• Complimentary Python Programming Bootcamp
• Only online M.Sc in DS for working professionals
• 60+ Case Studies and Projects
• Timely Doubt Resolution
• IIIT Bangalore & LJMU Alumni Status
• No Cost EMI Option
• Career mentorship Sessions(1:1)
• Just-in-Time Interviews
• Personalised Industry Session
• Industry Readiness Assessments
• Career Essential Soft Skills Program
• 500+ Hours of Learning
• Fortnightly Group Mentorship with Industry Mentors
• Support available 7 days, 24x7
• Global access to job opportunities
• NASSCOM certificate
• AI Powered Profile Builder
• High Performance Coaching(1:1)
• Career Bootcamp

Top Skills You Will Learn

Statistics, Predictive Analytics using Python, Machine Learning, Data Visualization, Big Data Analytics, etc.

Job Opportunity

Data Analyst, Data Scientist, Product Analyst, Machine Learning Engineer, Business Analyst

Minimum Eligibility

Bachelor’s Degree with minimum 50% or equivalent passing marks. No coding experience required.

Who Is This Programme For?

Any specialization can be chosen regardless of background. The program caters to: Engineers, Marketing & Sales Professionals, Freshers, Data Professionals, Domain Experts, Software & IT Professionals

Syllabus covered

Pre-Program Preparatory Content

1. Data Analysis in Excel
2. Analytics Problem Solving

Data Toolkit

1. Introduction to Python
2. Programming in Python
3. Python for Data Science
4. Data Visualization in Python
5. Exploratory Data Analysis
6. Credit EDA Case Study
7. Inferential Statistics
8. Hypothesis Testing
9. Data Analysis using SQL
10. Advanced SQL & Best Practices
11. SQL Assignment: RSVP Movies

Machine Learning

1. Linear Regression
2. Linear Regression Assignment
3. Logistic Regression
4. Unsupervised Learning: Clustering
5. Business Problem Solving
6. Clustering Assignment (Optional)
7. Case Study: Lead Scoring

Specialisation- Deep Learning

1. Tree Models
2. Model Selection & General ML Techniques
3. Bagging and Boosting
4. Advanced Regression
5. Advanced Regression Assignment
6. Principal Component Analysis
7. Time Series Analysis
8. Telecom Churn Case Study
9. Introduction to Neural Networks
10. Convolutional Neural Networks - Introduction and Industry Applications
11. CNN Assignment
12. Recurrent Neural Networks
13. Gesture Recognition
14. Capstone Project

Specialisation- Natural Language Processing

1. Tree Models
2. Model Selection & General ML Techniques
3. Principal Component Analysis
4. Advanced Regression
5. Advanced Regression Assignment
6. Bagging and Boosting
7. Time Series Analysis
8. Telecom Churn Case Study
9. Lexical Processing
10. Syntactic Processing
11. Syntactic Processing -Assignment
12. Neural Nets for NLP
13. Semantic Processing
14. Case Study: Automatic Ticket Classification
15. Capstone Project

Specialisation- Business Analytics

1. Tree Models
2. Time Series Forecasting
3. Retail-Giant Sales Forecasting Assignment
4. Model Selection & General ML Techniques
5. Advanced Excel
6. Visualisation using Tableau
7. Telecom Churn Case Study
8. Structured Problem Solving using Frameworks
9. Structured Problem Solving Assignment
10. Operations Research
11. Data Storytelling
12. Business Case Study
13. Capstone Project

Specialisation- Business Intelligence/Data Analytics

1. Data Modelling
2. Advanced SQL and Best Practices
3. SQL Weeklong Lab
4. Advanced Excel
5. NoSQL Databases and MongoDB
6. Introduction to Big Data and Cloud
7. Hive and Querying
8. Hive Case Study
9. Visualisation using Tableau
10. Sports Analytics - IPL Visualisation Assignment
11. Visualisation using PowerBI
12. Visualisation using Plotly
13. Data Storytelling
14. Business Case Study
15. Capstone Project

Specialisation- Data Engineering

1. Introduction to Big Data (Optional)
2. Introduction to Cloud and AWS Setup
3. Introduction to Hadoop and MapReduce Programming
4. Assignment (optional)
5. Data Management and Relational Database Modelling
6. NoSQL Databases and Apache HBase and NoSQL Databases and MongoDB(Optional)
7. Data Warehousing (Optional)
8. Data Ingestion with Apache Sqoop and Apache Flume
9. Hive & Querying
10. Assignment (optional)
11. Amazon Redshift
12. Introduction to Apache Spark
13. Project: ETL Data Pipeline
14. AWS Cloud Infrastructure (Optional)
15. Optimising Spark for Large Scale Data Processing
16. Apache Flink (Optional)
17. Real-Time Data Streaming with Apache Kafka
18. Real-Time Data Processing using Spark Streaming
19. Assignment (Optional)
20. Building Automated Data Pipelines with Airflow
21. Analytics using PySpark
22. Project: Real Time data processing
23. Capstone Project

Specialisation- Data Science Generalist

1. Tree Models
2. Boosting (optional)
3. Model Selection & General ML Techniques
4. Telecom Churn Case Study (optional)
5. Principal Component Analysis
6. ML Lab 1: Classification
7. Advanced Regression + ML Lab 2: Regression
8. Text Analytics & Processing + Text-Based Predictive Modelling
9. Visualisation using Tableau
10. Data Storytelling
11. Business Case Study
12. Data Modelling
13. Advanced SQL - Week II
14. SQL Weeklong Lab
15. Data Structures - Sets, Dictionaries, Stacks, Queues
16. Algorithm Analysis + Recursion
17. Searching and Sorting
18. Python Weeklong Lab-I
19. Python Weeklong Lab-II
20. Capstone Project

Research Methodologies

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

Dissertation

1. Investigate dietary patterns and metabolite fingerprints of takeaway (fast) food consumers using PCA and clustering methods
2. Investigate a diagnosis of eye diseases using imaging ophthalmic data
3. Structure medical images with information geometry
4. Using social media feed to place tweets regarding natural disasters on a map
5. Preventing credit card fraud through pattern recognition
6. Developing a recommender system for a Media giant
7. Risk modelling for Financial activities and Investment Banking