B.Sc. Data Science

Course Details

B.Sc. Data Science is designed to provide an in-depth knowledge of big data techniques, and their applications for effective decision making in improving business processes.

B.Sc. Data Science is a three years graduate interdisciplinary course spread over six semesters. The programme curriculum has been designed with feedback from industry and academia. The main attraction of the programme is live projects during 3rd year in which students will explore their knowledge while working on real-world business problems.

B.Sc. Data Science

03 Years full time

2020-21 Entry

40 Seats

10+2 (Sci.) with 50% marks aggregates.
Math must be a subject in 10+2 Level

45,000

Tuition fee per semester**

Semester Lectures per Week Program  Credits Marks
1st Semester 26 24 700
2nd Semester 26 24 700
3rd Semester 28 26 750
4th Semester 28 26 750
5th Semester 28 24 700
6th Semester 32 24 750
Total Lectures per Week= 168 Program Credits – 148 4350

 

AEC- Ability Enhancement Compulsory, CC   Core Course, CCP –Core Course Practical, GE– Generic Elective, GEP– Generic Elective Practical, SEC– Skill Enhancement Course, SECP– Skill Enhancement Course Practical, DSE – Discipline Specific Elective, DSEP – Discipline Specific Elective Practical

Semester-I

Subject Code Subjects Name Subject Type Contact Hours per Week Credits Examination Scheme
  L P Total L P Total Internal Assessment Theory Prac Total

Marks

BDS101 Programming Fundamental & Data structure  using C CC-1 4 4 4 4 20 80 100
BDS102 Computer Fundamentals CC-2 4 4 4 4 20 80 100
BDS103 Environmental Science AEC-1 2 2 2 2 20 30 50
BDS104 Discrete Mathematical Structure GE-1 4 4 4 4 20 80 100
BDS105 Descriptive Statistics SEC-1 4 4 4 4 20 80 100
BDS106 Programming Fundamentals & Data Structure using C -LAB CCP-1 2X2 4 2 2 100 100
BDS107 Computer Fundamentals-LAB CCP-2 2X2 4 2 2 100 100
BDS108 Self-Study Paper 1 25 25
BDS109 Seminar 1 25 25
Total 18 8 26 18 4 24 150 350 200 700
Total Contact Hours per Week=26 Total Credits=24 Total Marks= 700

Semester-II

Subject Code Subjects Name Subject Type Contact Hours per Week Credits Examination Scheme
  L P Total L P Total Internal Assessment Theory Prac Total

Marks

BDS201 Object Oriented Programming with JAVA CC-3 4 4 4 4 20 80 100
BDS202 Introduction to Data Science CC-4 4 4 4 4 20 80 100
BDS203 English Communications AEC-2 2 2 2 2 20 30 50
BDS204 Applied Probability and Statistic GE-2 4 4 4 4 20 80 100
BDS205 Database Management System (DBMS) SEC-2 4 4 4 4 20 80 100
BDS206 Object Oriented Programming with JAVA- LAB CCP-3 2X2 4 2 2 100 100
BDS207 DBMS (SQL) LAB SECP-1 2X2 4 2 2 100 100
BDS208 Self-Study Paper 1 25 25
BDS209 Seminar 1 25 25
Total 18 8 26 18 4 24 150 350 200 700
Total Contact Hours per Week=26 Total Credits=24 Total Marks= 700

Semester-III

Subject Code Subjects Name Subject Type Contact Hours per Week Credits Examination Scheme
  L P Total L P Total Internal Assessment Theory Prac Total

Marks

BDS301 Optimization Techniques CC-5 4 4 4 4 20 80 100
BDS302 Programming in Python CC-6 4 4 4 4 20 80 100
BDS303 Applied Linear Algebra DSE-1 4 4 4 4 20 80 100
BDS304 Operating Systems GE-3 4 4 4 4 20 80 100
BDS305 Introduction to Data warehouse and Data Mining SEC-3 4 4 4 4 20 80 100
BDS306 Optimization Techniques (Python)- LAB CCP-4 2X2 4 2 2 100 100
BDS307 Applied Linear Algebra (Python)   -LAB DSEP-1 2X2 4 2 2 100 100
BDS308 Self-Study Paper 1 25 25
BDS309 Seminar 1 25 25
Total 20 8 28 20 4 26 150 400 200 750
Total Contact Hours per Week=28 Total Credits=26 Total Marks= 750

Semester-IV

Subject Code Subjects Name Subject Type Contact Hours per Week Credits Examination Scheme
  L P Total L P Total Internal Assessment Theory Prac Total

Marks

BDS401 Introduction to Data Analytic CC-7 4 4 4 4 20 80 100
BDS402 Introduction to Artificial Intelligence CC-8 4 4 4 4 20 80 100
BDS403 Internet Of Things (IoT) SEC-3 4 4 4 4 20 80 100
BDS404 Software Engineering GE-4 4 4 4 4 20 80 100
BDS405 Statistical Analysis DSE-2 4 4 4 4 20 80 100
BDS406 Introduction to Artificial Intelligence (PROLOG / Python) -LAB CCP-5 2X2 4 2 2 100 100
BDS407 Statistical Analysis and IoT (Python)- LAB SECP-2 2X2 4 2 2 100 100
BDS408 Self-Study Paper 1 25 25
BDS409 Seminar 1 25 25
Total 20 8 28 20 4 26 150 400 200 750
Total Contact Hours per Week=28 Total Credits=26 Total Marks= 750

Semester-V

Subject Code Subjects Name Subject Type Contact Hours per Week Credits Examination Scheme
  L P Total L P Total Internal Assessment Theory Prac Total

Marks

BDS501 Machine Learning -I CC-9 4 4 4 4 20 80 100
BDS502 Computer Vision CC-10 4 4 4 4 20 80 100
BDS503 IoT Programming and Big Data SEC-4 4 4 4 4 20 80 100
BDS504 Machine Learning -I   Lab GE-5 4 4 4 4 100 100
BDS505 IoT Programming and Big Data  LAB SECP-4 2X2 4 2 2 100 100
BDS506 Project Work –Minor (IoT/ Machine Learning) CCP-6 2X4 8 4 4 150 150
BDS507 Self-Study Paper 1 25 25
BDS508 Seminar 1 25 25
Total 16 12 28 16 6 24 110 240 350 700
Total Contact Hours per Week=28 Total Credits=24 Total Marks= 700

Semester-VI

Subject Code Subjects Name Subject Type Contact Hours per Week Credits Examination Scheme
  L P Total L P Total Internal Assessment Theory Prac Total

Marks

BDS601 Machine Learning -II (Deep Learning) CC-11 4 4 4 4 20 80 100
BDS602 Introduction to Natural Language Processing and Text Mining CC-12 4 4 4 4 20 80 100
BDS603 Cloud Computing DSE-3 4 4 4 4 20 80 100
BDS604 Machine Learning -II – LAB CCP-7 2X2 4 2 2 100 100
BDS605 Text Mining Lab-I- LAB CCP-8 2X2 4 2 2 100 100
BDS606 Project Work – Major SECP-4 2X6 12 6 6 200 200
BDS607 Self-Study Paper 1 25 25
BDS608 Seminar 1 25 25
Total 12 18 32 12 10 24 110 240 400 750
Total Contact Hours per Week=32 Total Credits=24 Total Marks= 750