Introduction
CRISP-DM and Case Study 1
Data Pre-processing
Exploratory Data Analysis
Basics of Machine Learning
Nearest Neighbour Algorithm
Decision Tree
Logistic Regression
Model Selection and Hyperparameter Tuning
Model Evaluation and Pipeline
Review of Term 1
Case study: IPO
Ensemble Learning 1
Ensemble learning 2
Feature Selection
Clustering methods
Clustering Evaluation
Case Study: Customer segmentation
Simple Linear Regression
Artificial Neural Networks 1
Artificial Neural Networks 2
Introduction to Keras and Deep Learning
Deep Feedforward Networks (MLP)
Convolutional neural networks
Using Pre-trained Convnet
Review of Term 2