• Learn from the faculty of IIT Madras
• 20+ Case Studies and Projects
• 25+ Industry Mentorship Sessions
• Career Mentorship Sessions (1:1)
• India's most Advanced Cloud Programme
• Globally Accepted Advanced Certification
• High Performance Coaching (1:1)
• Just-in-Time Interviews
• Industry Readiness Assessments
• Designed for Senior Working Professionals
• Practical Hands-on Workshops
• 500+ Hours of Learning
• No Cost EMI Option
• 4 weeks Industry Capstone Project
• India's No.1 Ranked Engineering College
• Exclusive Job Opportunities Portal
• AI Powered Profile Builder
• Personalised Industry Session

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

• Prepatory Content

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

• Introduction to Machine Learning and Cloud

1. Exploratory Data Analysis and Data Visualisation
2. Intro to ML + Understanding the ML pipeline
3. Introduction to Cloud
4. Elastic Provision Services 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