The Complete Data Analysis Course Using ChatGPT

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8:20:42

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1 - Introduction to Chat GPT

1 - What is ChatGPT and Why You Must Know About It.mp4

07:19

2 - Account Creation and Choosing Between Free and Paid Version of Chat GPT.mp4

07:40

3 - Downloading and Installing Anaconda and Running Jupyter Lab.mp4

03:38

2 - Working with Chat GPT and Jupyter Lab

4 - Learning to Import an Excel Data File in Jupyter Lab with ChatGPT Code.mp4

09:22

5 - Developing Familiarity with Jupyter Lab Note Book.mp4

05:21

3 - Prompt Engineering

6 - What is Prompt Engineering.mp4

08:17

7 - Ten Principles of Effective Prompt Engineering Part 1.mp4

13:07

8 - Understanding Temperature and Topk Parameters.mp4

03:31

9 - Understanding Pivoting.mp4

06:37

10 - Depth Safety and Evaluation Principles of Prompt Engineering.mp4

07:13

11 - Prompt Engineering Example Asking ChatGPT to Suggest Right Statistical Test.mp4

08:59

12 - Prompt Engineering Example Using ChatGPT to Find an Impactful Research Idea.mp4

17:29

13 - How to Use ChatGPT to Generate a Simulated Dataset for Factor Analsyis.mp4

16:32

14 - Using ChatGPT for Manual Calculation of Factor Loadings.mp4

11:09

15 - How to Use ChatGPT to Generate APA Style Tables.mp4

06:05

16 - Using ChatGPT to generate APA style Write Up.mp4

04:00

17 - Using ChatGPT to create a List of Major Statistical Test with Formula.mp4

05:43

4 - Data Screening and Descriptive and Analysis in Chat GPT

18 - Data Screening Using ChatGPT.mp4

01:20

19 - Missing Value Analysis Methods Naive vs Imputation Methods.mp4

05:38

20 - GPT19-Understanding-Listwise-vs.Pairwise-Deletion-Article.docx

20 - Understanding Listwise vs Pairwise Deletion.mp4

05:08

21 - Missing Value Analysis Imputation Methods.mp4

07:15

22 - Missing Value Analysis Using ChatGPT Plus.mp4

06:46

23 - GPT22-Missing-Value-Analysis-Using-ChatGPT-ChatPrompts.docx

23 - GPT22-Survival-Heart-Stroke-DEL-missing.xlsx

23 - GPT22-Survival-Heart-Stroke-missing-1.xlsx

23 - GPT22-Survival-Heart-Stroke-missing-EM.xlsx

23 - GPT22-Survival-Heart-Stroke-missing-UPDATED.xlsx

23 - Missing Value Analysis Using ChatGPT.mp4

12:00

24 - Understanding Skewness.mp4

05:10

25 - Calculating Skewness in ChatGPT Numerical and Visual Method.mp4

06:48

26 - Calculating Pearson Bowley and Kellys Coefficients of Skewness Using Chat GPT.mp4

09:02

26 - GPT25-26-Income-and-Grades-Data.xlsx

26 - GPT25-GPT25-Calculating-Pearson-Bowley-and-Kellys-Coefficients-of-Skewness-Using-ChatGPT-Plus-Prompt.docx

27 - Calculating Coefficients of Skewness in ChatGPT.mp4

08:34

27 - GPT25-26-Income-and-Grades-Data.xlsx

27 - GPT26-Calculating-Coefficients-of-Skewness-in-ChatGPT-Prompts-and-Codes.docx

28 - Understanding Normality Normal Distribution and Standard Normal Distribution.mp4

08:31

29 - Historical Origin of Normal Distribution Gauss vs Laplaces Contribution.mp4

05:09

30 - Properties of Normal Distribution.mp4

04:46

31 - Understanding KolmogorovSmirnov Test and ShapiroWilk Test.mp4

02:02

32 - GPT31-Normality-Analysis-Result-in-APA-format.docx

32 - GPT31-Perfomaity-Normality-Analysis-in-ChatGPT-Plus-and-Reporting-Result-in-APA-format-Prompt.pdf

32 - Perfomaity Normality Analysis in ChatGPT Plus and Reporting Result in APA format.mp4

10:32

33 - GPT32-Normality-Test-Using-ChatGPT-and-Jupyter-Lab-Jupyter-Lab-Codes.docx

33 - GPT32-Normality-Test-Using-ChatGPT-and-Jupyter-Lab-Prompt.pdf

33 - Normality Test Using ChatGPT and Jupyter Lab.mp4

08:06

5 - Data Analysis Plan Using ChatGPT

34 - Introduction to Data Analaysis Steps.mp4

01:28

35 - Role of Setting in Data Analysis Process.mp4

07:11

36 - Steps Involved in Research Data Analysis From Raw.mp4

14:42

37 - Understanding Differences Between Models vs Theories.mp4

08:20

6 - Descriptive Statistics Using ChatGPT

38 - Descriptive Statistics Using ChatGPT.mp4

01:38

39 - Understanidng Descriptive Statistics.mp4

04:45

40 - Types of Measures of Central Tendency.mp4

01:41

41 - Understanding Arithmetic Mean.mp4

04:42

42 - Calculation of Arithmetic Mean using ChatGPT Plus.mp4

03:31

7 - Analysis of Group Differences Using ChatGPT

43 - Introduction to Analysis of Group Differences.mp4

04:45

44 - Types of Group Difference tests.mp4

10:22

45 - Assumptions of Parametric Tests.mp4

08:40

46 - Understanding Statistical Formula of ttest.mp4

03:01

47 - Understanding Data and Formulating Hypothesis.mp4

06:00

48 - Calculation of ttest in ChatGPT Plus.mp4

12:53

48 - GPT47-Calculation-of-t-test-in-GPT-Plus.docx

49 - Calculation of ttest using Chat GPT and Python.mp4

07:24

49 - GPT48-Calculation-of-t-test-Using-ChatGPT-and-Python.docx

50 - Paired Sample ttest Introduction and Formula.mp4

03:14

51 - Understanding Data and Hypothesis Development for.mp4

01:26

52 - Paired Sample tTest in GPT Plus.mp4

06:10

53 - Paired Sample ttest using CHatGPT and Python.mp4

08:03

54 - Introduction to OneWay Anova.mp4

02:31

55 - Theory and Calculation of One Way Anova.mp4

11:36

56 - Understading Data and Developing Hypothesis.mp4

01:29

57 - Conducting ANOVA Using ChatGPT Plus.mp4

11:40

57 - GPT56-Conducting-ANOVA-using-ChatGPT-Plus.docx

58 - Conducting ANOVA using ChatGPT and Python.mp4

12:01

58 - GPT57-ANOVA-Codes-from-Jupyter-Lab.docx

58 - GPT57-ANOVA-Output-of-Chat-GPT.pdf

8 - Corrletaional Analysis Using ChatGPT

59 - A SelfIntroduction to Correlations.mp4

05:31

60 - Calculation of Correlation Coefficient Using ChatGPT.mp4

06:20

60 - GPT59-ChatGPT-Plus-Output-of-Pearson-Product-Moment-Correlation.pdf

61 - Calculating Pearson Correlation using ChatGPT and P.mp4

08:06

61 - GPT60-ChatGPT-3.5-Prompt-and-Output-for-Pearson-Correlation.pdf

61 - GPT60-Python-Code-for-calculating-Pearson-Correlation.docx

9 - Regression Analysis Using ChatGPT

62 - Introduction of Regression Analysis Using ChatGPT.mp4

07:50

63 - Types of Regression Linear Multiple Logistic.mp4

08:18

64 - Types of Regression Polynomial Ridge and Lasso Reg.mp4

07:30

65 - Types of Regression Elastic Net Quantile and Poisson.mp4

03:46

66 - Assumptions of Linear Regression.mp4

14:10

67 - Understanding Data and Formulating Hypothesis of Multiple Regression.mp4

02:51

68 - GPT67-ChatGPT-Output.docx

68 - Regression Analysis Using ChatGPT Plus.mp4

14:10

69 - GPT68-Regression-Analysis-Using-GPT-3.5-Python-Codes.docx

69 - GPT68-Regression-Analysis-Using-GPT-3.5-and-Python.pdf

69 - Regression Analysis Using GPT 35 and Python.mp4

14:08

Description

Power UP Your Data Analysis Skills with Chat GPT. Analyse Complex Datasets, Create Stunning Visualizations with Chat GPT

What You'll Learn?

Conduct AI Driven Data Analysis Using ChatGPT
Visualize Data and Identify Unique Patterns in Data Using ChatGPT
Write and Manage Python Codes for Advanced Statistical Analysis Using ChatGPT
Prepare Professional Reports and APA Style Write-Ups Using ChatGPT
Improve Research Productivity Using ChatGPT

Who is this for?

This course is intended for working professionals looking to improve their productivity for research and data analysis.

It can also be useful for anyone looking to harness the power of AI for data analysis.

What You Need to Know?

A computer or a similar device with an internet connection and a ChatGPT account

More details

Description
Course Description
Discover the power of data analysis and artificial intelligence with this unique courseÂ AI Driven Data Analysis Using Chat GPT. This course is designed to equip you with the knowledge and skills to leverage ChatGPT, one of the most advanced AI models developed by OpenAI, for in-depth data analysis. Whether you are a beginner curious about AI and data science or a seasoned professional looking to enhance your skills, this course provides a structured path from fundamental concepts to advanced applications.
Learning Outcomes
By the end of this course, you will be able to:
Understand the essentials of ChatGPT and its significance in data analysis.
Navigate through different versions of ChatGPT and select the appropriate one for your needs.
Set up and use Jupyter Lab for executing ChatGPT-powered data analysis tasks.
Master prompt engineering to optimize interactions with ChatGPT for specific outputs.
Conduct comprehensive data screenings, manage missing values, and understand different imputation methods using ChatGPT.
Perform advanced statistical analysis, including hypothesis testing, ANOVA, and regression analysis, facilitated by ChatGPT.
Generate and interpret data visualizations and statistical reports in APA format using ChatGPT.
Develop and validate data-driven hypotheses, leveraging the AI's capabilities to enhance accuracy and insights.
Pre-requisites
This course is accessible to learners with varying levels of experience. However, the following are recommended to ensure a smooth learning journey:
Basic understanding of data analysis and statistics.
Familiarity with Python programming is beneficial but not mandatory.
Access to a computer capable of running Anaconda and Jupyter Lab.
Unique Features
Hands-On Learning: Each module includes practical exercises and projects, allowing you to apply concepts in real-time using ChatGPT.
Comprehensive Coverage: From setting up your environment to advanced data analysis techniques, the course covers every aspect in detail.
Expert Support: Gain insights and feedback from industry experts specializing in AI and data science.
Flexible Learning: Access the course content at any time, and learn at your own pace with lifetime access to all resources.
Course Content Overview
Introductory Modules: Begin with an introduction to ChatGPT, its importance, and detailed guides on setting up your account and tools like Anaconda and Jupyter Lab.
Data Handling: Learn to import and manipulate data efficiently in Jupyter Lab using ChatGPT, covering a range of file types and data structures.
Prompt Engineering: Dive deep into prompt engineering, learning to craft prompts that guide ChatGPT to produce optimal outputs for various data analysis tasks.
Statistical Analysis: Engage with modules on statistical tests, understanding and applying different methods such as t-tests, ANOVA, and various forms of regression analysis using both theoretical knowledge and ChatGPT's computational power.
Advanced Data Management: Tackle complex scenarios in data management, including missing value analysis and understanding data distribution properties.
Final Projects: Apply everything you've learned in comprehensive projects that challenge you to use ChatGPT for real-world data analysis scenarios.
This course not only enhances your analytical skills but also prepares you to be at the forefront of AI-assisted data science, making you a valuable asset in any data-driven industry. Join us to transform data into insights and AI understanding into practical expertise.
Who this course is for:
This course is intended for working professionals looking to improve their productivity for research and data analysis.
It can also be useful for anyone looking to harness the power of AI for data analysis.

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