Syllabus

• Pre-Program Preparatory Content (3 Weeks)

  Introduction to Python

  Python for Data Science

  Data Visualisation in Python

  Data Analysis Using SQL

  Advanced SQL & Best Practices

  Data Analysis in Excel

  Analytics Problem Solving

  Math for Machine Learning

• Statistics and EDA (5 Weeks)

  Exploratory Data Analysis

  Cloud Essentials: Intro to Git and Github

  Inferential Statistics

  Hypothesis Testing

  Lending Club Case Study

• Machine Learning- I (7 Weeks)

  Linear Regression

  Linear Regression Assignment

  Logistic Regression

  Naive Bayes

  Module Selection

  Tools Covered: Python

• Machine Learning- II (7 Weeks)

  Advanced Regression

  Advanced Regression Assignment

  Support Vector Machine (Optional)

  Tree Models

  Model Selection - Practical Considerations

  Boosting

  Unsupervised learning: Clustering

  Unsupervised Learning: Principal Component Analysis

  Telecom Churn Case Study

  Tools Covered: Python

• Deep Learning (8 Weeks)

  Introduction to Neural Networks

  Convolutional Neural Networks -Industry Applications

  Convolutional Neural Networks - Assignment

  Recurrent Neural Networks

  Neural Networks Project - Gesture Recognition

  Tools Covered: Python, Keras, TensorFlow and OpenCV