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M.Sc. Data Analytics

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M.Sc. Data Analytics (Online) offers an advanced and industry-aligned curriculum covering statistics, programming, machine learning, big data, cloud computing, and analytics techniques. Students gain hands-on experience through Python, R, SQL, NLP, Hadoop, AI/ML, and research projects. The program trains learners to collect, process, analyze, and interpret complex datasets, enabling data-driven decision-making across business, technology, healthcare, and emerging domains.
M.Sc. Data Analytics (Online) offers an advanced and industry-aligned curriculum covering statistics, programming, machine learning, big data, cloud computing, and analytics techniques. Students gain hands-on experience through Python, R, SQL, NLP, Hadoop, AI/ML, and research projects. The program trains learners to collect, process, analyze, and interpret complex datasets, enabling data-driven decision-making across business, technology, healthcare, and emerging domains.

Program Duration

M.Sc. Data Analytics is a 2 years program with 4 semesters.

Eligibility

Bachelor’s degree in Computer Science, Maths, Statistics, Engineering, or any relevant discipline.

Program Curriculum

Click here

Specialization Electives 

Electives

  • Ensemble Learning for Predictive Analytics
  • Time Series Analytics and Forecasting
  • Computer Vision and  Image Analytics
  • Generative AI and Deep Learning Models
  • Clinical Decision Support and Healthcare Analytics
  • Text Analytics
  • Reinforcement Learning for Artificial Intelligence
  • Fundamentals of Cryptography and Network Security
  • Internet of Things and Arduino Programming
  • Artificial Neural Networks and Deep Learning
Skill Enhancement Courses

Skill Enhancement Courses

  • Advanced Excel for Data Analytics
  • Tableau for Data Analysis
  • Unix Shell Programming
  • Agile Methodologies for Project Management
  • SQL Advanced Concepts and Applications
  • Statistical Analysis usingJamovi
  • Web Scraping with Python
  • PySpark for Big Data and Analytics
  • Microsoft Azure in AI
  • Business Intelligence and Visualization with PowerBI

What makes studying M.Sc. Data Analytics online a valuable option?

Studying M.Sc. Data Analytics online is valuable because it offers industry-relevant, flexible learning with the same academic depth as a traditional program. The curriculum covers statistics, programming, AI/ML, NLP, big data, cloud computing, and hands-on labs in Python, R, and Hadoop. With electives like forecasting and deep learning plus a full research project, learners gain practical, end-to-end analytics skills while balancing work and study.

Standout Features

  • Under the Entitled Category of UGC
  • Dual Degree Opportunity 
  • Career-focused 
  • Flexibility & Convenient
  • Affordable & Accessible Education
  • Globally Recognized Qualification

Program Perks

Industry-Aligned Curriculum: The M.Sc. Data Analytics online program offers an advanced, industry-focused curriculum covering statistics, machine learning, big data, cloud computing, AI, NLP, and predictive analytics. Designed around real-world applications, it equips learners with the technical and analytical expertise required for high-impact roles in data-driven industries.
Higher Earning Potential: With strong skills in advanced analytics, AI/ML, big data engineering, and business intelligence, graduates are in high demand across IT, finance, healthcare, consulting, e-commerce, and research sectors. The growing reliance on data-driven strategies enables enhanced salary prospects and promising career progression.
Expert Faculty Mentorship: The program is led by experienced faculty and industry practitioners who bring a blend of academic excellence and practical insights. Students receive personalized mentoring, exposure to industry tools, and guidance in mastering complex analytics techniques relevant to modern workplaces.
Professional Growth & Specialisation: M.Sc. Data Analytics provides advanced proficiency in statistical modeling, AI, machine learning, cloud analytics, and Hadoop ecosystems. With hands-on labs, electives in areas like time-series forecasting, deep learning, and healthcare analytics, and a major research project, learners graduate ready to drive data-informed decisions across diverse industries.

Career Prospects

Senior Data Analyst / Lead Data Analyst

Senior Data Analyst / Lead Data Analyst

Leads analytics projects, builds advanced models, manages dashboards, and presents insights to leadership teams to support strategic decision-making and business planning.

Decision Scientist / Decision Analytics Specialist

Decision Scientist / Decision Analytics Specialist

Applies behavioural and predictive analytics to optimize pricing, promotions, and customer retention. Helps e-commerce, fintech, and service companies make high-impact business decisions.

Big Data Engineer / Hadoop Engineer

Big Data Engineer / Hadoop Engineer

Designs and manages large-scale data systems using Hadoop, Spark, Kafka, Hive, and cloud platforms. Supports real-time analytics for banking, telecom, e-commerce, and AI-driven firms.

Quantitative Analyst

Quantitative Analyst (Quant)

Uses mathematical and statistical models to analyze financial markets, assess risk, and support trading strategies. A highly specialized role in finance and investment companies.

Advanced Data Scientist

Advanced Data Scientist

Builds and deploys complex ML models, works with NLP and deep learning, and performs A/B testing. Drives innovation across tech, healthcare, finance, and supply-chain industries.

Analytics / BI Consultant

Analytics / BI Consultant

Works with organizations to solve data challenges, design analytics systems, and create data strategies. Translates insights into clear, actionable business outcomes.

Cloud Data Architect

Cloud Data Architect (Associate Level)

Designs secure and scalable cloud-based data pipelines on AWS, Azure, or Google Cloud. Supports enterprise cloud migration, governance, and optimization.

Marketing / Customer Analytics Manager

Marketing / Customer Analytics Manager

Analyzes customer behaviour, campaign performance, and buying patterns. Helps companies improve targeting, engagement, and retention in fast-growing digital markets.

Healthcare Analytics Specialist

Healthcare Analytics Specialist

Analyzes medical and hospital data to build dashboards, track outcomes, and predict health trends. Supports hospitals, pharma companies, and research institutes in improving patient care.

Data Governance & Compliance Manager

Data Governance & Compliance Manager

Creates data policies, ensures regulatory compliance, and maintains data quality. Essential for banks, insurance, telecom, and enterprises handling sensitive information.

AI Analytics Integrator

AI Analytics Integrator

Implements machine learning models into real business workflows. Works with MLOps teams to enable AI-driven automation and ensure smooth deployment and monitoring.

Research Associate / PhD Pathway

Research Associate / PhD Pathway

Supports academic and industry research, writes publications, and contributes to AI and data science innovations. Ideal for students aiming for a PhD or research-focused career.

Support Offered During the Program 

  • Online Orientation Program 
  • Weekly Lesson Plan
  • Interactive Self-Learning Materials
  • Online Review Sessions
  • Predefined Academic Calendar
  • Intuitive LMS Platform
  • Faculty Mentorship

Tools You Will Master

Hands-on with industry tools and frameworks used across AI, Machine Learning, Data Analytics, and Web Development.

SQL
r
Power BI
tableau
tensorflow
microsoft azure
aws
jamovi
flutter

FAQs

What is M.Sc. Data Analytics?

M.Sc. Data Analytics is a postgraduate program that focuses on advanced data science techniques, statistical modelling, machine learning, big data processing, and cloud-based analytics. It trains learners to convert raw data into meaningful insights. The curriculum is designed to build both theoretical knowledge and strong hands-on analytical skills.

Students gain expertise in Python, R, SQL, Hadoop, NLP, AI/ML, cloud computing, and advanced statistical analysis. They build strong problem-solving, data interpretation, visualization, and modelling skills. The program also includes real datasets, labs, and a research project to strengthen applied analytics experience.

Graduates can take up roles such as Data Analyst, Machine Learning Engineer, Data Scientist, Big Data Engineer, BI Analyst, NLP Engineer, and Cloud Data Engineer. The degree prepares learners for both technical and research-oriented careers. With advanced skills, they can progress into leadership roles in analytics and AI.

Yes. The curriculum includes Research Methodology and a full-fledged Research Project, enabling graduates to pursue PhD programs or research careers. The strong foundation in analytics, AI, and statistical modelling helps learners transition smoothly into academic and research domains.

Graduates are employed across IT, finance, healthcare, e-commerce, telecom, consulting, manufacturing, and research sectors. Industries increasingly rely on analytics for optimization, prediction, automation, and strategic planning, creating strong demand for skilled professionals.

The program includes R, Python, SQL, Tableau, Power BI, Hadoop, Spark, cloud platforms, and machine learning frameworks. Learners also explore NLP, deep learning, big data ecosystems, advanced statistics, and domain-specific analytics tools.

Absolutely. With strong analytical, modelling, and problem-solving capabilities, graduates are well-suited for data consulting, business strategy, and decision-science roles. Their ability to derive insights and build predictive solutions adds significant value to consulting and advisory environments.