Program Overview
The M.Tech. Analytics provides a comprehensive academic foundation with industry-relevant curriculum, practical learning, and career-focused education designed for professional success.
The M.Tech in Analytics integrates advanced engineering analytics with management principles. It prepares graduates to analyze complex data, build intelligent models, and align analytical insights with organizational strategy across technology-driven business environments.
Students develop competencies in statistical analysis, machine learning, big data processing, analytical programming, data visualization, and managerial decision frameworks for translating technical insights into strategic business actions.
Admission At A Glance
Duration
2 Years
Semesters
4 Semesters
Scholarship
Available
Program Fees
₹75,000 Per Year
Eligibility
Qualification
B.E. / B.Tech
Branch Required
Minimum Score
50% aggregate
Entrance Exams
Program Highlights
The M.Tech. Analytics offers industry exposure, modern infrastructure, expert faculty, internships, skill development, and holistic campus learning experiences.
Interdisciplinary Curriculum
Blends analytics engineering with management decision sciences
Applied Learning
Emphasis on projects, case studies, and real datasets
Research Exposure
Opportunities in funded analytics and AI research
Industry Collaboration
Engagement with startups and technology-driven enterprises
Major Specialization Tracks
The M.Tech. Analytics offers specialized career tracks in high-demand domains, helping students build expertise, innovation skills, and professional competence. Students may select a M Tech Analytics specialization to develop deep expertise. Elective subjects will be based on the chosen track of M Tech Analytics course.
Data Science
Advanced statistical modeling and data-driven insight generation
Business Analytics
Analytical methods for strategic and operational decision making
Artificial Intelligence
Intelligent systems for predictive and cognitive applications
Big Data Systems
Scalable architectures for large-scale data processing
Syllabus
The M.Tech. Analytics syllabus integrates core fundamentals, emerging technologies, interdisciplinary subjects, and practical training aligned with current industry trends.The M Tech Analytics syllabus is designed to build essential knowledge, practical skills, and leadership qualities for success in today’s evolving professional world
The curriculum progresses from analytical foundations and programming to advanced machine learning, big data systems, predictive modeling, and strategic management applications, supported by research projects and practical industry-oriented problem solving.
Program Outcomes
The M.Tech. Analytics helps students achieve strong technical knowledge, critical thinking, professional skills, research aptitude, and global career readiness.
- Design analytical models supporting strategic and operational decisions
- Develop machine learning solutions for complex, real-world datasets
- Analyze business problems using quantitative and computational methods
- Implement data-driven strategies aligned with organizational objectives
Career Opportunities
The M.Tech. Analytics prepares graduates for diverse career opportunities, top industry roles, entrepreneurship, higher education, and global employment prospects.
To apply for the M.Tech. Analytics programme at Pillai University, one of the top private universities in Mumbai, candidates must meet the following criteria:
Required Documents:
- S.S.C. and H.S.C. marksheets & passing certificates
- Transfer/Leaving Certificate
- Caste Certificate (if applicable)
- Non-Creamy Layer Certificate (for DT/VJ, NT, OBC, SBC categories)
- Migration Certificate (if applicable)
- Domicile Certificate
- Aadhar Card copy
- Income Certificate (if applicable)
- Anti-Ragging Affidavit (signed and submitted online)
Highlights:
Pillai University, recognised among the best universities in Mumbai and a top university in Navi Mumbai, offers industry-aligned, career-oriented programmes with global exposure, experiential learning, and research-driven education.