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MS in Data Science

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MS in Data Science

The MS in Data Science is a comprehensive graduate program designed to equip students with advanced skills in data analysis, statistical modeling, machine learning, and data visualization. This program combines rigorous coursework with hands-on projects, allowing students to apply data-driven techniques to solve real-world problems.

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Requirements

Educational Background, Programming Skills, Mathematics and Statistics, Experience with Data Tools, GRE/GMAT Scores,

Description

Master of Science in Data Science
Overview

Go the extra mile to become a data-driven leader. Learn from a world-class curriculum developed by leading faculty & Industry experts.

Duration	18 months
Total Fee	₹5,50,000
Mode of learning	Online
Difficulty level	Beginner
Official Website	Go to Our Course
Credential	Certificate

Master of Science in Data Science

Highlights

Discover More ▶

Complimentary Python Programming Bootcamp
500+ Hours of Learning
IIIT Bangalore & LJMU Alumni Status
No Cost EMI Options Available
High Performance Coaching (1:1)

14+ Case Studies and Projects
Fortnightly Group Mentorship with Industry Mentors
Daily Doubt Resolution Support

Master of Science in Data Science
Course Details

Skills you will learn

Applied statistics, Machine learning, Data visualization techniques

More about this course

Complimentary Python Programming Bootcamp
WES recognised Masters Degree in Data Science
Fortnightly Group Mentorship Sessions with Industry Experts
IIIT Bangalore & LJMU Alumni Status
Daily Doubt Resolution and Access to Job Opportunities
Save over INR 50 lakhs, more than conventional courses
A qualification that is recognized in the US and Canada

Master of Science in Data Science
Curriculum

Course 1: Data Toolkit ▼

✓ Programming in Python
✓ Introduction to Python
✓ Python for DS
✓ Data Visualisation in Python
✓ Exploratory Data Analysis
✓ Credit EDA Assignment
✓ Inferential Stats

Course 2: Machine Learning-1 ▼

✓ Linear Regression - I
✓ Linear Regression - II + Gradient Descent for SLR
✓ Linear Regression Assignment
✓ Logistic Regression - I
✓ Classification using Decision Trees
✓ Unsupervised Learning: Clustering
✓ Basics of NLP and Lexical Processing
✓ Business Problem Solving + Intro to GIT and GITHUB
✓ Case Study: Lead Scoring

Course 3: Specialization: Data Analytics ▼

✓ Data Modelling
✓ Advanced SQL Programming
✓ Introduction to Cloud and AWS
✓ Analytics at Large Scale in Spark - I
✓ Analytics at Large Scale in Spark - II
✓ Big Data Case Study
✓ Basic Viz. using Tableau
✓ Advanced Excel
✓ Analytical Thinking and Structured Problem Solving using Frameworks
✓ Data Storytelling
✓ Airbnb Case Study
✓ Data Structures and Algorithms
✓ Searching & Sorting
✓ Algorithm Analysis and Recursion
✓ Advanced Database Programming using Pandas
✓ SQL & Python Lab
✓ Capstone

Course 4: Specialization: Business Analytics ▼

✓ Bagging & Random Forest
✓ Model Selection - I
✓ Model Selection - II
✓ Time Series Forecasting - I
✓ Time Series Forecasting - II
✓ Model Selection Case Study
✓ Basic Viz. using Tableau
✓ Advanced Excel
✓ Data Analysis and Visualisation in PowerBI
✓ Data Storytelling
✓ Airbnb Case Study
✓ Product Development using OpenAI APIs, Fine Tuning using STaR technique in Python
✓ Integrating speech using Whisper API and application deployment using Flask
✓ Interview Gynie AI: Chatbot Development Project
✓ Capstone

Course 5: Specialization: Natural Language Processing ▼

✓ Analytical Thinking and Structured Problem Solving using Frameworks
✓ Data Storytelling
✓ Airbnb Case Study
✓ Integrating speech using Whisper API and application deployment using Flask
✓ Product Development using OpenAI APIs, Fine Tuning using STaR technique in Python
✓ Interview Gynie AI: Chatbot Development Project
✓ Capstone

Course 6: Specialization: Deep Learning ▼

✓ Bagging & Random Forest
✓ Boosting
✓ Model Selection
✓ PCA
✓ Advanced Regression + Time Series Forecasting (Optional)
✓ Advanced ML case study
✓ Introduction to Neural Networks and ANN
✓ Backpropogation & Hyperparameter Tuning in Neural Networks
✓ Introduction to Convolutional Neural Networks
✓ CNN Architectures and Industry Applications + Recurrent Neural Networks (Optional)
✓ Applications of DL in CV: Object Detection Image Segmentation (Optional)
✓ Gesture Recognition Case Study
✓ Product Development using OpenAI APIs, Fine Tuning using STaR technique in Python
✓ Integrating speech using Whisper API and application deployment using Flask
✓ Interview Gynie AI: Chatbot Development Project
✓ Capstone