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. Master in Data Science (MDS)

Overview

MDS (TU) is a postgraduate program focused on data analysis, big data management, machine learning, and AI applications. It trains students to extract insights from complex data, build predictive models, and support data-driven decision-making. The program is research and industry-oriented, preparing graduates for roles in analytics, IT, and research.

  • Course Info

    Affilation Tribhuwan University (TU)
    Duration 2 Years
    Institute Type College
    Average Fees Incurred Around NPR 2 – 4 Lakhs
    Average Salary Offered Starting: NPR 50,000 – 1,00,000 per month
    Employment Roles
    • Data Scientist
    • Data Analyst
    • Machine Learning Engineer
    • AI Specialist
    • Business Intelligence Analyst
    • Data Engineer
    • Researcher in Analytics

  • Admission Criteria

    • Bachelor’s degree in IT, CS, Statistics, Mathematics, Engineering, or related field
    • Minimum 2nd division or CGPA 2.0
    • Must pass TU entrance exam
    • Selection based on merit list from entrance exam

  • Salient Features

    • Focus on data science, AI, and machine learning
    • Project-based and practical learning
    • Includes thesis / research work
    • Elective options for specialization
    • Prepares for industry roles and research careers

  • Eligibility

    • Recognized Bachelor’s degree in IT, CS, Computer Engineering, Statistics, Mathematics, or related fields
    • Must qualify the entrance exam

  • Job Prospectus

    • Data Scientist
    • Data Analyst
    • Machine Learning Engineer
    • AI Specialist
    • Business Intelligence Analyst
    • Data Engineer
    • Researcher in Analytics
    • IT Consultant in data-driven projects

    These roles are in IT companies, banks, telecom, research organizations, government agencies, and multinational corporations.

  • Curricular Structure

    Core Subjects:

    • Data Analytics & Visualization
    • Big Data Technologies
    • Machine Learning & AI
    • Database Management & SQL
    • Statistical Methods for Data Science
    • Python / R Programming
    • Cloud Computing & Data Security

    Elective Subjects (Examples):

    • Deep Learning
    • Natural Language Processing (NLP)
    • Business Intelligence
    • IoT Analytics

    Other Components:

    • Practical labs and assignments
    • Seminars and case studies
    • Final Thesis / Research Project

    Evaluation:

    • Internal assessment + Final exams
    • Thesis evaluated separately

Interested in this course?

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