B.Tech. (CS – Data Science)

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Bachelor of Technology (CS – Data Science)

Duration: 4 years, Eight semesters. (Admissions open for the batch 2018-19)

Eligibility:Pass in the 10+2 examination (Pre-University Board Examination) with Physics, Chemistry & Mathematics that is recognised by any state board / central board as per norms. Admissions to the programs to be done on the basis of the JEE / University Entrance Exams.

About B.Tech (CS – Data Science)

This unique program provides dual career options for the students in the fast-growing technology sectors of Data Science. In addition to all the mandatory subjects of a traditional engineering program, this specialized program offers in-depth practical know-how of the current trend Technology – Data Science. These sectors have the potential to grow exponentially and they provide challenging job opportunities for young professionals with the right skill sets.

On the Data Science front, the program will provide students with the fundamental knowledge of all aspects of Statistics and Analytics. The program focuses on Probability and Statistics, Server Inferential Statistics, Machine Learning Techniques, Exploratory Data Analysis, Visualization Techniques and other related Data Science concepts.

On the Big Data Analytics front, this program equips the students with the concepts and the technical skills needed to secure knowledge on Big Data analytics concepts and real time practical knowledge. The focus of the program is on the models, tools and techniques for enforcement of Big Data Analytics, Big data Analytics on Cloud, Real time data Processing and NoSQL data base concepts.

Special Features of the Program:

  • Duration of the course is 4 years with 8 semesters.
  • Classes are conducted between 9:00 AM and 4:30 PM for 5 days a week and between 9:00 AM and 1:00 PM on Saturdays.
  • Spacious multimedia classrooms and well equipped laboratories with sufficient number of computer systems with latest updated software.
  • Dynamic, qualified, dedicated and research oriented teaching faculty who work towards the overall betterment of the students.
  • Excellent technical faculty to provide technical assistance to the students during practical sessions.
  • E-Study material will be provided from the college for every subject according to the syllabus.
  • Industry oriented syllabus with special focus on experimental learning.
  • Mini projects that help students implement the theoretical knowledge gained into practical applications which gives a better understanding of the subject.
  • Innovations in examination system with opportunity to seethe evaluated papers in person.
  • Make-up exams in every semester to avoid year loss.
  • Placement support and research oriented projects for every student.
  • Focus on smart skill development and training for competitive exams.
  • Opportunity for internships and industrial visits.
  • Tie up with industries to get students trained in latest technology through industry sessions/ workshops.
  • Number of seminars, technical talks by experts from industries and academicians is organised by the Department of CSE.
  • Hands on sessions/workshops by industry experts, technical paper presentations, project exhibitions, coding and debate competitions are held by the Department of CSE.

Career Opportunities:

Associate Business analyst, Data Science Engineer, Database Developer, Hadoop Transfer, ETL Developer, Data Analyst, Data warehouse analyst, ETL Specialist.

Anvar Shathik J

B.E., M.E., M.I.S.T.E

Co-Ordinator B.Tech.in Data Science

 Programme Structure:

SEMESTER 1 SEMESTER 2
S.No Subjects Marks S.No. Subjects Marks
1 Engineering Mathematics – I 100 1 Engineering Mathematics – II 100
2 Engineering Physics 100 2 Engineering Chemistry 100
3 Elements of Electronics Engineering 100 3 Basics of Electrical Engineering 100
4 Elements of Mechanical Engineering 100 4 Elements of Civil Engineering 100
5 Computer Concepts & C Programming 100 5 Elements of Engineering Graphics 100
6 Engineering Physics Laboratory 100 6 Engineering Chemistry Laboratory 100
7 Computer Concepts & C Programming Laboratory 100 7 Workshop Practice 100
8 Personality Development & Communication 100 8 Principles of Environmental Studies 100
  Total Marks 800   Total Marks 800
SEMESTER 3 SEMESTER 4
1 Statistics and Probability – I 100 1 Statistics and Probability – II 100
2 Introduction to Data Science 100 2 Linear Algebra 100
3 Data Structures and Algorithms 100 3 Exploratory Data Analysis 100
4 Database Management Systems 100 4 NoSQL Data bases 100
5 Object Oriented Programming using Java 100 5 R Programming Language 100
6 Database Management Systems Laboratory 100 6 R Programming Language Laboratory 100
7 Data Structures and Algorithms Laboratory 100 7 NoSQL Database Laboratory 100
8 Object Oriented Programming using Java Laboratory 100 8 Object Oriented Programming using Java – Laboratory 100
    800     800
           
SEMESTER 5 SEMESTER 6
1 Inferential Statistics 100 1 Machine Learning – II 100
2 Machine Learning – I 100 2 Big Data Analytics – II 100
3 Big data Analytics – I 100 3 Elective – 3 100
4 Python Programming for Data Science 100 4 Elective – 4 100
5 Elective – 1 100 5 Dimension Reduction Techniques 100
6 Elective – 2 100 6 Artificial Neural Network 100
7 Machine Learning – I Laboratory 100 7 Machine Learning – II Laboratory 100
8 Big data Analytics – I Laboratory 100 8 Big Data Analytics – II Laboratory 100
  Total Marks 800   Total Marks 800
SEMESTER 7 SEMESTER 8
1 Visualization Techniques 100 1 Optimization Techniques 100
2 Natural Language Processing 100 2 Design of Experiments 100
3 Model Validation Techniques 100 3 Internship review* 100
4 Security and Privacy for Data Science 100 4 Project work 100
5 Elective – 5 100 5 Technical seminar 100
6 Elective – 6 100      
7 Model Validation Techniques Laboratory 100      
8 Visualization Techniques Laboratory 100      
  Total Marks 800   Total Marks 800

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