Overview
The MSc Programme in Digital Epidemiology (from academic year 2021-22 onwards) offered at the Department of Data Science aims to build competencies in designing efficient and scalable algorithms for processing, mining, and analyzing dynamic and large-scale epidemiologic/non-epidemiologic data. The programme aspires to achieve data-driven, evidence informed policy impacts for the benefit of the global community by nurturing the students with inter-disciplinary expertise through
• Methodological expertise in big data analysis and its applications
• Strong methodological foundations in multi-disciplinary facets of epidemiology
• Data driven evidence-based research and development using advanced computational capabilities
Curriculum Overview
· Probability and Probability Distributions
· Epidemiology
· Computational Mathematics
· Biostatistical Inference
· Linear Regression Models
· Categorical Data Analysis and Logistic Regression Models
· Clinical Trials
· Disease Modelling and Spatial Modelling
· Programming with R and Python
· Data Management and Data Warehousing
· Data Processing Techniques
· Digital Infrastructure
· Digital Innovation Methods
· Digital Monitoring and Evaluation
· Digital Communication
· Digital Legislation and Policy
· Machine Learning Methods
· Deep Learning and Text Mining
· Health Technology Assessment
· Certification in Research Methodology and Health Informatics
Duration
Two-year full-time programme with modular-based curriculum framework.
Eligibility Criteria
Graduates with the following qualifications (with a minimum of 60% of marks or equivalent grade) from UGC Recognized Universities may apply for MSc (Digital Epidemiology) programme.
• BSc. Statistics/Mathematics/ Computer Science
• BE/B. Tech/BCA
• Any other Graduation with a minimum of two years of learning of Mathematics or Statistics
• Programming knowledge is a pre-requisite for admissions to this programme
Selection Criteria
Selection of eligible candidates will be based on merit of rank obtained in the entrance examination and/or personal interview. In the absence of entrance examination/interview, the merit of rank is prepared by using the grade obtained in Mathematics and/or Statistics and/or Computer Science in the qualifying examinations.
Placement Assistance
The department prepares students for a promising career in the domains of health care technology, e-health governance, policy think tanks along with research and academia. Through industry-academia collaborations, the department provides placement assistance to the students on successful completion of the course.
How to Apply
Applications open for the academic year 2022-23.
Apply at https://apply.manipal.edu/.
Choose Stream: Data Science to apply for this programme.
Click here for the Programme Brochure
Key Dates & Deadlines
15
Mar 15 23
Mar ' 23
Last date to Apply
'
Tentative Course Commencement Date
Indian Students Apply
Manipal Academy of Higher Education not only caters to one’s academic needs, but also lays emphasis on all-round development of its students.
International Students Apply
Manipal Academy of Higher Education not only caters to one’s academic needs, but also lays emphasis on all-round development of its students.
Indian Students Apply
Manipal Academy of Higher Education not only caters to one’s academic needs, but also lays emphasis on all-round development of its students.
International Students Apply
Manipal Academy of Higher Education not only caters to one’s academic needs, but also lays emphasis on all-round development of its students.
Facilties

Healthcare
Access to hospital facilities gives student hands-on training

Innovation Centre
State-of-the-art Innovation Centre facilitates multi-disciplinary research

Labs
Laboratories give students the opportunity for practical experience

Sports & Fitness
Marena has world-class facilities with courts for badminton, tennis, soccer & squash, as well as a well-equipped gymnasium

Libraries
Libraries give students access to study resources, digital and print

Student Housing
Student hostels are their homes away from homes