M.Tech. (Bioinformatics)

Post Graduate Programmes

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Program Code 10346

Course Overview

  • Campus
  • Noida
  • Institute
  • Amity Institute of Biotechnology
  • University
  • Amity University Uttar Pradesh
  • Program Code
  • 10346
  • Eligibility

  • For Non- Sponsored: Engg. Degree of 4 years (agg. 60% ) in Bioinformatics / Biotechnology/ Computer Science OR B.Pharm (agg. 60%) OR Master's Degree (agg.60%) in Biotech / Life Sciences / Computer Science AND Class XII (agg.60%) with PCB/PCM

    For Sponsored: Eligibility will be relaxed by 5% in Bachelor's or Master's Degree and Class XII.

     

  • Duration
  • 2 years
  • 1st Year Non Sponsored Semester Fee (Rs. in Lacs)
  • 0.720
  • 1st Year Sponsored Semester Fee (Rs. in Lacs)
  • 1.080
 
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  • Fee Structure
  • Program Educational Objectives
  • Program Learning Outcomes
1st Year Non Sponsored Semester Fee (Rs. in Lacs) : 0.720
1st Year Sponsored Semester Fee (Rs. in Lacs) : 1.080
  • The student shall be able develop conceptual as well as applied knowledge in the field of Bioinformatics & Computational Biology to attain academic excellence.
  • The student shall be able to implement self-directed and active learning strategies in independent work related to Bioinformatics.
  • The student shall demonstrate and apply scientific enquiry and research aptitude towards development of sustainable solutions through Bioinformatics.
  • The student shall be able to use and apply information and communication technologies and participate in collaborative networks for developing requisite skills of Industry 4.0 in the field of computational biology.
  • The student shall be able to apply critical thinking and knowledge to design and synthesize solutions for scientific problems in bioinformatics.
  • The student shall develop effective communication skills to facilitate relationship building.
  • The student shall be able to combine scientific creativity and reflective thinking to critically evaluate innovative ideas in Bioinformatics for developing processes and products relevant to industry/societal needs.
  • The student shall be able use modern tools & algorithms to compare, contrast and analyze large biological datasets to take appropriate and effective decisions.
  • The student shall be able to attain and demonstrate result-oriented teamwork and conflict resolution through leadership qualities while maintaining responsibility and accountability.
  • The student shall demonstrate competence in a cross-cultural environment and evolve as a responsible global citizen.
  • The student shall be able to practice and establish the ethical principles in social and professional life.
  • The students shall be able to acquire social and emotional skills to work effectively with varied group of people in multi-cultural environment and situations.
  • The student shall be able to define their career aspirations and work towards achieving the same by engaging in developing appropriate skills and competencies in their selected profession (corporate career, start ups or higher education etc.).
  • The student shall be able to develop and reflect lifelong learning approach to create new knowledge from existing knowledge in the field of Bioinformatics.
  • The student shall be able to execute their knowledge to conserve natural resources and develop sustainable technologies in the field of Bioinformatics.
  • The student will be able develop conceptual as well as applied knowledge in the field of bioinformatics & computational biology to attain academic excellence.
  • The student shall be able to implement self-directed and active learning strategies in independent work related to Bioinformatics.
  • The student will demonstrate and apply scientific enquiry and research aptitude towards development of sustainable solutions through bioinformatics knowledge.
  • The student will be able to use and apply information and communication technologies and participate in collaborative networks for developing requisite skills of Industry 4.0 in the field of bioinformatics.
  • The student will be able to apply critical thinking and knowledge to design and synthesize solutions for scientific problems in field of bioinformatics.
  • The student will be confident and effective in employing communication skills to developing interpersonal skills relationship-building and communication.
  • The student will be able to combine scientific creativity and reflective thinking to critically evaluate innovative ideas in bioinformatics for developing processes and products relevant to industry/societal needs.
  • . The student will be able use modern tools & algorithms to compare, contrast and analyse large biological datasets to take appropriate and effective decisions.
  • The student will be able to attain and demonstrate result-oriented teamwork and conflict resolution through leadership qualities while maintaining responsibility and accountability.
  • The student will demonstrate competence in a cross-cultural environment and evolve as a responsible global citizen.
  • The student will be able to practice and establish the ethical principles in social and professional life.
  • The students will be able to acquire social and emotional skills to work effectively with diverse group of people in multi-cultural environment and situations.
  • The student will be able to define their career aspirations and work towards achieving the same by engaging in developing appropriate skills and competencies in their chosen profession (corporate career, start up, and higher education etc.).
  • The student will be able to develop and reflect lifelong learning approach to create new knowledge from existing knowledge in the field of bioinformatics.
  • The student will be able to execute their knowledge to conserve natural resources and develop sustainable technologies through the use of bioinformatics.

Course Structure

  • 1st Year

Semester 1

Course Title Course Type Credit L T PS SW Total Credits Syllabus
Programming Skills & Algorithms (PG) Core Courses 0 0 0 0 0.00 View
Advanced biology (PG) Core Courses 2 0 2 0 4.00 View
Bioinformatics and Computational Biology (PG) Specialisation Elective Courses 3 0 2 0 4.00 View
Data science in life sciences (PG) Specialisation Elective Courses 0 0 0 0 0.00 View
Applied Mathematics & Bio-Statistics (PG) Specialisation Elective Courses 0 0 0 0 0.00 View
Biochemical and Molecular Diagnostics in Health Care (PG) Specialisation Elective Courses 3 0 0 0 3.00 View
Protein Engineering (PG) Specialisation Elective Courses 3 0 0 0 3.00 View

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