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| WEEK 1 | WHAT'S IN THERE | TASK 1 | TASK 2 | TASK 3 |
|---|---|---|---|---|
| Day 0 | Getting Started with Setting Up Your Data Science Environment using Anaconda, Jupyter Notebooks, Google Colab, and Kaggle. | Jupyter Notebook Complete Beginner Guide | Windows / Mac / Linux | |
| Day 1 | Basics of Python and understanding ML. | Beginner Tutorial (up to 30 mins) | Moving Ahead (30 min – 1:30 hr) | What is ML? |
| Day 2 | Basics of Python continued & NumPy overview. | Python continued (1:30 hr to end) | Numpy Video | Numpy Notebook |
| Day 3 | Gaining an overview of Pandas. | Pandas Overview | Kaggle Micro-course | Pandas Notebook |
| Day 4 | Matplotlib and common ML problems. | Intro to Matplotlib | Matplotlib Notebook | Common ML Problems |
| Day 5 | Seaborn and Descriptive Statistics. | Seaborn Overview | Data Types in Stats | Central Tendencies & Normal Distribution |
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