BSc. Honours Degree in Data Science - Curriculum
Guidelines for Course Codes and Credits
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Each course code consists of four digits together with the prefix (alphabets).
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Prefix alphabets denote the abbreviation of the name of the degree program (DS).
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The first digit of each course code is the corresponding semester of study (1-8).
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The second digit represents the revision of the course, and it will increment if the course is revised.
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The third and fourth digit represents the course number.
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Example: The course code of DS1101 denotes the following.
|
Abbreviate Name of Degree Program |
Semester |
Revision Number |
Course Number |
|
DS (Data Science) |
1 |
1 |
01 |
Summary of the Courses
|
Semester I |
|||
|
DS1101 |
Introduction to Data Science |
1 |
Compulsory |
|
DS1102 |
Programming Fundamentals |
2 |
Compulsory |
|
DS1103 |
Calculus |
2 |
Compulsory |
|
DS1104 |
Introduction to Statistics |
2 |
Compulsory |
|
DS1105 |
Database Management Systems |
2 |
Compulsory |
|
DS1106 |
Computer System Organization |
2 |
Compulsory |
|
DS1107 |
Data and Society |
1 |
Compulsory |
|
DS1108 |
Web Programming I |
2 |
Compulsory |
|
DS1109 |
Communication Skills I |
- |
Compulsory (Non-GPA) |
|
DS1110 |
Academic Integrity |
- |
Compulsory (Non-GPA) |
|
DS-EGP-1101 |
General English I |
- |
Compulsory (Non-GPA) |
|
Total |
14 |
|
|
|
Semester II |
|||
|
DS2101 |
Operating Systems |
2 |
Compulsory |
|
DS2102 |
Data Structures |
2 |
Compulsory |
|
DS2103 |
Linear Algebra |
2 |
Compulsory |
|
DS2104 |
Object Oriented Programing |
2 |
Compulsory |
|
DS2105 |
Capstone Project in Data Science I |
2 |
Compulsory |
|
DS2106 |
Analysis of Algorithms |
2 |
Compulsory |
|
DS2107 |
System Analysis and Design |
2 |
Compulsory |
|
DS2108 |
Data Pre-Processing |
1 |
Compulsory |
|
DS2109 |
Communication Skills II |
- |
Compulsory (Non-GPA) |
|
DS-EGP-1201 |
General English II |
- |
Compulsory (Non-GPA) |
|
Total |
15 |
|
|
|
Semester III |
|||
|
DS3101 |
Probability Theory |
2 |
Compulsory |
|
DS3102 |
Regression Analysis |
2 |
Compulsory |
|
DS3103 |
Multivariate Calculus |
2 |
Compulsory |
|
DS3104 |
Real World Analytics |
1 |
Compulsory |
|
DS3105 |
Computer Networking |
2 |
Compulsory |
|
DS3106 |
Data Warehousing |
2 |
Compulsory |
|
DS3107 |
Web Programming II |
2 |
Compulsory |
|
DS-EAP-1201 |
Academic English I |
- |
Compulsory (Non-GPA) |
|
Total |
13 |
|
|
|
Semester IV |
|||
|
DS4101 |
Advanced Database Management Systems |
2 |
Compulsory |
|
DS4102 |
Scientific Writing & Documentation |
1 |
Compulsory |
|
DS4103 |
Software Engineering |
2 |
Compulsory |
|
DS4104 |
Data Visualization |
2 |
Compulsory |
|
DS4105 |
Capstone Project in Data Science II |
2 |
Compulsory |
|
DS4106 |
Applied Data Mining |
2 |
Compulsory |
|
DS4107 |
Social and Professional Issues in Computing |
2 |
Compulsory |
|
DS4108 |
Business Intelligence |
2 |
Compulsory |
|
DS4109 |
Discrete Mathematics |
2 |
Compulsory |
|
DS4110 |
Artificial Intelligence |
2 |
Compulsory |
|
DS-EAP-2201 |
Academic English II |
- |
Compulsory (Non-GPA) |
|
Total |
19 |
|
|
|
Semester V |
|||
|
DS5101 |
Semantic Web |
2 |
Compulsory |
|
DS5102 |
Time Series Analysis and Forecasting |
2 |
Compulsory |
|
DS5103 |
Information Security |
2 |
Compulsory |
|
DS5104 |
Machine Learning |
2 |
Compulsory |
|
DS5105 |
Linear Programming |
2 |
Compulsory |
|
DS5106 |
Graph Theory |
2 |
Compulsory |
|
DS-EBP-3101 |
Business English |
|
Compulsory(Non-GPA) |
|
Students should select courses covering 04 Credits from the following elective courses |
|||
|
DS5107 |
Image Processing |
2 |
Elective |
|
DS5108 |
Mobile Computing |
2 |
Elective |
|
DS5109 |
Data Science for Bioinformatics |
2 |
Elective |
|
DS5110 |
Human Resource Management |
2 |
Elective |
|
DS5111 |
Parallel and Distributed Computing |
2 |
Elective |
|
Total (Compulsory + Electives) |
16 |
|
|
|
Semester VI |
|||
|
DS6101 |
Introduction to Deep Learning |
1 |
Compulsory |
|
DS6102 |
Bayesian Learning and Graphical Models |
2 |
Compulsory |
|
DS6103 |
Mathematical Optimization |
2 |
Compulsory |
|
DS6104 |
Industrial Training |
6 |
Compulsory |
|
Students should select a course covering 02 Credits from the following elective courses |
|||
|
DS6105 |
Web Services |
2 |
Elective |
|
DS6106 |
Cloud Computing |
2 |
Elective |
|
DS6107 |
Business Process Management |
2 |
Elective |
|
DS6108 |
Software Quality Assurance |
2 |
Elective |
|
DS6109 |
Fraud and Anomaly Detection |
2 |
Elective |
|
Total (Compulsory + Electives) |
13 |
|
|
|
Semester VII |
|||
|
DS7101 |
Research Method |
2 |
Compulsory |
|
DS7102 |
Advanced Deep Learning |
2 |
Compulsory |
|
DS7103 |
Emerging Trends in Data Science |
1 |
Compulsory |
|
DS7104 |
Numerical Methods |
2 |
Compulsory |
|
DS7105 |
Natural Language Processing |
2 |
Compulsory |
|
Students should select courses covering 04 Credits from the following elective courses |
|||
|
DS7106 |
Entrepreneurship and Innovation |
2 |
Elective |
|
DS7107 |
Internet of Things |
2 |
Elective |
|
DS7108 |
Design Patterns and Anti-patterns |
2 |
Elective |
|
DS7109 |
Ontology Engineering |
2 |
Elective |
|
DS7110 |
Blockchain and Cryptocurrency |
2 |
Elective |
|
Total (Compulsory + Electives) |
13 |
|
|
|
Semester VIII |
|||
|
DS8101 |
Research Project in Data Science |
8 |
Compulsory |
|
DS8102 |
Information Retrieval and Web Analytics |
2 |
Compulsory |
|
DS8103 |
Reinforcement Learning |
2 |
Compulsory |
|
DS8104 |
Computational Intelligence |
2 |
Compulsory |
|
DS8105 |
Business Analytics and Applications |
1 |
Compulsory |
|
Students should select a courses covering 02 Credits from the following elective courses |
|||
|
DS8106 |
Geographical Information Systems |
2 |
Elective |
|
DS8107 |
Digital Forensics |
2 |
Elective |
|
DS8108 |
Business Process Simulation |
2 |
Elective |
|
DS8109 |
Robotics |
2 |
Elective |
|
Total (Compulsory + Electives) |
17 |
|
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