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IIT-Madras Pravartak AI Silver
Module 1
Success Mindset - Very important please watch this & complete your goal card
Module 2 Introduction to Python Programming
Module 1.1 - Python Basics Refresher
Python Basics | Using Collab | Intro to Pandas and NumPy
NumPy Deep Dive | Arrays
Indexes | Data Frames | Joins
Review 1
Quiz 1.1
Bonus: Python Challenge
Module 3 Exploratory Data Analysis
Exploratory Data Analysis Lecture
Exploratory Data Analysis Assignment
Review 2
Quiz 1.2
Module 4 Make Features
Make Features Lecture
Make Features Assignment
Review 3
Module 5 Join & Reshape Data
Join & Reshape Lecture
Join & Reshape Assignment
Review 4
Module 6 Make Explanatory Visualizations
Make Explanatory Visualizations Lecture
Make Explanatory Visualizations Assignment
Review - 5
Module 7 Sprint
Sprint Introduction to Python
Programming Concepts
Module 8
Python Explanation Discussion
Module 9 Statistics
Module 2.1 - Hypothesis Testing t-tests Lecture
Hypothesis Testing t-tests Assignment
Module 10 Hypothesis Testing chi-square tests
Hypothesis Testing chi-square tests Lecture
Hypothesis Testing chi-square Assignment
Bonus Confidence Intervals
Confidence Intervals Lecture
Confidence Intervals Assignment
Bonus Bayesian Statistics
Bayesian Statistics Lecture
Bayesian Statistics Assignment
Bonus Sprint
Statistics Sprint
Bonus Statistics Intermediate
Statistics Completion Discussion
Bonus Linear Algebra
Module 3.1 - Simple Linear Regression Lecture
Simple Linear Regression Assignment
Bonus Inference for Regression
Inference for Regression Lecture
Inference for Regression Assignment
Module 3.3 Multiple Linear Regression
Multiple Linear Regression Lecture
Multiple Linear Regression Assignment
Module 3.4- Linear Algebra
Linear Algebra Lecture
Linear Algebra Assignment
Sprint 3
Linear Algebra Sprint
Linear Algebra Sprint Solution
4. Linear Models
Module 4.1 - Linear Regression
Linear Regression1 Assignment
Linear Regression 1 Quiz
Module 4.2 Linear Regression 2
Linear Regression 2 Lecture
Linear Regression2 Assignment
Module 4.3 - Ridge Regression
Ridge Regression Lecture
Ridge Regression Assignment
Module 4.4 - Logistic Regression
Logistic Regression Lecture
Logistic Regression Assignment
Sprint 4
Sprint Linear Models
Sprint Linear Models Solution
Module 5 - Kaggle Challenge
Module 5.1 Decision Trees
Decision Tree Lecture
Decision Tree Assignment
Module 5.2 - Random Forests
Random Forests Lecture
Random Forests Assignment
Module 5.3 Cross-Validation
Cross-Validation Lecture
Cross-Validation Assignment
Module 5.4 Classification Metrics
Classification Metrics Lecture
Classification Metrics Assignment
Sprint 5
Kaggle Challenge Sprint
Kaggle Challenge Solution
Sprint 6
Applied Modeling Sprint
Applied Modeling Sprint Solution
6. Applied Modelling
Module 6.1 - Define ML Problems
Define ML Problems Assignment
Module 6.2 Wrangle ML Datasets
Wrangle ML Datasets
Wrangle ML Datasets Assignment
Module 6.3 Permutation & Boosting
Permutation & Boosting Lecture
Permutation & Boosting Assignment
Module 6.4 - Model Interpretation
Model Interpretation Lecture
Model Interpretation Assignment
Module 7 AI Silver Certification
Kaggle In Class Presentation 1 (End to end capstone project)
Kaggle International Presentation 2 (End to end capstone project)
Updated Linkedin Profile
Exploratory Data Analysis
Exploratory Data Analysis 1
Exploratory Data Analysis 2
Exploratory Data Analysis 3
Supervised Learning - Regression
Regression 1
Regression 2
Regression 3
Regression 4
Classification Model Evaluation and KNN
Classification Model Evaluation and KNN 1
Classification Model Evaluation and KNN 2
Ensemble Learning and Decision trees
Decision Trees
Ensemble learning
Ensemble Learning and Naive Bayes
Unsupervised learning
Unsupervised learning - 2
Clustering and PCA
Clustering and PCA - 2
PCA -3
TensorFlow - I
TensorFlow-II
TensorFlow Classification
Deep Learning
Understanding Deep Learning - Part 1 (129:04)
Understanding Deep Learning - Part 2 (122:33)
Neural networks
Working with neural networks (120:17)
Natural Language Processing
RNNs, LSTMs (Recurrent Neural Networks & Long Short Term Memory)
Linear Regression 2 Lecture
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