1. Introduction to ChatGPT
2. ChatGPT for Data Science and Machine Learning
3. Fundamentals of Statistics for Data Science
4. Missing Values and Outliers
5. Relation Between Variables and Charts
6. Data Preparation
7. Training and Evaluation
8. Fine Tuning, Features Selection, and Final Model
9. Data Preparation and Training
10. Fine Tuning and Final Model
11. Data Analysis and Dataset Manipulation (NLP)
12. Sentiment Analysis and Predictions
13. ChatGPT-4 for a Completely Automated Data Science Workload
14. Customizing GPT for Applications
15. Takeaways and Conclusions
      Index