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Master of Science (M.Sc.) in Mathematics for AI and ML
Duration
2 Years
Eligibility Criteria
Bachelor's degree in IT/CS/Mathematics/ PCM, BCA, B.Sc. Statistics/Data Science with minimum 50% marks
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This course is tailored to meet the increasing demand for skilled professionals in artificial intelligence and machine learning sectors. Over two years, students delve into mathematical concepts essential for understanding and developing AI and ML algorithms. The curriculum covers topics such as linear algebra, calculus, optimisation, probabilistic graphical models, etc., providing students with a solid foundation for advanced studies in AI and ML. With a focus on mathematical rigour and computational techniques, students are well-prepared for careers in research, development, and implementation of AI technologies across diverse sectors.
Apply NowCurriculum
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Introduction to Artificial Intelligence & Machine Learning
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Probability and Random Variables
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Introduction to Python for AI
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Linear Algebra
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Fundamentals of MS Office
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Foundation of Professional Development
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Intellectual Property Rights (IPR)
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Fundamentals of MS Office Lab
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Introduction to Python for AI Lab
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Probability Distributions
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Discrete Structure
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Deep Learning
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Graph Theory
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Cyber Security and Laws
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Analytical Thinking & Problem Solving Skills
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Deep Learning Using Python Lab
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Time Series Analysis and Forecasting
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Big Data Analytics
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Data Visualization
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Numerical Methods
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Introduction to Cloud Computing
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Data Visualization Lab by using Power BI
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Paper/Book/Chapter/Patent
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Generative AI
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Design and Analysis of Algorithms
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Optimization Techniques
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Research Project
USPs
Comprehensive Curriculum: Cover a broad spectrum of mathematical disciplines, including pure and applied mathematics, statistics, and computational mathematics, ensuring a well-rounded and in-depth understanding of the field.
Advanced Research Opportunities: Engage in cutting-edge research projects and collaborate with faculty on innovative mathematical problems, preparing you for a Ph.D. or a research-oriented career.
Expert Faculty: Learn from renowned mathematicians and experienced educators who provide valuable insights and mentorship, helping you to achieve academic and professional excellence.
Strong Career Prospects: Benefit from the program's emphasis on both theoretical and practical applications of mathematics, equipping you with the skills needed for careers in academia, industry, finance, technology, and beyond.
Program Objectives POs
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POs 1
sciences, economics fundamentals, and statistics specialization to solve complex problems in AI and ML.
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POs 2
Problem analysis: Identify, formulate, and analyze complex AI and ML problems, reaching substantiated conclusions using the first principles of mathematics, natural sciences, and statistical methods
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POs 3
Design/development of solutions: Solve complex mathematical and statistical problems in AI and ML, designing system components or processes that meet specified needs while considering public health, safety, cultural, societal, and environmental factors.
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POs 4
Conduct investigations of complex problems: Utilize research-based methods, including the design of experiments, data analysis, interpretation, and synthesis of information, to draw logical conclusions.
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POs 5
Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern tools for prediction and modeling in AI and ML, understanding their limitations.
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POs 6
Professional and Societal Impact: Apply reasoning within contextual knowledge to address societal, health, safety, legal, and cultural issues and responsibilities relevant to professional practice in AI and ML.
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POs 7
Environment and sustainability: Understand the impact of professional AI and ML solutions in societal and environmental contexts, demonstrating the knowledge of and need for sustainable development.
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POs 8
Ethics: Apply ethical principles and commit to professional ethics, responsibilities, and norms in the practice of AI and ML.
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POs 9
Individual and team work: Function effectively both as an individual and as a member or leader in diverse teams and multidisciplinary settings
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POs 10
Communication: Communicate effectively on complex AI and ML activities with the scientific community and society at large, giving and receiving clear instructions.
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POs 11
Project management and finance: Demonstrate knowledge and understanding of principles in statistics, data science, AI/ML, and management, applying them to one's own work as a team member or leader to manage projects in multidisciplinary environments.
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POs 12
Life-long learning: Recognize the need for and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.
Program Educational Objectives PEOs
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PEOs 1
Advanced Knowledge and Skills: They will possess a comprehensive understanding of mathematical and statistical theories, enabling them to apply advanced techniques in AI and ML to solve complex real-world problems across various fields such as business, healthcare, engineering, and social sciences.
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PEOs 2
Research and Innovation: They will be equipped with the skills necessary to conduct independent research and contribute to the advancement of AI and ML knowledge. They will develop innovative solutions and methodologies, driving progress in academic, industrial, and governmental research initiatives.
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PEOs 3
Professional and Ethical Leadership: They will demonstrate professional integrity and ethical responsibility in their practice. They will be prepared to assume leadership roles, effectively communicating mathematical concepts and AI/ML results to both technical and non-technical audiences, and contributing to informed decision-making processes within their organizations.