Curriculum

Master of Technology (M.Tech) in Data Science

The Department of Computer Science and Engineering, SRM University-AP, Amaravati offers M.Tech Computer Science and Engineering with Data science as specialization. The programm is offered in two year duration. The Data Science is a multi-disciplinary area required techniques to handle the flood of big data generated across the world. Experts in the field of Statistics and Computer Science working together for developing the skill set required to collect, process and extract meaningful information from large and diverse data sets. The Data visualization is a technique, which allows a way to understand the big data. The experts in Data science are required by every industry, government organization and Internet start-ups to financial institutions to handle big data projects at every level. It is understood that by 2018, there is requirement for more than 2 million data scientists and 1.5 million managers and analysts who understand how to use big data to make decisions. This post-graduate programme, which specializes in Data Science along is aimed at enhancing the skill set of engineers to be data scientists.

  • Semester 1

    Credits
  • Mathematical Foundations for data science

    3
  • Machine Learning Techniques

    3
  • Data Analytics

    3
  • Advanced Algorithms and Analysis

    3
  • Elective I

    3
  • Data Analytics Lab

    2
  • Machine Learning Lab

    2
  • Semester 2

    Credits
  • Analytic Database

    3
  • Social Media Analysis

    3
  • Information Retrieval

    3
  • Elective-I

    3
  • Elective II

    3
  • Social Media Analysis Lab

    2
  • Information Retrieval Lab

    2
  • Semester 3

    Credits
  • Project work- Phase I

    12
  • Semester 4

    Credits
  • Project Work –Phase II

    12
  • 62

List of Electives

  • Data Security
  • Data Privacy
  • Data Acquisition and Productization
  • Parallel and Distributed Systems
  • Multicore and GPU architecture
  • Image and Video Analytics
  • Web Database and Information Systems
  • Bio-informatics
  • Mining for Big Data
  • Financial Analytics
  • Internet of Things
  • Business Intelligence
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