• Learn from the faculty of IIT Madras & LJMU
• 650+ Hours of Learning
• Globally accepted M.Sc. Degree
• Practical Hands-on Workshops
• No Cost EMI Option
• Offline peer-to-peer networking (non-COVID time)
• Personalised Industry Session
• Just-in-Time Interviews
• AI Powered Profile Builder
• Career Bootcamp
• 25+ Case Studies and Assignments
• India's Most Advanced Cloud Program
• Designed for Working Professionals
• India's No.1 Ranked Engineering College
• 4 Weeks Industry Capstone Project
• Career Mentorship Sessions (1:1)
• High Performance Coaching (1:1)
• Industry Readiness Assessments
• Exclusive Job opportunities Portal

Top Skills You Will Learn

Python, BD processing using Spark, Deploy ML Models, Supervised & Unsupervised ML Models, Predictive Analytics & Statistics

Who Is This Programme For?

Engineers, Software and IT Professionals, Data Professionals

Minimum Eligibility

Bachelor’s Degree with 50% or equivalent at graduation. Coding experience required.* (B. Tech or B.E- preferably 60% or higher or first class if you have less than two years of experience)

Job Opportunities

Big Data Analyst, Data Engineer, Data Scientist, Machine Learning Engineer

Syllabus covered

Preparatory Content

1. Python Programming
2. Python for Data Science
3. Data Visualisation in Python
4. Python Assignment (Optional)

Introduction to Machine Learning in Cloud

1. Exploratory Data Analysis and Data Visualization
2. Intro to ML + Understanding the ML pipeline
3. Introduction to Cloud
4. Elastic Provisions of cloud and setting up cloud
5. Assignment

Data Warehousing & Data Management

1. Introduction to HDFS
2. Introduction to SQL
3. Hive Querying
4. Case Study
5. Assignment

Big Data Processing using Spark

1. Introduction to Spark
2. PySpark Programming
3. PySpark implementation on a Dataset: ALS & Spark Streaming
4. Assignment

Machine Learning - I

1. Inferential Statistics and Hypothesis Testing
2. Linear Regression - I
3. Linear Regression - II
4. Logistic Regression
5. Assignment

Machine Learning - II

1. Decision Trees
2. Random Forest Trees
3. Assignment
4. Principal Component Analysis + Linear Algebra
5. Clustering

Deep Learning

1. Introduction to Neural Nets with TensorFlow
2. Convolution Neural Networks
3. Melanoma Detection Assignment
4. Recurrent Neural Networks

NLP with Deep Learning

1. Natural Language Processing Fundamentals
2. Case Study on applications of Deep Learning in NLP
3. Case Study on Computer Vision
4. NN Assignment: Gesture Recognition

Deployment

1. Deployment
2. Implementation: Regression + Model Selection on SageMaker

Capstone

1. Capstone Project

Research Methodology

1. Introduction to Research and Research Process
2. Research Design
3. Literature Reviewing
4. Research Project Management
5. Report Writing and Presentation Skills
6. Scientific Ethics

Master's Dissertation

1. Master's Thesis