School of Computing
BSc. Data Science
This programme is designed to prepare you for a career in the evergrowing field of technology, finance, health, marketing and many more. You will be wellequipped to pursue a successful career in data science, leveraging your skills and knowledge to extract insights from data, drive informed decisionmaking, and contribute to advancements in various industries and sectors.
ADMISSION OPTIONS
 100 Level Admissions
 Direct Entry Admissions
ADMISSION OPTIONS
 100 Level Admissions
 Direct Entry Admissions
Tuition Per Session
₦350,000
₦320,000
Tuition Per Semester
₦175,000
Introduction to Data Science
Start your bachelor’s degree in Data Science
Our Bachelor of Science in Data Science programme is designed to prepare you for a career in the dynamic and rapidly expanding field of data science. You will acquire a strong foundation in the principles and methodologies of data science, encompassing statistical analysis, machine learning, data visualisation, and data management.
Our programme is taught by experienced and knowledgeable faculty who are passionate about teaching data science. We offer a variety of resources to help you succeed, including a stateoftheart data science Lab, a career centre, research opportunities, data science library and resources and a variety of student organisations.
If you are interested in a career in data science, our Bachelor of Science in Data Science programme is the perfect choice for you. Apply today!
Why you should apply;
 Our programme is taught by experienced and knowledgeable faculty members who are passionate about teaching data science.
 We offer a variety of resources to help you succeed, including a stateoftheart computer lab, a career center, and a variety of student organizations.
 Our graduates are in high demand by employers in the tech industry.
 A degree in data science can lead to a variety of highpaying and rewarding careers.
Applications for May 2024 admission is ongoing.
Apply before 31st May 2024, to secure your place. Discount applies for full year’s payment.
Programme Summary
Study Level
Study Duration
8 Semesters
Mode of study
Blended Learning
Tuition per session
Tuition per semester
₦175,000
Curriculum
Programme Outline
Our curriculum is designed to provide students with the skills and knowledge they need to succeed in a variety of careers in the tech industry. The programme covers a wide range of topics, including programming, data structures, algorithms, operating systems, and artificial intelligence.
The faculty is available to students through forums, email, and phone calls. Students also have access to a variety of resources, including a stateoftheart elibrary, virtual computer labs, a career center, and a variety of student organisations.
1st Semester  Units 

Communication in English I  2 
At the end of this course, students should be able to:
 
Elementary Mathematics I – Algebra and Trigonometry  2 
At the end of this course, students should be able to:
 
General Physics I – Mechanics  2 
At the end of this course, students should be able to:
 
General Practical Physics I  1 
At the end of this course, students should be able to:
 
Use of Library, Study Skills and ICT  2 
At the end of this course, students should be able to:
 
Descriptive Statistics  3 
At the end of this course, students should be able to:
 
Introduction to Computing Sciences  3 
At the end of this course, students should be able to:
 
Environment and Sustainability (Elective)  2 
At the end of this course, students should be able to:
 
Contemporary Health Issues (Elective)  2 
At the end of this course, students should be able to:

2nd Semester  Units 

Introduction to Problem Solving  3 
At the end of this course, students should be able to:
 
Nigerian People and Culture  2 
At the end of this course, students should be able to:
 
Elementary Mathematics II – Calculus  2 
At the end of this course, students should be able to:
 
General Physics II – Electricity & Magnetism  2 
At the end of this course, students should be able to:
 
General Practical Physics II  1 
At the end of this course, students should be able to:
 
Introduction to Web Technologies  3 
At the end of this course, students should be able to:
 
Communication in English II  2 
At the end of this course, the student will be able to:

1st Semester  Units 

Entrepreneurship and Innovation  2 
At the end of this course, students should be able to:
 
Mathematical Methods I  2 
At the end of this course, students should be able to:
 
Computer Programming I  3 
At the end of this course, students should be able to:
 
Discrete Structures  2 
At the end of this course, students should be able to:
 
Introduction to Data Science  2 
At the end of this course, students should be able to:
 
Introduction to R Programming  2 
At the end of this course, students should be able to:
 
Set, Logic, and Algebra  2 
At the end of this course, students should be able to:
 
Introduction to Numerical Analysis  2 
At the end of this course, students should be able to:

2nd Semester  Units 

Philosophy, Logic and Human Existence  2 
At the end of this course, students should be able to:
 
Computer Programming II  3 
At the end of this course, students should be able to:
 
Computer Architecture and Organisation  — 
At the end of this course, students should be able to:
 
Statistical Computing Inference and Modelling II  3 
At the end of this course, students should be able to:
 
Linear Algebra I  2 
At the end of this course, students should be able to:
 
Data Engineering  2 
At the end of this course, students should be able to:
 
SIWES I  2 
At the end of this training, students should be able to:

1st Semester  Units 

Data Structures  3 
At the end of the course, students should be able to:
 
Introduction to Cybersecurity and Strategy  2 
At the end of this course, students should be able to:
 
Data Quality and Data Wrangling  3 
At the end of this course, students should be able to:
 
Introduction to Data Protection and IT Security  3 
At the end of this course, students should be able to:
 
Internet of Things  3 
At the end of this course, students should be able to:

2nd Semester  Units 

Peace and Conflict Resolution  2 
At the end of this course, students should be able to:
 
Venture Creation  2 
At the end of this course, students should be able to:
 
Big Data Computing  2 
At the end of this course, students should be able to:
 
Data Science Innovation and Entrepreneurship  2 
At the end of this course, students should be able to:
 
Ethics and Legal Issues in Data Science  2 
At the end of this course, students should be able to:
 
Machine Learning  2 
At the end of this course, students should be able to:
 
Cloud Computing  3 
At the end of this course, students should be able to:
 
Probability for Data Science  2 
At the end of this course, students should be able to:
 
Data Management I  3 
At the end of this course, students should be able to:
 
SIWES II  2 
At the end of this training, students should be able to:

1st Semester  Units 

Research Methodology and Technical Report Writing  3 
At the end of this course, students should be able to:
 
Algorithms and Complexity Analysis  2 
At the end of this course, students should be able to:
 
Project Management  2 
At the end of this course, students should be able to:
 
Final Year Project I  3 
At the end of this course, students should be able to:
 
Data Visualisation for Datadriven Decision Making  2 
At the end of this course, students should be able to:
 
Neural Nets and Deep Learning  3 
At the end of this course, students should be able to:

2nd Semester  Units 

Data Warehouses and Marts  2 
At the end of this course, students should be able to:
 
Business Intelligence  2 
At the end of this course, students should be able to:
 
Model Engineering  2 
At the end of this course, students should be able to:
 
Final Year Project II  3 
At the end of this course, students should be able to:
 
Operating Systems  3 
At the end of this course, students should be able to:
 
Time Series Analysis  2 
At the end of this course, students should be able to:

Admission Requirements
100 Level Entry requirements for BSc. in Data Science
Here’s what you need to study for a bachelor’s programme at Miva University
Direct Entry Candidates must meet ‘O’ Level requirements for the programme:
 English Language
 Mathematics
 Physics
 Chemistry
 Any other subjects
Please note that submission of Joint Admissions and Matriculation Board (JAMB) results is not mandatory at this stage. However, upon admission to the university, the provided results will be thoroughly verified for authenticity and compliance with the stated criteria, including JAMB Regularisation.
Direct Entry Admission Requirements for BSc. in Data Science
Here’s what you need to study for a bachelor’s programme at Miva Open University
Direct Entry Candidates must meet ‘O’ Level requirements for the programme:
 Two (2) 'A' Level passes in science subjects including Mathematics.
 NCE merit passes in Mathematics and one other Science subject.
 ND lower credit in Computer Science or other Mathematics/Computing/Physics/Electronics based programmes.
 Very good passes in three (3) JUPEB subjects: Physics, Mathematics, Chemistry or Biology.
 'A' Level passes chosen from English Language, Mathematics, Environmental Science, Biology, Chemistry, Physics, LiteratureinEnglish, Government, History, Economics, Geography, Further Mathematics, Technical Drawing, Visual Arts, Computer Studies, Information Technology, Civics, and French.
 International Baccalaureate (IB) Diploma in relevant subjects.
Careers
Potential roles for BSc. Data Science degree holders
Career Options
Learn on your terms with prerecorded engaging and interactive videos on your educational journey for flexible, convenient, and selfpaced study.
 Data Analyst
 Data Scientist
 Business Intelligence Analyst
 Data Consultant
 Data Engineer
 Healthcare Data Analyst
 Market Research Analyst
 Quantitative Analyst
 Data Visualization Specialist
 Machine Learning Engineer
Tuition
Payment Plans
Miva Open University offers a flexible payment plan for its degree programmes. You may choose to pay the year’s fee or per semester.
Tuition Per Semester
Pay Per Semester. No hidden charges. No additional costs.
₦175,000
Discount applies for full year’s payment.
Tuition Per Session
Pay Per Session. No hidden charges. No additional costs.