ME – Artificial Intelligence and Data Science



In early days, the computing systems were used only for solving computing problems. But looking at the reasoning capabilites of these systems, the problems relating to intelligent computing are also successfully solved. The artificially intelligent systems tend to do as many tasks as human can do with his natural intelligence. Many companies and organizations are applying the artificially intelligent systems into their products and processes. The application areas of Artificial Intelligence and Data Science are Healthcare, Education, Sports, Agriculture, Construction, Banking, Marketing, E-commerce and many more. The virtual assistants, robots, self driving vehicles are real examples of artificially intelligent system. India is always at the front when it comes to adopt emerging technologies. Many industries and organizations are hiring AI and data science experts to help them to get actionable insights from large volumenous data. As the data analytics sector is growing, there is increase in demand for highly-skilled professionals who knows the technical methods to get the insights from raw data.

Career Prospects
    After successful completion of this PG program, the aspirants have the opportunities to play a role such as Data Scientist, Machine Learning Engineer, Data Analyst, Statistician, Data Architect, Business Intelligence Developer, Enterprise Architect, Big Data Engineer in public/private sector.
    As both these intersecting fileds (i.e.Artificial Intelligence and Data Science) have numerous scope for research, the aspirants may select research path and buid a bright career.
    One can also explore the opportunities of enterprenureship as there are many funding options initiated by Government to promote the youth in these emerging technologies.

 

Program Outcomes

  • An ability to independently carry out research /investigation and development work to solve practical problems.
  • An ability to write the present substantial technical report/documents.
  • Students should be able to demonstrate a degree of mastery over the area as per the specialization of the program. The mastery should be at a level higher than the requirements in the appropriate bachelor program.

Program Specific Outcomes

  • To understand and analyse the various statistical methods, data visualization methods, expert systems, optimization algorithms to build AI based data driven models.
  • Develop models in Data Science and Machine learning technologies using acquired AI knowledge and modern tools.
  • Apply advanced knowledge of data science and AI algorithms to identify research challenges, and contribute individually or in a team to resolve societal real-time problems.

Program Educational Objectives

  • To deliver the knowledge for developing intelligent sustainable systems as per need of society.
  • To work in reputed industries, Government and Research organizations or as an entrepreneur to build career in the field of data science and Artificial intelligence.
  • To able to manage the challenges in developing knowledge based systems through consistent learning, better responsibility, teamwork and an ethical code of conduct.


  • High-Performance Computing (HPC) Laboratory
  • Data Science Laboratory
L=Lectures,T=Tutorial,P=Practical,E=Theory External,M=Theory Internal,I=Practical Internal,V=Practical External
Subject codeBranch codeSubject NameCategorySemesterLTPCreditEMIVTotal Marks
370000495 Value EducationAudit120005000050
3710001
95Research Methodology and IPRMLC11022002080100
171950195Artificial and Computational IntelligenceCore -I1302470302030150
1719502
95 Foundations for Data ScienceCore -II1302470302030150
171950395Bio-inspired AlgorithmsProgram Elective -I1302470302030150
171950495Statistics and Exploratory Data AnalysisProgram Elective -I1302470302030150
171950595Advanced Data StructuresProgram Elective -I1302470302030150
171950695Real World Applications of Artificial Intelligence and Data ScienceProgram Elective -II1302470302030150
171950795Data Visualization and InterpretationProgram Elective -II1302470302030150
171950895Graphs - Algorithms & MiningProgram Elective -II1302470302030150
370000195English for Research Paper WritingAudit Course220005000050
372000195Mini Project with SeminarCore20042001000100
172950195Deep LearningCore III2302470302030150
172950295Big Data Systems and AnalyticsCore IV2302470302030150
172950395Explainable Artificial IntelligenceProgram Elective III2302470302030150
172950495Blockchain TechnologyProgram Elective III2302470302030150
172950595Natural Language ProcessingProgram Elective III2302470302030150
172950695IoT & Embedded SystemsProgram Elective IV2302470302030150
172950795Software TestingProgram Elective IV2302470302030150
172950895Human Computer InteractionProgram Elective IV2302470302030150
373000295Internal Review-ICore30042001000100
373000395Dissertation Phase-ICore300168000100100
373000595Business AnalyticsOpen Elective33002703000100
373000695Industrial SafetyOpen Elective33002703000100
373000895Cost Management of Engineering ProjectsOpen Elective33002703000100
373000795Operation ResearchOpen Elective33002703000100
173950195Artificial Intelligence for RoboticsProgram Elective V3302470302030100
173950295Cloud and Edge ComputingProgram Elective V3302470302030100
173950395Pattern RecognitionProgram Elective V3302470302030100
374000195Internal Review - IIDissertation40042001000100
374000295Dissertation Phase - IIDissertation4002814000100100

Tokyo

Tokyo is the capital of Japan.

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