Bachelor of Science in Data Science & Analytics
- Entry Requirements
- 2 Principal passes, [One of the passes should be (MATHS or PHYSICS)]
- OR A diploma in ICT-related field, or Statistics
- OR a Higher Education Certificate (HEC)
Overview
We equip you with industry-relevant skills for employment in many sectors, including banking, healthcare, transportation, finance, marketing, eGovernment, cybersecurity, architecture & urban planning, and mechanical & civil engineering.
You have the option to specialize in Artificial Intelligence, Machine Learning, Data Engineering, Data Visualization, Business Intelligence, Financial Analytics, and more.
In this era of digital transformation, organizations realize the value and importance of making the right decisions at the right time, which can only be made through relying on the relevant and timely availability of data and information that are processed as part of the decision-making process.
In the era of digital transformation, organizations realize the value and importance of making the right decisions at the right time, which can only be made through relying on the relevant and timely availability of data and information that are processed as part of the decision-making process
Data science is an interdisciplinary academic field that uses statistics, scientific computing, scientific methods, processes, algorithms and systems to extract or extrapolate knowledge and insights from noisy, structured, and unstructured data.
Data science offers several advantages as a career choice. Firstly, it has a high demand across industries, including finance, healthcare, e-commerce, and technology.
Admission Requirement
- A Uganda Certificate of Education (UCE) or an equivalent qualification, AND;
- A Uganda Advanced Certificate of Education (UACE) with at least two principal passes obtained at the same sitting or its equivalent. One of the principal passes must be in either physics or mathematics or economics.
- A Higher Education Certificate of at least second class (Upper Division) with either Mathematics or Physics as the major subjects
- The applicant should hold a diploma of atleast second class-lower division in any field related to Science, Technology Engineering, and Mathematics (STEM).
- The Department of Computing and Technology reserves the right to determine course equivalence between the applicant’s Diploma program and the UCU BSDS curriculum. The department may waive the equivalent courses passed by the applicant and determine the level the applicant can join the BSDS program.
- Candidates for the Mature Age/Special Entry scheme must be Ugandan nationals of at least 22 years and have had formal education.
- Those who are successful in both the written and the oral examination are then considered for admission.
- In the case of international applicants, their academic documents have to be assessed by UNEB to evaluate their qualifications and rating against the Ugandan system. This will then be checked against the other entry requirements before being considered for admission.
In the event that an applicant is seeking to transfer accumulated credits from a program in a Ugandan university or any international partner university with which a bilateral partnership agreement exists, the departmental of Computing and Technology shall assess their qualifications (credits) against the UCU system to ascertain their possible level of entry before consideration for admission. Applicants for credit transfer from other Universities into the BSIT program shall fulfill the following conditions:
- Shall fulfill all the requirements for direct entry to the BSDS program, and;
- The originating University MUST be recognized by the Ugandan National Council of Higher Education (NCHE).
- The Department of Computing and Technology reserves the right to determine course equivalence between the applicant’s program of origin and the UCU BSDS curriculum. The department may waive the equivalent courses passed by the applicant and determine the level the applicant can join the BSDS program.
Tuition fees
The 2023 tuition fees for the BSc in Data Science and Analytics are UGX 2,345,000 for Ugandan applicants and UGX 3,517,000 for international applicants. Note: The stated fees are provisional to help you plan accordingly. The actual fees for the application year will be stated in your admission letter.
Course Curriculum
Semester 1
| Code | Course Name | Type | CU |
|---|---|---|---|
| CSC1101 | Structured Programming (Python) | C | 4 |
| MTH1102 | Probability and Statistics | C | 3 |
| ICT1102 | Essential Hardware and Software concepts | C | 4 |
| ICT1103 | Fundamentals of Computing | C | 4 |
| LNG1101 | Writing and Study Skills | C | 3 |
| TBS1103 | Understanding the Old Testament | C | 3 |
Semester 2
| Code | Course Name | Type | CU |
|---|---|---|---|
| DSC1201 | Introduction to Data Science | C | 3 |
| MTH1202 | Discrete Mathematics | C | 3 |
| CSC1203 | Data Structures and Algorithms (Python) | C | 4 |
| ICT1205 | Database Design and Applications | C | 4 |
| ICT1206 | Local Area Computer Networking | C | 3 |
| TBS1201 | Understanding the New Testament | C | 3 |
| PBH2108 | Health and Wholeness | C | 3 |
RECESS Semester 1
| Code | Course Name | Type | CU |
|---|---|---|---|
| DSC1302 | DS Field Attachment I – Workshop Practice | C | 3 |
Semester 1
| Code | Course Name | Type | CU |
|---|---|---|---|
| MTH2104 | Calculus | C | 3 |
| MTH2206 | Linear Algebra | C | 3 |
| CSC2105 | Object Oriented Programming | C | 4 |
| CSC2208 | Artificial Intelligence | E | 4 |
| DSC2104 | Big Data Analytics (R) & Technologies | C | 4 |
| DSC2107 | Data Mining and Wrangling | C | 4 |
| CSC2115 | Prompt Engineering | C | 3 |
Semester 2
| Code | Course Name | Type | CU |
|---|---|---|---|
| CSC2216 | Machine learning | C | 4 |
| CSC2209 | Big Data Databases & Data Storage | C | 4 |
| CSC2214 | Computational Research Methods | C | 3 |
| DSC2210 | Business Intelligence | C | 3 |
| DSC2206 | Time Series Analysis and Forecasting | C | 3 |
| SYE2201 | Data Engineering Principles/td> | C | 4 |
| DSC2205 | Data Visualization and Storytelling | E | 3 |
| CSC2210 | Fullstack Development (E) | E | 3 |
RECESS Semester 2
| Code | Course Name | Type | CU |
|---|---|---|---|
| DSC2302 | DS Field Attachment II – Internship | C | 3 |
Semester 1
| Code | Course Name | Type | CU |
|---|---|---|---|
| DSC3121 | DS Research project I | C | 3 |
| DSC3114 | Scientific writing and publishing | C | 3 |
| ENT3152 | Data Product Entrepreneurship & Strategy | C | 3 |
| TST2206 | Understanding Ethics from a Christian Perspective | C | 3 |
| Track 1 Electives (Artificial Intelligence & Machine Learning ) | |||
| MTH3207 | Optimisation Methods in Machine Learning | E | 3 |
| CSC3218 | Computer Vision & Deep learning | E | 3 |
| Track 2 Electives (Big Data & Cloud Engineering) | |||
| DSC3219 | Cloud and Distributed Computing | E | 3 |
| DSC3220 | Cloud Infrastructure & Deployment | E | 3 |
| Track 3 Electives (Business Intelligence & Financial Analytics) | |||
| DSC3206 | Econometric Analysis and Forecasting | E | 3 |
| DSC3207 | Machine Learning in Finance | E | 3 |
| Track 4 Electives (Computational Biology) | |||
| DSC3208 | Biological Modeling and Simulation | E | 3 |
| DSC3209 | Biostatistics | E | 3 |
Semester 2
| Code | Course Name | Type | CU |
|---|---|---|---|
| DSC3221 | DS Research project II | C | 3 |
| CSC3221 | Data Governance & Security | C | 4 |
| TST3108 | Understanding World Views | C | 3 |
| Track 1 Electives (Artificial Intelligence & Machine Learning ) | |||
| CSC3224 | Natural Language processing | E | 4 |
| CSC3225 | AI Model Deployment & Scalability | E | 4 |
| DSC3212 | Cognitive Computing | E | 3 |
| Track 2 Electives (Big Data & Cloud Engineering) | |||
| SYE3206 | Internet of Things & Edge Computing | E | 3 |
| DSC3220 | Advanced Data Engineering and Data Warehousing | E | 3 |
| CSC3221 | API and AI Agents Development | E | 3 |
| Track 3 Electives (Business Intelligence & Financial Analytics) | |||
| DSC3215 | Financial and Risk Analytics | E | 4 |
| DSC3216 | Operational & Health Analytics | E | 3 |
| DSC3217 | Data-driven Strategic Planning | E | 3 |
| Track 4 Electives (Computational Biology) | |||
| DSC3218 | Sequence Analysis | E | 3 |
| DSC3219 | Introduction to Bioinformatics | E | 3 |
| DSC3220 | Computational Genomics | E | 3 |
Career Prospects
The BSc Data Science and Analytics aims to provide a programme of study that combines, mathematics, statistics, and computer science especially machine learning and programming to find approaches to solve data analysis and analytics problems
How to Apply?
You can apply either online (recommended) or download and fill out application forms and submit them physically at any of our campuses in Kampala, Mukono, Kabale, Mbale or Arua.