M.Tech (Data Science)

Post Graduate Programmes

APPLY NOW 2022 Admissions

Program Code 10684

Course Overview

  • Campus
  • Noida
  • Institute
  • Amity School of Engineering and Technology
  • University
  • Amity University Uttar Pradesh
  • Program Code
  • 10684
  • Eligibility
  • For Non Sponsored category:

    Bachelor Degree of 4 year Engg. in (CSE/IT/ECE/EEE/EE/E&TE/AI/ME/Instrumentation & Control Engg./ Bioinformatics) agg.60% or AMIE / AMIETE in (CS/IT) agg. 60% or MCA or Master's Degree in (CS/IT/Maths/Physics/Statistics) agg. 60%

    AND

    Class XII (agg.60%) with PCM

    For Sponsored category:

    Eligibility will be relaxed by 5% in bachelor's degree and class XII for Sponsored category.

     

     

     

     

     

  • Duration
  • 2 years
  • 1st Year Non Sponsored Semester Fee (Rs. in Lacs)
  • 0.735
  • 1st Year Sponsored Semester Fee (Rs. in Lacs)
  • 1.105
 
  • Fee Structure
  • Program Educational Objectives
  • Program Learning Outcomes
1st Year Non Sponsored Semester Fee (Rs. in Lacs) : 0.735
1st Year Sponsored Semester Fee (Rs. in Lacs) : 1.105
  • 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.
  • The students shall have the ability to acquire a combination of theoretical, conceptual, analytical, computational, and experimental knowledge in the field of Electronics and Communication for research, design and development of novel products and solutions as an individual / member of a team/ leader in diverse teams and as an entrepreneur.
  • The students shall have the ability to examine the impact of engineering solutions and relate issues to the broader social, economic, legal, health, safety, cultural, and environmental contexts.
  • The students shall have the ability to analyse the engineering information and infer the results for successful and productive careers or advance studies/research in the field of Electronics and Communication.
  • The students will be able to practice professional ethics and academic integrity and demonstrate these as an individual / team member / leader in diverse teams
  • Students will be able to demonstrate professional attitudes, effective communication and behavioural skills and sustain effective performance in the professional / entrepreneurial careers.
  • The student will have the ability to support and practice independent and life-long learning for professional development.
  • 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.
  • Graduates will have ability to apply the knowledge of mathematics, sciences and engineering to solve problems using concepts of Data Science.
  • Graduates will have the ability to choose self–directed and active learning through strong intellectual engagement in independent work relevant to Data Science for maximizing their potential by utilizing abilities and academic excellence and furthermore, think independently, analytically and creatively through self-directed learning.
  • Graduates will have the ability to use research-based knowledge and methods including design of experiments, analysis and interpretation of data, and synthesis of the information to arrive at valid conclusions, exercise critical judgment and thinking to create new systems / products / services etc.
  • Graduates will have the ability to create, select, and apply modern engineering techniques, resources and IT tools for modelling and simulation of engineering problems, develop self-paced learning through various tools and techniques of ICT.
  • Graduates will have the ability to apply critical, creative and evidence-based thinking for creating solutions of engineering problems and to design system components or processes that meet the specified needs with appropriate consideration for the public health, safety, cultural, societal, and environmental considerations
  • Graduates will have the ability to communicate effectively on engineering activities with the engineering professionals and society at large, such as, being able to comprehend and write effective reports, make effective presentations, give & receive clear instructions by utilizing various Information Technology tools and skills.
  • Graduates will have the ability to demonstrate scientific creativity and reflective thinking to critically evaluate ideas for developing innovative processes and products relevant to industry/societal needs.
  • Graduates will have the ability to demonstrate analytical and decision-making skills to identify, formulate, and analyse complex engineering problems reaching substantiated conclusions using concepts of mathematics, science & engineering.
  • Graduates will have the ability to function effectively as an individual, and as a member or leader in diverse teams, VUCA world and multidisciplinary settings for making the organization resourceful and achieving organisation goals.
  • Graduates will have the ability to apply contextual knowledge to assess societal, health, safety, legal, cultural issues and the consequent responsibilities relevant to the professional engineering practice, appreciate diversity (caste, ethnicity, gender and marginalization), values and beliefs of multiple cultures in a global perspective.
  • Graduates will have the ability to demonstrate ethical practices in professional field, display integrity at workplace and be responsible global citizens, and also appreciate concerns on environment sustainability.
  • Graduates will have the ability to acquire social and emotional skills to work effectively with diverse group of people in multi-cultural environment and situations, demonstrate adaptability and resilience during uncertain situations.
  • Graduates will have the ability to demonstrate knowledge and understanding of the engineering & management principles and use these enterprising skills to bring new business ideas and product of innovative designs with a social impact to start a new venture.
  • Graduates will have the ability to develop independent thinking and life-long learning in broader context of technological changes, explore new ideas and learning opportunities for self-directed learning.
  • Graduates will have the ability to understand the impact of the professional engineering solutions in societal and environmental contexts and develop sustainable technologies using Computer Science Engineering knowledge.

Course Structure

  • 1st Year
  • 2nd 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 Computer Graphics (PG) Specialisation Elective Courses 3 0 2 0 4.00 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
Data Warehousing and Data Mining (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

Semester 2

Course Title Course Type Credit L T PS SW Total Credits Syllabus
Principles Of Machine Learning (PG) Core Courses 0 0 0 0 0.00 View
Web Intelligence and Big Data (PG) Core Courses 3 0 4 0 5.00 View
Pattern Recognition and Image Processing (PG) Specialisation Elective Courses 3 0 4 0 5.00 View
Parallel and Distributed Algorithms (PG) Specialisation Elective Courses 3 1 0 0 4.00 View
Distributed Computing Systems (PG) Specialisation Elective Courses 3 0 0 0 3.00 View
Data Compression and Techniques (PG) Specialisation Elective Courses 3 1 0 0 4.00 View
Advanced Database Management Systems (PG) Specialisation Elective Courses 3 0 4 0 5.00 View
Independent Study and Research - I (PG) Non Teaching Credit Courses 0 0 0 0 2.00 View

Semester 3

Course Title Course Type Credit L T PS SW Total Credits Syllabus
Data Visualization (PG) Specialisation Elective Courses 3 1 0 0 4.00 View
Information Retrieval System (PG) Specialisation Elective Courses 3 1 0 0 4.00 View
R-Programming and Hadoop (PG) Specialisation Elective Courses 3 0 4 0 5.00 View
System Simulation and Modeling Techniques (PG) Specialisation Elective Courses 3 0 4 0 5.00 View
Web Intelligence and Big Data (PG) Specialisation Elective Courses 3 0 4 0 5.00 View
Text Mining and Analytics (PG) Specialisation Elective Courses 3 1 0 0 4.00 View
Information Security Policies in Industries (PG) Specialisation Elective Courses 3 0 0 0 3.00 View
Summer Internship (PG) Non Teaching Credit Courses 0 0 0 0 4.00 View
Minor Project (PG) Non Teaching Credit Courses 0 0 0 0 4.00 View
Advanced Neural Networks (UG) Specialisation Elective Courses 3 0 2 0 5.00 View
Artificial Neural Networks (PG) Specialisation Elective Courses 2 0 2 0 3.00 View
Deep Learning Algorithms and Applications (PG) Specialisation Elective Courses 2 0 2 0 3.00 View
Industry 4.0 and Industrial Internet of Things (PG) MOOC (Amity On - line / NPTEL / SWAYAM / Future Learn) 0 0 0 0 0.00 View
MOOC (Amity On - line / NPTEL / SWAYAM / Future Learn) 0 0 0 0 0.00 View

Semester 4

Course Title Course Type Credit L T PS SW Total Credits Syllabus
Dissertation (PG) Non Teaching Credit Courses 0 0 0 0 16.00 View