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B.Tech. CSE with Specialization in Data Science

Why take this course?

B.Tech in Data Science - The advent of the internet has expanded the digital technology landscape. Our every action online leave a footprint in the digital form. This has completely transformed the business world at a rapid speed. There is a massive explosion of data on daily basis, which is helping organizations to monitor the behavior of their customers. As a result, organizations are giving more prominence for extracting valuable insights from the information available and the responsibility is mainly handled by data science professionals. It has generated an enormous scale of job opportunities for data science professionals in the market. In order to meet this demand, Jain University is offering B.Tech (Hons.) in CSE with specialization in Data Science, which helps students find better jobs in this sector.

What will I experience?

  • Learn a set of data science principles, tools, and techniques to solve real-world business problems and also suggest a suitable solution with relevant findings.
  • Recognize various issues in everyday business; apply data science for better understanding of data-driven management decisions to help organizations get an edge over competition
  • Provide insight into leading analytic practices, design and lead iterative learning and development cycles. Knowledge on producing new and creative analytic solutions that will become part of any business core deliverables
  • Knowledge on how to improve business results by building data fuelled products that help their customers.

What opportunities might it lead to?

According to NASSCOM, the big data analytics market will reach $16 billion by the year 2025 growing eightfold from its market worth in 2016. And India will require over 200,000 data scientists by 2018 as per various industry insights.

Some of the designations, which students can look forward to in organizations are:

  • Data Engineer
  • Citizen Data Scientist
  • Enterprise Data Analyst
  • Machine Learning Engineer

 

Degree Awarded

Bachelor of Technology

Course Commencement

June 2017

Eligibility

Student must have passed 10+2 or equivalent examination with Physics, Mathematics and English as compulsory subjects along with Chemistry or Biotechnology or Biology or any technical vocational subjects as optional with a minimum of 60% marks (55% in case of SC/ST) taken together in Physics, Mathematics and any one of the optional subjects.

Study Campus

Admission Office



Curriculum Structure & Teaching

I Semester
  • Mathematics for Data Scientist -I
  • Sociology and Elements of Indian History for Engineers
  • Basics of Civil and Mechanical Engineering
  • Probability & Statistics - I
  • Introduction to Data Analytics using Excel
  • Introduction to Information Science
  • Information Science Lab
  • Workshop Lab
  • Value Education Human Right and Legislative problems
II Semester
  • Mathematics for Data Scientist -II
  • Law for Engineers
  • Basics of Electrical and Electronics
  • Probability & Statistics - II
  • Linear Algebra
  • Computer Programming
  • Computer Programming Lab
  • Electrical and Electronics Lab
  • Environmental Studies
III Semester
  • Mathematics for Data Scientist -III
  • Economics for Engineering
  • Data Structures
  • Computer Organisation and Architecture
  • Object-Oriented Programming with Java
  • RDBMS
  • Data Structures Lab
  • Object Oriented Programming with Java Lab
  • RDBMS Lab
  • Energy Studies

IV Semester
  • Operating System
  • Analysis of Algorithm
  • Data Visualization (Tool Based)
  • Introduction to SQL (Tool Based)
  • NoSQL Databases
  • Business Communication and Presentation skill / Professional Ethics
  • Scientific Programming using R (Tool Based)
  • Linux Lab
  • NoSQL Databases Lab

V Semester
  • Inferential Statistics (Tool Based)
  • Advanced SQL
  • Big Data Analysis
  • Machine Learning Algorithms - I
  • Optimization Techniques
  • Artificial Intelligence
  • Advance SQL Lab
  • Machine Learning Algorithms - I Lab
  • Big Data Analysis - I Lab

VI Semester
  • Exploratory Data Analysis (Tool Based)
  • Big Data Analysis - II
  • Machine Learning Algorithms - II
  • Time Series Analysis (Tool Based)
  • Elective - I
  • Elective - II
  • Elective - I Lab
  • Big Data Analysis - II Lab
  • Machine Learning Algorithms - II Lab
Elective - I
  • Cloud Management System
  • Cloud Web Services
  • Cloud Solution Management
Elective - II
  • Natural Language Processing
  • Neural Networks
  • Recommender System

VII Semester
  • Dimensionality Reduction and Model Validation(Tool Based)
  • Advanced Machine Learning Algorithms (Tool Based)
  • Data Science Project Management
  • Latest Trends in Data Science
  • Open Elective-I
  • Open Elective-II
  • Mini Project

VIII Semester
  • Open Elective-III
  • Open Elective-IV
  • Internship/ Project work –II
* Subject to Changes if Any