Swipe to view full content
| 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 |
Swipe to view full content
| WEEK 2 | WHAT'S IN THERE | TASK 1 | TASK 2 | TASK 3 |
|---|---|---|---|---|
| Day 1 |
Hey, excited for Week 2? Often the data we deal with can have various issues like missing values, categorical values and outliers. Today we will learn about basic techniques to deal with such issues! |
Introduction to Feature Engineering Outlier Analysis |
Handling Missing Values |
Practical Handling Missing Values |
| Day 2 |
Today’s light on tech—we'll explore ML basics, supervised vs. unsupervised learning, and how to handle categorical data. Optional math refresher included!
|
Handling Categorical Variables
Supervised and Unsupervised Learning |
All Feature Transformations
(Optional) Linear Algebra Refresher (Watch Chapters 1, 2, 3, 4, 9, 14) |
Introduction to Process Mining
REQUIRED FOR PROJECT
Complete this task from Celonis Academy & learn about Process Intelligence Fundamentals |
| Day 3 | Today we dive into the basics of ML with Linear Regression, Cost Function, and Gradient Descent—simple concepts with powerful impact! |
Linear Regression with One Variable |
Loss Function and Gradient Descent Explained |
Linear Regression Blog Loss Function Blog |
| Day 4 | Time to level up—today we tackle Linear regression with Multiple features and get hands-on with Scikit-learn, plus a sneak peek into Logistic Regression! |
Linear Regression with Multiple Variables (Videos 21 - 24) | Linear Regression with Scikit-learn | Logistic Regression Blog |
| Day 5 | Today we will be introduced to our first ever classification model, Logistic Regression. Learn it inside out! | Logistic Regression Videos 31 - 36 |
Logistic Regression with SciKit-learn |
Logistic Regression from scratch |
Coming soon!
Coming soon!
Coming soon!
| LINK | DEADLINE | INSTRUCTIONS |
|---|---|---|
| Week 1 Quiz |
June 7, 2026 11:59 PM IST |
| LINK | DATE | CONNECT WITH THE SPEAKER | |
|---|---|---|---|
| Introductory Session ft. Gunin Goel, Anuj Gupta, Tejas Vijayvargiya |
31st May, 2026 5:00PM IST | ||
| Build In Public ft. Pavan Venkatesh |
3rd June, 2026 6:00PM IST | ||
| Why EDA Matters in Real World ft. Samarth Saraswat |
7th June, 2026 3:00PM IST |
Finished today's content? Tweet what you learned. #SummerAnalytics2026 #BuildInPublic @cnaiitg
Post Now →
Copyright © Consulting & Analytics Club, IIT Guwahati