M.Tech (Data Science)

Post Graduate Programmes

APPLY NOW 2019 Admissions

Program Code 10684

Course Overview

  • Campus
  • Noida
  • Institute
  • Amity School of Engineering and Technology
  • University
  • Amity University Uttar Pradesh
  • Program Code
  • 10684
  • Eligibility
  • BE / B. Tech. / AMIE / MCA / M. Sc. (CS / IT / Physics / Maths / Stats) (min 60%) & 10+2 (min 60%). Eligibility will be relaxed by 5% for Sponsored category.

  • Duration
  • 2 years
  • 1st Year Non Sponsored Semester Fee (Rs. in Lacs)
  • 0.70
  • 1st Year Sponsored Semester Fee (Rs. in Lacs)
  • 1.05
 
  • Fee Structure
  • Program Educational Objectives
  • Program Learning Outcomes
1st Year Non Sponsored Semester Fee (Rs. in Lacs) : 0.70
1st Year Sponsored Semester Fee (Rs. in Lacs) : 1.05
  • To equip students with the knowledge to extract meaningful information from the continuously increasing data by applying data engineering techniques.
  • To enhance student knowledge about collecting data, effective data analysis, making inferences and conclusions about real world phenomena and applying modern statistical methods.
  • To equip students with the latest knowledge and technology to meet the latest industry as well as research needs and get their dream jobs.
  • To expose students to the Global Work Environment and work / research in international cultures.
  • To motivate students to become entrepreneurs, leaders, researchers or academicians both in their chosen profession and in other activities.
  • To prepare students to serve industry as an individual or as a team member with high degree of professional ethics and values.
  • Graduates will be able to apply the knowledge of mathematics, science, engineering fundamentals, and domain knowledge of Computer Science and Engineering to the solution of complex engineering problems.
  • Graduates will be able to identify, formulate and solve complex engineering problems reaching substantiated conclusions with focus in Computer Science and Engineering.
  • Graduates will be able to create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations with focus in Computer Science and Engineering
  • Graduates will be able to design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations
  • Graduates will be able to communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
  • Graduates will be able to function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
  • Graduates will be able to apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
  • Graduates will follow ethical principles/norms and commit to professional ethics and responsibilities/ norms of engineering practice
  • Graduates will be able to demonstrate knowledge and understanding of the Computer Science and Engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments
  • Graduates will 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.
  • Graduates will be able to understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
  • Graduates will be able to use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.

Course Structure

  • 1st Year

Semester 1

Course Title Course Type Credit L T PS SW Total Credits Syllabus
Advanced Data Structures (PG) Core Courses 0 0 0 0 0.00 View
Mathematical Foundation of Computer Science (PG) Core Courses 0 0 0 0 0.00 View
Advanced Software Project Planning and Management (PG) Specialisation Elective Courses 3 0 4 0 5.00 View
Advanced Software Testing and Quality Assurance (PG) Specialisation Elective Courses 3 0 4 0 5.00 View
High Performance Computer Architecture (PG) Specialisation Elective Courses 3 1 0 0 4.00 View
Data Warehousing and Data Mining (PG) Specialisation Elective Courses 3 0 4 0 5.00 View
Advanced Computer Graphics (PG) Specialisation Elective Courses 3 0 2 0 4.00 View
Data Preparation and Analysis (PG) Industry Specific Courses 0 0 0 0 0.00 View