Master of Science in Machine Learning & Artificial Intelligence

Course material for Master of Science in Machine Learning & Artificial Intelligence by UpGrad in collaboration with Indian Institute of Technology, Madras & Liverpool John Moores University.

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Learn to deploy Machine Learning models using Cloud computing with an M.Sc. Degree from Liverpool John Moores University, and an Advanced Certification from IIT Madras

Content Formatting

Content accross the course in different courses and modules are mostly .md and .ipynb formats with a few .pdf documents and .sql files for database related modules. Highly recomend to download the entire repo and view content in respective IDE or browser

PS: This respository is not meant to promote plagarism or be used as an alternative to actually taking up the course. Purpose of this repository is only to be used as a reference for the course. The content of this repository is intended to be used as an additive not a replacement for actual studying or practicing course content. Please use this as content reference only and if interested do enroll through the course. A basic honor system is expected to be maintained everyone.

Contents

• Course 1 - PreLaunch Preparatory Content
  • Module 1 - Introduction to Python Programming
    • Basics of Python
    • Data Structures in Python
    • Control Structures and Functions
    • Object-Oriented Programming in Python
  • Module 2 - Python Libraries
    • NumPy
    • Pandas
  • Module 3 - Data Visualisation in Python
    • Introduction to Data Visualization with Matplotlib
    • Introduction to Data Visualization
    • Data Visualisation with Seaborn
  • Module 4 - Math for Machine Learning
    • Introduction to Probability
    • Introduction to Linear Algebra
    • Linear Transformations and Matrices
    • Differential Calculus
  • Uber Case Study
• Course 2 - Introduction to Machine Learning and Cloud
  • Module 2 - Introduction to Machine Learning
    • Understanding Machine Learning
    • The Machine Learning Pipeline
    • The Apriori Algorithm : Theory
  • Module 3 - Exploratory Data Analysis
    • Data Sourcing
    • Data Cleaning
    • Univariate Analysis
    • Bivariate and Multivariate Analysis
  • Module 4 - Basics of RDBMS and SQL Querying
    • RDBMS and its Features
    • Basic SQL Querying
    • Advanced SQL Querying
    • Practice Workbench
  • Module 5 - Inferential Statistics and Hypothesis Testing
    • Introduction to Probability
    • Probability and Probability Distribution
    • Central Limit Theorem and Confidence Interval
    • Hypothesis Testing with a Single Population
    • Hypothesi Testing with Two Populations
    • A/B Testing Case Study
    • Applications of Sampling Methods
  • Case Study - Bank Loan Default Risk EDA
• Course 3 - Big Data and Cloud
  • Module 1 - Introduction to Cloud
    • Why Cloud?
    • Deployment and Service Models
    • Amazon Web Services
  • Module 2 - Working with AWS
    • AWS CLI
    • AWS Services
    • Applications in AWS
  • Module 3 - Hadoop Framework
    • Hadoop Distributed File System
    • MapReduce and YARN
    • EMR CLuster
• Docs
  • Amazon Web Services
  • Books
  • Cheet Sheets
  • Course Overview
  • Instalation Guides

Partner Platforms & Universities

UpGrad

Indian Institute of Technology Madras

Liverpool John Moores University