Bachelor of Science in Data Science & Analytics

Overview

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
DSC1101 Introduction to Data Science C 3
MTH1102 Discrete Mathematics C 3
CSC1101 Structured Programming C 4
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
CSC1203 Data Structures and algorithms C 4
CSC2210 Web Programming C 4
MTH1203 Probability and Statistics C 3
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 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
SYE2101 Software Design and Engineering C 3
TST2206 Understanding Ethics from a Christian Perspective C 3

Semester 2

Code Course Name Type CU
DSC2204 Big Data Analytics with R C 4
DSC2205 Data Visualization and Storytelling C 4
DSC2207 Data Mining and Wrangling C 4
MTH2207 Optimization Theory C 3
CSC2214 Computational Research Methods C 3
DSC2206 Time Series Analysis and Forecasting E 3
CSC3116 Machine learning E 4

RECESS Semester 2

Code Course Name Type CU
DSC2302 Internship C 3

Semester 1

Code Course Name Type CU
DSC3121 DS Research project I C 3
DSC3114 Scientific writing, reporting and publishing C 3
CSC3218 Deep learning E 4
CSC2209 Database Programming C 4
DSC3108 Big Data Mining and Analytics E 3
DSC3110 Business Intelligence E 3
DSC3112 Cognitive Computing E 3
DSC3113 Knowledge Engineering E 3
ICT3114 Biological Modeling and Simulation E 3
ICT3113 Biostatistics E 3

Semester 2

Code Course Name Type CU
DSC3221 DS Research project II C 3
CSC3221 Cyber Threat Intelligence and Data Security C 4
ENT3152 Advanced Topics and Technopreneurship C 3
TST3108 Understanding World Views C 3
DSC3215 Financial and Risk Analytics E 4
DSC3216 Operations-Related Data Analytics E 3
DSC3218 Text Analytics and Natural Language Processing E 3
SYE3206 Internet of Things E 3
DSC3220 Data Engineering and Data Warehousing E 3
DSC3219 Cloud and Distributed Computing E 3
DSC3217 Sequence Analysis E 3
ICT3219 Introduction to Bioinformatics E 3
ICT3218 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.