Bachelor of Science in Data Science & Analytics

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

  1. A Uganda Certificate of Education (UCE) or an equivalent qualification, AND;
  2. 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.
  3. A Higher Education Certificate of at least second class (Upper Division) with either Mathematics or Physics as the major subjects

 

  1. The applicant should hold a diploma of atleast second class-lower division in any field related to Science, Technology Engineering, and Mathematics (STEM).
  2. 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.
  1. Candidates for the Mature Age/Special Entry scheme must be Ugandan nationals of at least 22 years and have had formal education.
  2. Those who are successful in both the written and the oral examination are then considered for admission.
  3. 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:

  1. Shall fulfill all the requirements for direct entry to the BSDS program, and;
  2. The originating University MUST be recognized by the Ugandan National Council of Higher Education (NCHE).
  3. 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.