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    Applications Open for 2026

    MBA/MTECH Analytics

    Interdisciplinary analytics program blending management and technical expertise

    2 Years | 4 Semesters
    MBA–M.Tech. Integrated
    School Of Business

    Program Overview

    The MBA–M.Tech. in Analytics integrates engineering, analytics, and management education to develop professionals capable of leading data-driven strategy, intelligent systems, and technology-enabled decision-making across modern organizations.

    Students gain expertise in data analytics, machine learning, programming, analytical modeling, and business strategy, enabling them to translate complex data insights into effective managerial and technological decisions.

    At a Glance

    Duration

    2 Years

    Semesters

    4 Semesters

    Scholarship

    Available

    Eligibility

    Qualification

    Bachelor’s degree

    Branch Required

    Any discipline

    Minimum Score

    50% aggregate

    Entrance Exams

    PU PULSECATMATXATCMATGMAT

    Program Highlights

    Dual-degree Integration

    Combined engineering and management curriculum for technical and strategic depth.

    Hands-on Labs

    Industry datasets, cloud platforms, and coding practica for real-world experience.

    Capstone Projects

    Solve live business problems with mentoring from industry partners.

    Research & Innovation

    Access to faculty-led research, patents, and startup incubation support.

    Syllabus

    Progressive curriculum from mathematical and programming foundations to advanced machine learning, big-data engineering, AI systems, strategic analytics, and a project-driven capstone integrating technical and managerial learning.

    Year 1Foundation
    SEM 1 & 2
    Computer Programming ParadigmsBusiness Communication and Intellectual PropertyPython for AnalyticsProbability/StatisticsBig Data SystemsComputing for Data AnalyticsData and Visual AnalyticsMachine Learning and Data Analytics
    Year 2Capstone
    SEM 3 & 4
    Introduction to Business for AnalyticsSocial Media AnalyticsIntroduction to Financial EngineeringSupply Chain and Logistic ManagementDissertationShare Market Trading System

    Major Specialization Tracks

    Students may select a specialization to develop deep expertise. Elective subjects will be based on the chosen track.

    Machine Learning

    Advanced supervised, unsupervised, and deep learning applications.

    Big Data Engineering

    Distributed systems, data pipelines, and cloud-native analytics infrastructure.

    Business Analytics

    Prescriptive and descriptive analytics focused on managerial decision-making.

    AI in Finance

    Quantitative models, risk analytics, and fintech applications.

    Marketing Analytics

    Customer analytics, attribution modeling, and growth experimentation.

    Program Outcomes

    • Design end-to-end machine learning solutions for business problems.
    • Develop scalable data pipelines and deploy analytics applications.
    • Analyze complex datasets to generate actionable business insights.
    • Evaluate AI strategies and align them with organizational goals.

    Career Pathways

    Graduates are equipped to work with top-tier tech companies and startups in a wide range of roles.

    Data Scientist
    Machine Learning Engineer
    Data Engineer
    Analytics Manager
    Business Analyst
    AI Consultant
    Quantitative Analyst
    Product Analyst
    Chief Data Officer

    Frequently Asked Questions

    Who should apply for this program?
    Graduates with STEM, commerce, or management backgrounds seeking analytics and AI leadership.
    Do I need programming experience?
    Prior coding helps; we teach Python, R, SQL, and cloud tool workflows.
    How are industry projects structured?
    Team-based, client-linked projects with faculty and industry mentorship across two semesters.
    Which tools and platforms will I learn?
    Python, R, SQL, TensorFlow, PyTorch, Spark, Hadoop, and major cloud services.
    What careers follow graduation?
    Roles in data science, ML engineering, analytics leadership, product analytics, and fintech.
    MBA/MTECH Analytics