Module 1

  Module 2 Introduction to Python Programming

  Module 3 Exploratory Data Analysis

  Module 4 Make Features

  Module 5 Join & Reshape Data

  Module 6 Make Explanatory Visualizations

  Module 7 Sprint

  Module 8

  Module 9 Statistics

  Module 10 Hypothesis Testing chi-square tests

  Bonus Confidence Intervals

  Bonus Bayesian Statistics

  Bonus Sprint

  Bonus Statistics Intermediate

  Bonus Linear Algebra

  Bonus Inference for Regression

  Module 3.3 Multiple Linear Regression

  Module 3.4- Linear Algebra

  Sprint 3

  4. Linear Models

  Module 4.2 Linear Regression 2

  Module 4.3 - Ridge Regression

  Module 4.4 - Logistic Regression

  Sprint 4

  Module 5 - Kaggle Challenge

  Module 5.2 - Random Forests

  Module 5.3 Cross-Validation

  Module 5.4 Classification Metrics

  Sprint 5

  Sprint 6

  6. Applied Modelling

  Module 6.2 Wrangle ML Datasets

  Module 6.3 Permutation & Boosting

  Module 6.4 - Model Interpretation

  Module 7 AI Silver Certification

  Exploratory Data Analysis

  Supervised Learning - Regression

  Classification Model Evaluation and KNN

  Ensemble Learning and Decision trees

  Deep Learning

  Neural networks