Data Science (DS) is an interdisciplinary programme where it requires a variety of skills in the fields of Computer Science, statistics, and mathematics. This degree is focusing on applying the concepts required from each of these fields in the context of data. Data Science specialization aims at teaching individuals about data science principles and how to apply them to real world problems. This curriculum also pays significant attention to data analytics, statistical methods, mathematics, and Computer Science fundamentals.
Students who follow this degree programme will learn how to interact with data at all stages of an investigation and will be able to work within a team environment. Key competencies of such students are; Computational and statistical thinking, Mathematical foundations, Model building and assessment, algorithms and software foundation, data curation, and knowledge transference – communication and responsibility.
Data Science graduates have a variety of career opportunities, both nationally and internationally and upon completion of the degree, they will be qualified to work in Data Science roles that range from general to specialized. Possible career opportunities include but not limited to Data Scientist, Data Analyst, Data Science Consultant, Big Data Engineer, and Machine learning engineer. The depth and breadth of knowledge in this area of study are increasingly attractive to employers and would lead to careers not only as Data Scientist professionals but also in wider areas of the ICT industry.
Facilities
This department is located within the Faculty of Computer Science and Engineering where students will have access to:
Careers and Graduate Options
This challenging and highly demanding degree will enhance student’s ability to think analytically and solve complex problems using data. Some transferable skills you’ll develop on the course include:
The course equips students for a wide range of careers where analytical, computational, and data-driven skills are highly valued.
Some of our graduates take advantage of the specialist opportunities open to them. They secure employments in areas such as:
Other graduates choose careers in areas such as :
Teaching
Teaching is provided through lectures, practical, tutorials, seminars and small-group supervisions.
Assessment
Students will be assessed through written exams, practical tests and continuous assessments.
Year 01 Semester 01
| Module | Module Title | Credits |
| COM1301 | Introduction to Computer Systems | 3 |
| COM1302 | Computer Architecture | 3 |
| COM1303 | Fundamentals of Programming | 3 |
| COM1304 | Academic Practices and Grooming | 3 |
| DSC1301 | Discrete Mathematics and Graph Theory | 3 |
Year 01 Semester 02
| Module | Module Title | Credits |
| COM1306 | Data Structures and Algorithms | 3 |
| COM1307 | Object Oriented Programming | 3 |
| DSC1302 | Database Systems | 3 |
| COM1309 | Data Communication | 3 |
| DSC1303 | Linear Algebra and Vector Analysis | 3 |
Year 02 Semester 01
| Module | Module Title | Credits |
| DSC2301 | Introduction to Data Science | 3 |
| DSC2302 | Data Privacy and Security | 3 |
| COM2302 | Systems Analysis and Design | 3 |
| SEN2301 | Introduction to Software Engineering | 3 |
| DSC2303 | Calculus | 3 |
Year 02 Semester 02
| Module | Module Title | Credits |
| DSC2304 | Artificial Intelligence | 3 |
| DSC2305 | Operating Systems and System Administration | 3 |
| DSC2306 | Statistics for Data Science | 3 |
| DSC2307 | Data Acquisition and Management | 3 |
| DSC2308 | Cryptography and Information Theory | 3 |
| DSC2309 | Data Visualization | 3 |
| Career Planning and Employability Skills Development – Seminar |
Year 03 Semester 01
| Module | Module Title | Credits |
| COM3301 | Research Methods for Computing | 3 |
| DSC3301 | IT Professionalism and Practice | 3 |
| DSC3302 | Data Mining and Data Warehousing | 3 |
| DSC3303 | Introduction to Machine Learning | 3 |
| DSC3304 | Data Science Group Project | 3 |
| 01 Elective | ||
| DSC3306 | Business Analytics | 3 |
| DSC3307 | Business Intelligence | 3 |
| DSC3308 | Bioinformatics | 3 |
Year 03 Semester 02
| Module | Module Title | Credits |
| DSC3908 | Work Based Enterprise Placement | 9 |
Year 04 Semester 01
| Module | Module Title | Credits |
| COM4901 | Final Year Individual Project | 9 |
| DSC4301 | Big Data Systems | 3 |
| DSC4302 | Distributed Systems | 3 |
| DSC4303 | Introduction to Blockchain Technology | 3 |
| DSC4304 | Data Science Project Management | 3 |
| 01 Elective | ||
| COM4307 | Internet of Things
|
3 |
| DSC4311 | Web Technologies | 3 |
| COM3302 | Knowledge-based Systems | 3 |
| DSC4305 | Database Internals | 3 |
| AIN3302 | Introduction to Natural Language Processing | 3 |
Year 04 Semester 02
| Module | Module Title | Credits |
| DSC4306 | Advanced Machine Learning | 3 |
| DSC4307 | Data Modeling and Simulation | 3 |
| DSC4308 | Big Data Analytics | 3 |
| DSC4312 | Advanced Statistics | 3 |
| 01 Elective | ||
| AIN4302 | Information Retrieval | 3 |
| AIN4310 | Natural Computing | 3 |
| DSC4309 | Stochastic Modeling | 3 |
| MIS4307 | Entrepreneurship | 3 |
| DSC4310 | Compiler Theory | |
This challenging and highly demanding degree will enhance student’s ability to think analytically and solve complex problems using data. Some transferable skills you’ll develop on the course include:
· critical thinking and evaluation
· Statistical analysis and data interpretation
· communicating effectively and presenting findings clearly
· organization and time management
· working creatively and effectively with others
· research and independent problem-solving skills
The course equips students for a wide range of careers where analytical, computational, and data-driven skills are highly valued.
Some of our graduates take advantage of the specialist opportunities open to them. They secure employments in areas such as:
· data analysis and business intelligence
· Machine Learning and artificial intelligence research
· big data engineering and cloud-based analytics
· research and teaching in universities (following further study)
Other graduates choose careers in areas such as :
· finance, banking, and insurance
· government and civil service roles in data policy and analytics
· healthcare and biomedical data analysis
· industry and business decision support
· software and technology development
· consulting and project management
Duration : 04 years including 01 year industrial placement
Assessment criteria: Continuous assessment and final examination.
CA 40% + FE 60% = Z 100%
(CA = Continuous Assessment, FE = Final Examination, Z = Total Marks)
CA
10% Assignment 1
10% Assignment 2
20% Data Science case study in relevant area/domain
FE
60% Three-hour exam
Internship Opportunities : In ICT companies, In all other industries, in Consulting companies
