MSc Mathematics with Data Science

Specialise in mathematics, statistics, and data analytics, with a focus on industry and research applications.

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Programme Overview

The MSc in Mathematics with Data Science programme offers advanced studies in mathematics, statistics, and data analytics, with a strong focus on industry applications and research. The course covers a wide range of topics, including machine learning, data mining, statistical modelling, and computational mathematics, ensuring that students are equipped to handle complex data-driven problems. Graduates of this programme are highly sought after in sectors such as finance, healthcare, tech, and research, where data-driven decision-making and analytical expertise are in high demand.

Doctorate Programme

PhD in Mathematics

The Ph.D. programme offered by the Department of Mathematics, School of Sciences at IILM University Greater Noida is designed to promote advanced research, innovation, and academic excellence in both pure and applied mathematics. The department is supported by a team of highly qualified and specialized faculty members with expertise in diverse areas such as Supply Chain Management, General Topology, Time Series and Forecasting Analysis, Special Functions, Fluid Dynamics, Reliability Engineering, and Differential Geometry, etc.. The program emphasizes rigorous theoretical foundations along with interdisciplinary applications, enabling scholars to address complex real-world problems through analytical and computational approaches. With a strong focus on research methodology, critical thinking, and modern mathematical tools, the Ph.D. (Mathematics) program aims to develop competent researchers, academicians, and industry professionals who can contribute significantly to scientific advancement and societal development.

Frequently Asked Questions

The MSc Mathematics with Data Science is a two-year postgraduate program (4 semesters) that combines advanced mathematics, statistics, and computational techniques for data analysis and machine learning.

Graduates can work as Data Scientists, Machine Learning Engineers, Quantitative Analysts, Business Analysts, and Statistical Modelers in tech companies, financial firms, healthcare, and research organizations.

Yes, many universities offer internships, industry collaborations, and placement support in IT companies, finance, healthcare analytics, and AI-driven industries.

Graduates are in demand in technology, finance, healthcare, research, and consulting. Top employers include AI firms, banks, analytics firms, government research organizations, and global MNCs.

Program Specific Outcomes (PSOs)

PSO1:

Apply advanced concepts of pure and applied mathematics to analyze theoretical and practical problems.

PSO2:

Develop mathematical models and computational simulations for scientific and industrial applications.

PSO3:

Use advanced numerical techniques and mathematical software to solve complex equations and optimization problems.

PSO4:

Conduct independent research and contribute to the development of new mathematical ideas and applications.

Programme Outcomes

PO-1 (Critical Thinking and Analytical Reasoning):

Demonstrate critical thinking and logical reasoning to recognize, analyze, and evaluate complex real-life scientific Mathematical problems.

PO-2 (Investigation of Complex Problems):

Conduct systematic investigations using research-based knowledge, experimental design, data analysis, interpretation, and synthesis to derive valid conclusions in Mathematical Science.

PO-3 (Modern Tool Usage):

Select and apply appropriate scientific, engineering, and information technology tools, including modeling and prediction techniques, with an understanding of their limitations in Mathematical Science.

PO-4 (Communication):

Communicate effectively with scientific/legal communities and society through clear technical writing, documentation, presentations, and professional interactions.

PO-5 (Environment and Sustainability):

Assess the societal and environmental impact of scientific solutions and demonstrate awareness of sustainable development principles.

PO-6 (Ethics):

Apply ethical principles and uphold professional responsibilities, standards, and norms in scientific and Mathematical practices.

PO-7 (Individual and Team Work):

Function effectively as an individual and as a member or leader in multidisciplinary and diverse teams for Mathematical investigation.

PO-8 (Lifelong Learning):

Recognize the importance of continuous learning and demonstrate the ability to engage in independent and lifelong learning in response to technological advancements in the field of Mathematical Science.

Programme Educational Objectives

PEO1:

Apply advanced mathematical theories and methods to solve complex scientific, technological, and industrial problems.
PEO2:

Pursue doctoral research, academic careers, or advanced professional roles in mathematics and related fields.
PEO3:

Use advanced analytical and computational tools to develop innovative mathematical solutions.
PEO4:

Demonstrate professional ethics, critical thinking, and leadership in academic, research, and industrial environments.

Alumni Speaks

"
My MBA at IILM equipped me with essential business and corporate skills that helped me excel professionally. Case studies, group discussions, and grooming sessions with brilliant peers shaped me into a lifelong learner. Transitioning from a non-finance background to a finance enthusiast was possible due to IILM’s well-designed curriculum. Grateful to call IILM my Alma Mater!”

Anita Ahuja Senior Vice President

MBA 2008-10 Citibank, Singapore

"
As a proud gold medallist of my batch, I had the privilege of dedicating over a decade to Deloitte Consulting. My time at IILM was truly transformative, shaping both my career and personal growth. Returning to campus for the alumni meet was a nostalgic and heartwarming experience.”

Shillaza Girdhar Director - Human Resources

2004-06 Engineering & Consulting Services

"
My MBA at IILM equipped me with essential business and corporate skills that helped me excel professionally. Case studies, group discussions, and grooming sessions with brilliant peers shaped me into a lifelong learner. Transitioning from a non-finance background to a finance enthusiast was possible due to IILM’s well-designed curriculum. Grateful to call IILM my Alma Mater!”