Advance your career with our
Online M.Sc.
UGC Entitled
20+ Industry Partners
2 Tailored Specializations
Admission Enquiry
Duration:
2 Years | 4 Semesters
2 Specializations
- Statistics
- Data Science & AI
Work Experience:
No work experience required.
Duration:
2 Years | 4 Semesters
Specializations
2 Specializations:
- Statistics
- Data Science & AI
Work Experience:
No work experience required.
Why Choose This Course?
Our Highlights
- UGC Entitled.
- Accredited with A+ grade in NAAC.
- Industry relevant curriculum curated as per AICTE norms.
Our Curriculum is
- Crafted by industry experts.
- Designed for aspiring leaders who want to thrive in today’s world.
- Integrated with global business insights, preparing students to work in multicultural & international business environments.
We Give You
- AI enabled proctored exams: guaranteeing fair & trustworthy assessment process.
- Personalized Mentorship & guidance from experienced mentors
- Unique 4 Quadrant Approach & our very own Learning Management System.
The M.Sc. program at Dr. M.G.R. Educational and Research Institute is structured to provide a comprehensive blend of theoretical concepts and practical applications, preparing students for the evolving demands of the data-driven world. With a strong emphasis on analytical thinking, problem-solving, and technological advancements, the curriculum is tailored to enhance research capabilities and industry readiness.
Both specializations [M.Sc. Statistics & M.Sc. Data Science & AI] are designed to cater to the growing need for data experts and analytical professionals. Whether aspiring for a career in academia, research, finance, healthcare, or technology-driven industries, students gain in-depth expertise and hands-on experience, making them valuable assets in today’s competitive job market.
For M.Sc. Statistics:
- B.Sc (Mathematics), B.Sc (Statistics) or any UG Degree with Mathematics/Statistics as one of the core / Allied/Ancillary paper from a recognized University.
For M.Sc. Data Science & AI:
- Minimum of 3 or 4 years duration Bachelor’s degree in Statistics/Mathematics/Computer Science/ Engineering/Technology or any other discipline with a minimum of 2 years of learning Mathematics or Statistics from a recognized University with at least 50% marks in aggregate.
Program Educational Objectives:
- PEO1:
- PEO2:
- PEO3:
- PEO4:
- Every Student would be registered on provisional basis and the students are provided the access to course material as a learner.
- Confirmed admission for respective course is subject to eligibility check which would be communicated tentatively one month before the scheduled exams based on all the mandatory documents submitted by the students.
- The prospective student should check their eligibility before provisional enrolment process and there would be no refund of any registration or part fees payment paid to the university for enrolment
- The student would be provided with the login credentials of the Virtual Campus on email for accessing the courses online.
The LMS have semester wise buckets for subjects of the respective programs as enrolled. The student would have access to following learning resources:
- Live Interactive Online Sessions
- Tutorials
- Quick Learning Book
- Simulated Case Studies
- Frequently Asked Questions (FAQ)
- Web Resources for Research Purpose
- Online Discussion Forums
- Digital Text Book
- Gamified Practice Test
- Practice Assignments
- Misconceptions
- Every subject would have continuous evaluation and semester end examination.
- Weightage on every subject: Continuous Evaluation : 25% and Semester End Exams : 75%.
- The continuous evaluation would be done through the learning management system.
- The university follows the grading system for evaluation purpose please refer the university website for the same.
- The semester end exams information would be mentioned on university website and the same would be communicated to students well in advance.
- The score of Objective type of assignment (A1) would be displayed immediately after the assignments are submitted at the respective assignment tab in LMS as the same is system evaluated.
- The score of Subjective assignment (A2) would be displayed at respective assignment tab in LMS only after the faculty has evaluated the scores.
- The score of Graded Discussion Forum (A3) would be displayed at respective assignment tab in LMS only after the faculty has evaluated the scores.
The M.Sc. program at Dr. M.G.R. Educational and Research Institute is structured to provide a comprehensive blend of theoretical concepts and practical applications, preparing students for the evolving demands of the data-driven world. With a strong emphasis on analytical thinking, problem-solving, and technological advancements, the curriculum is tailored to enhance research capabilities and industry readiness.
Both specializations [M.Sc. Statistics & M.Sc. Data Science & AI] are designed to cater to the growing need for data experts and analytical professionals. Whether aspiring for a career in academia, research, finance, healthcare, or technology-driven industries, students gain in-depth expertise and hands-on experience, making them valuable assets in today’s competitive job market.
For M.Sc. Statistics:
- B.Sc (Mathematics), B.Sc (Statistics) or any UG Degree with Mathematics/Statistics as one of the core / Allied/Ancillary paper from a recognized University.
For M.Sc. Data Science & AI:
- Minimum of 3 or 4 years duration Bachelor’s degree in Statistics/Mathematics/Computer Science/ Engineering/Technology or any other discipline with a minimum of 2 years of learning Mathematics or Statistics from a recognized University with at least 50% marks in aggregate.
Program Educational Objectives:
- PEO1: Empower graduates to excel in diverse data science and AI roles, leveraging advanced analytical techniques and machine learning algorithms.
- PEO2: Foster a culture of innovation and research, enabling graduates to contribute to cutting-edge advancements in data science and artificial intelligence.
- PEO3: Develop leaders who can effectively manage interdisciplinary teams and projects, driving innovation and addressing complex challenges in various industries.
- PEO4: Promote ethical practices and responsible use of data and AI technologies, ensuring graduates prioritize privacy, fairness, and transparency in their work.
- PEO5: Inspire a commitment to lifelong learning and professional development, equipping graduates to adapt to evolving technologies and industry trends throughout their careers.
- Every Student would be registered on provisional basis and the students are provided the access to course material as a learner.
- Confirmed admission for respective course is subject to eligibility check which would be communicated tentatively one month before the scheduled exams based on all the mandatory documents submitted by the students.
- The prospective student should check their eligibility before provisional enrolment process and there would be no refund of any registration or part fees payment paid to the university for enrolment
- The student would be provided with the login credentials of the Virtual Campus on email for accessing the courses online.
The LMS have semester wise buckets for subjects of the respective programs as enrolled. The student would have access to following learning resources:
- Live Interactive Online Sessions
- Tutorials
- Quick Learning Book
- Simulated Case Studies
- Frequently Asked Questions (FAQ)
- Web Resources for Research Purpose
- Online Discussion Forums
- Digital Text Book
- Gamified Practice Test
- Practice Assignments
- Misconceptions
- Every subject would have continuous evaluation and semester end examination.
- Weightage on every subject: Continuous Evaluation : 25% and Semester End Exams : 75%.
- The continuous evaluation would be done through the learning management system.
- The university follows the grading system for evaluation purpose please refer the university website for the same.
- The semester end exams information would be mentioned on university website and the same would be communicated to students well in advance.
- The score of Objective type of assignment (A1) would be displayed immediately after the assignments are submitted at the respective assignment tab in LMS as the same is system evaluated.
- The score of Subjective assignment (A2) would be displayed at respective assignment tab in LMS only after the faculty has evaluated the scores.
- The score of Graded Discussion Forum (A3) would be displayed at respective assignment tab in LMS only after the faculty has evaluated the scores.
Admission Process
