Bachelor of Data Science
Programme overview
The Bachelor's program in Data Science represents a rigorous educational journey, thoughtfully designed to mold graduates into adept professionals equipped with essential technical and professional competencies essential for tackling the multifaceted challenges within the realm of data science. Participants will gain comprehensive knowledge and proficiency in substantial data analytics, data mining, computational intelligence, machine learning, statistical learning, scalable algorithms, and the optimization of expansive databases.
Expected outcomes
- Describe the applications of data science in a wide range of data-related fields.
- Analyse and adapt the latest data science technologies to solve real-world problems in a broad range of sectors.
- Formulate appropriate models of data analysis and undertake a project in an independent or collaborative environment.
- Exhibit an in-depth understanding of the codes of ethics and conduct of data science professions.
Entry requirements
A candidate must satisfy the general University admission criteria for undergraduate programmes.
- A mean grade of C+ and above at KCSE OR
- Diplomas or professional qualifications OR
- A certificate of foundation or bridging courses from recognised institutions OR
- A portfolio for the purpose of recognition of prior learning OR
- Kenya Advanced Certificate of Education with a minimum of 1 principal OR
- A bachelor’s degree from an institution recognised by Senate.
Programme structure
Definitions of Terms
- Credit hours: A credit hour is equivalent to a minimum of 15 Instructional hours;
- Lecture/Instructional hours: means a period of time equivalent to one hour and representing one such continuous hour in lecture form, two in a tutorial or open learning session, three in a laboratory practical or practicum and five in farm or similar practice;
- Contact hours: Is the duration designated for a lecture session; Course units: Course Content covered in one credit hour.
Upon successful completion of this program, students will have cultivated the following capabilities:
- Articulate comprehensive insights into the applications of data science across a diverse spectrum of data-centric domains.
- Apply advanced data science technologies adeptly to resolve intricate real- world challenges spanning multiple sectors.
- Formulate sophisticated data analysis models and undertake independent or collaborative projects with precision.
- Demonstrate a profound understanding of the ethical codes and professional conduct principles inherent to the field of data science.
Learning Outcomes
By the end of this programme, the student will be able to:
- Describe the applications of data science in a wide range of data-related fields.
- Analyse and adapt the latest data science technologies to solve real-world problems in a broad range of sectors.
- Formulate appropriate models of data analysis and undertake a project in an independent or collaborative environment
- Exhibit an in-depth understanding to the codes of ethics and conduct of data science professions.
Total credit hours and course units required for graduation
The programme shall be offered in 8 semesters. The minimum total courses for the programme are 48. The minimum total course credit hours required for graduation is 144 hours.
Progressive Certification
Progressive Certificate Award: successful completion of one third of total course credits and a capstone project.
Progressive Diploma Award: successful completion of two thirds of total course credits and attachment or field work.
Assessment methods
Student Assessment at programme level
The course will be assessed through:
- Content embedded quizzes
- Online practical work
- Open book tests
- Project reports
- End of course online examination
The projects will be assessed through e- portfolios. Students will present their work to an evaluation panel. All students’ work will be checked for plagiarism. The students should be logged in with the university provided login details in order to carry out any task.
Countinous Assessment
Tests/Tasks: 50%
Examination 50%
Global careers
Career Prospects in Data Science:
Graduates of this program can explore diverse and promising career trajectories, including but not limited to:
- Data Scientist
- Data Analyst
- Machine Learning Scientist
- Machine Learning Engineer
- Business Intelligence Scientist
- Market Research Analyst
Application hub
Typical duration
Delivery mode
Online
Accreditation info
Fully accredited by the Commission for University Education (CUE) and recognised globally for digital-first excellence.
School of Science & Technology
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Apply online in a few steps, or check the fees and talk to our admissions team about entry requirements and start dates.
Location
Nairobi, Kenya