in cluster modeValidate AWS EMR Step Execution of Spark ApplicationStreaming Data Ingestion Pipeline using AWS KinesisAs part of this section, we will go through details related to the streaming data ingestion pipeline using AWS Kinesis which is a streaming service of AWS Data Analytics Services. We will use AWS Kinesis Firehose Agent and AWS Kinesis Delivery Stream to read the data from log files and ingest it into AWS s3.Building Streaming Pipeline using AWS Kinesis Firehose Agent and Delivery StreamRotating Logs so that the files are created frequently which will be eventually ingested using AWS Kinesis Firehose Agent and AWS Kinesis Firehose Delivery StreamSet up AWS Kinesis Firehose Agent to get data from logs into AWS Kinesis Delivery Stream.Create AWS Kinesis Firehose Delivery StreamPlanning the Pipeline to ingest data into s3 using AWS Kinesis Delivery StreamCreate AWS IAM Group and User for Streaming Pipelines using AWS Kinesis ComponentsGranting Permissions to AWS IAM User using Policy for Streaming Pipelines using AWS Kinesis ComponentsConfigure AWS Kinesis Firehose Agent to read the data from log files and ingest it into AWS Kinesis Firehose Delivery Stream.Start and Validate AWS Kinesis Firehose AgentConclusion - Building Simple Steaming Pipeline using AWS Kinesis FirehoseConsuming Data from AWS s3 using Python boto3 ingested using AWS KinesisAs data is ingested into AWS S3, we will understand how data can ingested in AWS s3 can be processed using boto3.Customizing AWS s3 folder using AWS Kinesis Delivery StreamCreate AWS IAM Policy to read from AWS s3 BucketValidate AWS s3 access using AWS CLISetup Python Virtual Environment to explore boto3Validating access to AWS s3 using Python boto3Read Content from AWS s3 objectRead multiple AWS s3 ObjectsGet the number of AWS s3 Objects using MarkerGet the size of AWS s3 Objects using MarkerPopulating GitHub Data to AWS DynamodbAs part of this section, we will understand how we can populate data to AWS Dynamodb tables using Python as a programming language.Install required libraries to get GitHub Data to AWS Dynamodb tables.Understanding GitHub APIsSetting up GitHub API TokenUnderstanding GitHub Rate LimitCreate New Repository for sinceExtracting Required Information using PythonProcessing Data using PythonGrant Permissions to create AWS dynamodb tables using boto3Create AWS Dynamodb TablesAWS Dynamodb CRUD OperationsPopulate AWS Dynamodb TableAWS Dynamodb Batch OperationsOverview of Amazon AWS AthenaAs part of this section, we will understand how to get started with AWS Athena using AWS Web console. We will also focus on basic DDL and DML or CRUD Operations using AWS Athena Query Editor.Getting Started with Amazon AWS AthenaQuick Recap of AWS Glue Catalog Databases and TablesAccess AWS Glue Catalog Databases and Tables using AWS Athena Query EditorCreate a Database and Table using AWS AthenaPopulate Data into Table using AWS AthenaUsing CTAS to create tables using AWS AthenaOverview of Amazon AWS Athena ArchitectureAmazon AWS Athena Resources and relationship with HiveCreate a Partitioned Table using AWS AthenaDevelop Query for Partitioned ColumnInsert into Partitioned Tables using AWS AthenaValidate Data Partitioning using AWS AthenaDrop AWS Athena Tables and Delete Data FilesDrop Partitioned Table using AWS AthenaData Partitioning in AWS Athena using CTASAmazon AWS Athena using AWS CLIAs part of this section, we will understand how to interact with AWS Athena using AWS CLI Commands.Amazon AWS Athena using AWS CLI - IntroductionGet help and list AWS Athena databases using AWS CLIManaging AWS Athena Workgroups using AWS CLIRun AWS Athena Queries using AWS CLIGet AWS Athena Table Metadata using AWS CLIRun AWS Athena Queries with a custom location using AWS CLIDrop AWS Athena table using AWS CLIRun CTAS under AWS Athena using AWS CLIAmazon AWS Athena using Python boto3As part of this section, we will understand how to interact with AWS Athena using Python boto3.Amazon AWS Athena using Python boto3 - IntroductionGetting Started with Managing AWS Athena using Python boto3List Amazon AWS Athena Databases using Python boto3List Amazon AWS Athena Tables using Python boto3Run Amazon AWS Athena Queries with boto3Review AWS Athena Query Results using boto3Persist Amazon AWS Athena Query Results in Custom Location using boto3Processing AWS Athena Query Results using PandasRun CTAS against Amazon AWS Athena using Python boto3Getting Started with Amazon AWS RedshiftAs part of this section, we will understand how to get started with AWS Redshift using AWS Web console. We will also focus on basic DDL and DML or CRUD Operations using AWS Redshift Query Editor.Getting Started with Amazon AWS Redshift - IntroductionCreate AWS Redshift Cluster using Free TrialConnecting to Database using AWS Redshift Query EditorGet a list of tables querying information schemaRun Queries against AWS Redshift Tables using Query EditorCreate AWS Redshift Table using Primary KeyInsert Data into AWS Redshift TablesUpdate Data in AWS Redshift TablesDelete data from AWS Redshift tablesRedshift Saved Queries using Query EditorDeleting AWS Redshift ClusterRestore AWS Redshift Cluster from SnapshotCopy Data from s3 into AWS Redshift TablesAs part of this section, we will go through the details about copying data from s3 into AWS Redshift tables using the AWS Redshift Copy command.Copy Data from s3 to AWS Redshift - IntroductionSetup Data in s3 for AWS Redshift CopyCopy Database and Table for AWS Redshift Copy CommandCreate IAM User with full access on s3 for AWS Redshift CopyRun Copy Command to copy data from s3 to AWS Redshift TableTroubleshoot Errors related to AWS Redshift Copy CommandRun Copy Command to copy from s3 to AWS Redshift tableValidate using queries against AWS Redshift TableOverview of AWS Redshift Copy CommandCreate IAM Role for AWS Redshift to access s3Copy Data from s3 to AWS Redshift table using IAM RoleSetup JSON Dataset in s3 for AWS Redshift Copy CommandCopy JSON Data from s3 to AWS Redshift table using IAM RoleDevelop Applications using AWS Redshift ClusterAs part of this section, we will understand how to develop applications against databases and tables created as part of AWS Redshift Cluster.Develop application using AWS Redshift Cluster - IntroductionAllocate Elastic Ip for AWS Redshift ClusterEnable Public Accessibility for AWS Redshift ClusterUpdate Inbound Rules in Security Group to access AWS Redshift ClusterCreate Database and User in AWS Redshift ClusterConnect to the database in AWS Redshift using psqlChange Owner on AWS Redshift TablesDownload AWS Redshift JDBC Jar fileConnect to AWS Redshift Databases using IDEs such as SQL WorkbenchSetup Python Virtual Environment for AWS RedshiftRun Simple Query against AWS Redshift Database Table using PythonTruncate AWS Redshift Table using PythonCreate IAM User to copy from s3 to AWS Redshift TablesValidate Access of IAM User using Boto3Run AWS Redshift Copy Command using PythonAWS Redshift Tables with Distkeys and SortkeysAs part of this section, we will go through AWS Redshift-specific features such as distribution keys and sort keys to create AWS Redshift tables.AWS Redshift Tables with Distkeys and Sortkeys - IntroductionQuick Review of AWS Redshift ArchitectureCreate multi-node AWS Redshift ClusterConnect to AWS Redshift Cluster using Query EditorCreate AWS Redshift DatabaseCreate AWS Redshift Database UserCreate AWS Redshift Database SchemaDefault Distribution Style of AWS Redshift TableGrant Select Permissions on Catalog to AWS Redshift Database UserUpdate Search Path to query AWS Redshift system tablesValidate AWS Redshift table with DISTSTYLE AUTOCreate AWS Redshift Cluster from Snapshot to the original stateOverview of Node Slices in AWS Redshift ClusterOverview of Distribution Styles related to AWS Redshift tablesDistribution Strategies for retail tables in AWS Redshift DatabasesCreate AWS Redshift tables with distribution style allTroubleshoot and Fix Load or Copy ErrorsCreate AWS Redshift Table with Distribution Style AutoCreate AWS Redshift Tables using Distribution Style KeyDelete AWS Redshift Cluster with a manual snapshotAWS Redshift Federated Queries and SpectrumAs part of this section, we will go through some of the advanced features of Redshift such as AWS Redshift Federated Queries and AWS Redshift Spectrum.AWS Redshift Federated Queries and Spectrum - IntroductionOverview of integrating AWS RDS and AWS Redshift for Federated QueriesCreate IAM Role for AWS Redshift ClusterSetup Postgres Database Server for AWS Redshift Federated QueriesCreate tables in Postgres Database for AWS Redshift Federated QueriesCreating Secret using Secrets Manager for Postgres DatabaseAccessing Secret Details using Python Boto3Reading Json Data to Dataframe using PandasWrite JSON Data to AWS Redshift Database Tables using PandasCreate AWS IAM Policy for Secret and associate with Redshift RoleCreate AWS Redshift Cluster using AWS IAM Role with permissions on secretCreate AWS Redshift External Schema to Postgres DatabaseUpdate AWS Redshift Cluster Network Settings for Federated QueriesPerforming ETL using AWS Redshift Federated QueriesClean up resources added for AWS Redshift Federated QueriesGrant Access on AWS Glue Data Catalog to AWS Redshift Cluster for SpectrumSetup AWS Redshift Clusters to run queries using SpectrumQuick Recap of AWS Glue Catalog Database and Tables for AWS Redshift SpectrumCreate External Schema using AWS Redshift SpectrumRun Queries using AWS Redshift SpectrumCleanup the AWS Redshift Cluster Who this course is for Beginner or Intermediate Data Engineers who want to learn AWS Analytics Services for Data Engineering Intermediate Application Engineers who want to explore Data Engineering using AWS Analytics Services Data and Analytics Engineers who want to learn Data Engineering using AWS Analytics Services Testers who want to learn key skills to test Data Engineering applications built using AWS Analytics Services Homepage https://www.udemy.com/course/data-engineering-using-aws-analytics-services/ Screenshot Rapidgator https://rg.to/file/2920699636897ec371102bdb027e8885/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part05.rar.html https://rg.to/file/2b9aa74769b487eaaedd3eec96345e51/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part04.rar.html https://rg.to/file/45d0ce3bc16db1d6999d3e6f18531e4c/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part06.rar.html https://rg.to/file/d29ebd836544f98050324f6aa8bef726/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part08.rar.html https://rg.to/file/d6f9f7479e24d0907c1621c594edb1fc/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part03.rar.html https://rg.to/file/e60b71f472370ab29b7e10f24d6cbe91/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part02.rar.html https://rg.to/file/e7a08371221bd4424901c60b4e7c8dd4/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part01.rar.html https://rg.to/file/ef32aa5500311afe27cc6fad7604a04d/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part07.rar.html Fikper Free Download https://fikper.com/1gyNST3T5B/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part02.rar.html https://fikper.com/BbGZKWTfP1/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part01.rar.html https://fikper.com/DJBmRaMzGu/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part03.rar.html https://fikper.com/SXxm2gI5gG/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part08.rar.html https://fikper.com/V3HWO9bEX3/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part05.rar.html https://fikper.com/m68l9B0z0U/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part06.rar.html https://fikper.com/yW1sDrNVjo/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part07.rar.html https://fikper.com/zvCGisvXzn/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part04.rar.html No Password - 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Free Download Data Cleaning using pandas and pyspan Published 10/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 57m | Size: 357 MB Master Data Cleaning with pandas and pyspan: Essential Techniques for Clean, Accurate, and Ready-to-Use Datasets What you'll learn Recognize opportunities for data cleaning and prepare your dataset for the cleaning process. Implement common data cleaning steps such as handle missing values and formatting date/time columns. Understand and implement complex data cleaning tasks such as outlier removal and splitting/creating new columns. Develop and apply custom data transformation techniques to standardize and enhance dataset quality. Requirements Basic understanding of Python programming. Understanding of using basic libraries like Pandas. A computer with internet access. Description Master the essential techniques of data cleaning with pandas and pyspan in Python! This beginner-friendly course will help you transform messy, raw data into clean, ready-to-use datasets for analysis. Data cleaning is a crucial first step in any data project, and in this course, you'll learn practical skills to tackle common data issues.You'll learn how to:Handle missing data effectively.Detect and remove outliers.Format and organize data for better clarity.Simplify your data cleaning process using pyspan.We'll start with a simple dataset, introducing basic data cleaning techniques step by step. By the end of the course, you'll have a solid foundation in using Python's pandas and pyspan libraries to clean and prepare data.No prior data cleaning experience is required, but basic knowledge of Python is helpful. This course is perfect for beginners, aspiring data analysts, or anyone looking to improve their data preparation skills.Throughout the course, you'll work on practical exercises that will help you apply the techniques you learn in real-world scenarios. By completing this course, you'll be ready to clean and prepare datasets for analysis with confidence. Whether you're entering the field of data analysis or just want to level up your Python skills, this course will provide the essential foundation you need. Who this course is for This course is designed for anyone working with data, including data analysts, data scientists, and aspiring professionals looking to enhance their data cleaning skills. If you frequently handle messy datasets and want to streamline your data preparation process using Python, this course will be especially valuable. It's also ideal for students and beginners with basic Python knowledge who are eager to master Pandas and Pyspan for data cleaning tasks. Whether you're in the tech industry or just starting your data journey, this course will equip you with essential skills. Homepage https://www.udemy.com/course/data-cleaning-using-pandas-and-pyspan/ Rapidgator https://rg.to/file/84ac7dedfd62d274072b5ee456247849/euoui.Data.Cleaning.using.pandas.and.pyspan.rar.html Fikper Free Download https://fikper.com/JYLAsnaPKE/euoui.Data.Cleaning.using.pandas.and.pyspan.rar.html No Password - Links are Interchangeable

Free Download Create AutoCAD LISP using Chat GPT Without Coding Knowledge Published 10/2024 Created by Abu Hamzah MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 5 Lectures ( 42m ) | Size: 438 MB Generate AutoCAD LISP using Microsoft Copilot, Chat GPT, no programming or coding knowledge..! What you'll learn Generate LISP routines using AI tools like ChatGPT and Microsoft Copilot. Customize AI-generated LISP scripts for specific AutoCAD tasks. Automate repetitive tasks in AutoCAD to improve workflow efficiency. Gain practical skills in leveraging AI for enhanced productivity in design projects. Requirements No Programming Experience: No prior coding knowledge required. AI Tools Access: Access to free or pro versions of ChatGPT and Microsoft Copilot. Basic AutoCAD Knowledge: Familiarity with AutoCAD interface and functions. AutoCAD Full Version: Must have the full version of AutoCAD (LT version not supported). Description Elevate your AutoCAD skills by learning how to create LISP routines using AI tools like ChatGPT and Microsoft Copilot, even if you have no prior coding experience. This course is specifically designed for intermediate AutoCAD users who want to streamline their workflows and automate tasks using AI, without the need for programming knowledge.**What You'll Learn:**- How to generate functional LISP code using AI tools like ChatGPT or Microsoft Copilot-no coding required.- Techniques to refine and customize AI-generated LISP routines for specific tasks in AutoCAD.- Practical ways to use AI to automate repetitive tasks, saving time and enhancing productivity.- How to experiment with and modify LISP scripts to tailor them for your project needs.**Who This Course Is For:**- **Intermediate AutoCAD Users**: Those who are comfortable with AutoCAD but don't have experience with LISP or coding will benefit from this beginner-friendly approach to automation.- **Designers, Architects, Engineers**: Ideal for professionals looking to simplify repetitive tasks in AutoCAD using AI-generated scripts.- **Anyone With No Coding Knowledge**: This course is perfect for users who want to utilize automation in AutoCAD without learning to code manually.**Why Take This Course:**- **No Programming Experience Needed**: Create LISP routines without any coding knowledge-AI does the work for you.- **Improve Efficiency**: Automate repetitive tasks in AutoCAD to speed up your workflow and focus more on design.- **Harness the Power of AI**: Learn how AI tools like ChatGPT and Microsoft Copilot can be integrated into your AutoCAD environment, giving you a cutting-edge advantage.**Required Tools & Software:**- **AutoCAD (Full Version)**: LT version doesn't support LISP routines.- **ChatGPT & Microsoft Copilot (Free or Pro Version)**: By the end of this course, you'll be able to automate a variety of tasks in AutoCAD using AI-generated LISP routines-boosting your productivity and saving time, all without needing any programming skills! Who this course is for Intermediate AutoCAD Users: For those familiar with AutoCAD seeking to automate tasks using AI-generated LISP routines. Efficiency-Seeking Professionals: Ideal for designers and engineers wanting to enhance productivity without coding skills. Non-Coders: Suitable for anyone with no programming experience who wants to leverage AI for AutoCAD automation. Homepage https://www.udemy.com/course/create-autocad-lisp-using-chat-gpt-without-coding-knowledge/ Screenshot Rapidgator https://rg.to/file/06c1a899a2a4b350dcc6eb46bb148753/rsjhq.Create.AutoCAD.LISP.using.Chat.GPT.Without.Coding.Knowledge.rar.html Fikper Free Download https://fikper.com/f4088pptcX/rsjhq.Create.AutoCAD.LISP.using.Chat.GPT.Without.Coding.Knowledge.rar.html No Password - Links are Interchangeable