OUTLINE:

I. DATA SCIENCE PROJECTS:
1. Explorative Data Analysis
2. Regression
3. Classification
4. Clustering
5. Dimensionality Reduction
6. Ensemble Learning
7. Time Series Analysis
8. Natural Language Processing
9. Computer Vision
10. Generative Adversarial Networks (GANs)
11. Explainable AI
12. Automate Machine Learning (AutoML)
13. Recommender System
14. A/B Testing

II. PYTHON PROGRAMMING:

1. Data Science Python Libraries and Packages:
i. Web Scraping and Data Extraction
ii. Data Exploration and Analysis
iii. Scientific Computing
iv. Pandas Data Analysis
v. NumPy
vi. Data Visualization
vii. Machine Learning
viii. Deep Learning
ix. Big Data
x. Natural Language Processing (NLP)
xi. Image Processing
xii. Generative AI
xiii. Explainable AI (XAI)
xiv. Automated Machine Learning (AutoML)
xiv. Model Deployment

2. Python for Data Science:
i. Data Cleaning & Manipulation
ii. Machine Learning & Deep Learning
iii. Text Handling & Processing

3. Python General:
i. Basics
ii. Data Manipulation & Handling
iii. Looping & Iterations
iv. Error Handling & Testing
v. Functions & Techniques

III. R PROGRAMMING:
1. Data Science R Libraries and Packages:
i. Data Manipulation and Analysis
ii. Data Visualization
iii…