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Module 0: Getting Started
Python and Libraries Setup
Module 1: Introduction to Python and Statistics
Introduction to Python Programming
Intermediate Python Concepts
Python Packages For Data Science Numpy & Matplotlib
Stats for Machine Learning
Exploratory Data Analysis - 1
Exploratory Data Analysis - 2
Inferential Statistics
Module 2: Data Extraction and Cleaning
Introduction to SQL
SQL For Data Science - Part 2
Web Scraping with Python
Web Scraping with Python - Part 2
Working with APIs
Text Data Cleaning
Module 2 Revision and Test
Module 3: Supervised Machine Learning
Introduction to Machine Learning
Naive Bayes Classifier
Content Based Recommendation Systems
Recommendation Systems - Collaborative Filtering
Gradient Descent For Machine Learning
Logistic Regression
Module 4: Intermediate ML Concepts
SVM - Introduction
Digit Recognition with SVM
Ensemble Methods, Bagging & Boosting
Neural Networks
Introduction to Neural Networks
Neural Networks - Part 2
Introduction to TensorFlow
Convolution Neural Networks (CNN)
Image Classification with CNN
Unsupervised Learning
Introduction to Unsupervised Learning using K-means
Principal Component Analysis (PCA)
Face Recognition using PCA
Reinforcement Learning
Inroduction to Reinforcement Learning
Reinforcement Learning with OpenAI Gym
Building a Crawling Robot with Q-Learning
Capstone Project
Part 1 - Research
Reinforcement Learning > Inroduction to Reinforcement Learning
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