Data Science (B.Sc.)

College of Information and Communication Technology

Course Overview

In today’s data-driven world, businesses, governments, and institutions generate vast amounts of data every second. From predicting natural disasters and monitoring global health trends to improving customer engagement and driving artificial intelligence, the demand for professionals who can interpret and derive insights from data has skyrocketed. The B.Sc. Data Science programme is designed to develop graduates equipped with a comprehensive blend of technical and analytical skills across mathematics, statistics, computing, and information technology. With hands-on exposure to the data lifecycle—acquisition, cleaning, analysis, and visualization—students will graduate ready to lead in the data revolution.

The B.Sc. Data Science programme runs over four academic years and provides a rigorous foundation in both theory and practice. Students are introduced to core principles in computational thinking, mathematical modeling, statistical inference, and advanced programming. The programme integrates cross-disciplinary learning through real-world projects and problem-solving tasks, preparing students to handle data challenges across various industries. Instruction is delivered via classroom lectures, case studies, laboratory practicals, and industry-relevant simulations. Assessment includes quizzes, assignments, coding tasks, presentations, and exams, with continuous feedback and performance review to reinforce competency-based learning. Students gain experience with modern tools such as Python, R, SQL, and machine learning frameworks that ensure they graduate job-ready in a data-driven economy.

Course detail

AWARD TITLE

B.Sc.

START DATE

September 2025

DURATION

4 years

STUDY MODE

Full-time

CAMPUS

Nigeria, Lokoja

Teaching and Learning

The programme combines theoretical instruction with intensive practical applications that reflect real-world data science environments.

Teaching Methods include:

  • Instructor-led lectures and hands-on lab sessions

  • Individual and group-based data projects

  • Case studies and research workshops

  • Seminars and expert guest lectures

Assessment Methods include:

  • Written exams and coding challenges

  • Data analysis reports and model evaluations

  • Group project presentations

  • Continuous assessment through quizzes and assignments

  • Research-based capstone project in final year

Modules

  1. Introduction to Data Science: Provides an overview of data science concepts, tools, and applications, covering data collection, exploration, and visualization techniques.
  2. Statistical Methods and Inference: Covers probability theory, hypothesis testing, regression analysis, and their application to real-world data problems.
  3. Programming for Data Science: Introduces students to programming in Python and R, focusing on scripting, data manipulation, and automation.
  4. Machine Learning: Explores supervised and unsupervised learning algorithms, model training and evaluation, and real-world ML use cases.
  5. Big Data Technologies: Introduces tools and platforms for handling large-scale datasets, including Hadoop, Spark, and cloud-based data infrastructure.
  6. Artificial Intelligence: Focuses on core AI techniques such as neural networks, decision trees, and reinforcement learning, with applications in automation and robotics.
  7. Data Visualization and Storytelling: Trains students in presenting data insights using visual tools like Tableau, Matplotlib, and Power BI, emphasizing clarity and impact.
  8. Data Ethics and Governance: Examines ethical considerations, data privacy, responsible AI, and regulations like GDPR in managing sensitive data.
  9. Natural Language Processing (NLP): Covers techniques for analyzing and extracting information from text, including sentiment analysis, tokenization, and text classification.
  10. Capstone Project: A supervised final-year research or industry-based project that allows students to apply their full range of knowledge and skills to solve a complex data science problem.

Career

Graduates of the B.Sc. Data Science programme are equipped for high-impact roles in various sectors. Potential career paths include:

  • Data Scientist

  • Machine Learning Engineer

  • Data Analyst

  • AI Developer

  • Business Intelligence Analyst

  • Research Data Specialist

  • Data Engineer

  • Quantitative Analyst

  • Decision Scientist

  • Risk Modeller

Entry Requirements

Five (5) credit-level passes in SSCE/GCE/NECO/NABTEB,

Required subjects: English Language, Mathematics, and at least three subjects from Physics, Chemistry, Biology, Economics, or Geography.

Candidates applying for admission into 100 level undergraduate programmes must possess a minimum of five (5) ‘O’ level credit passes at not more than two (2) sittings in WASC, GCE, NECO or its equivalent. Awaiting result is also accepted.

  1. JAMB UTME result print-out.
  2. SSCE/NECO Result (Awaiting Result Accepted).
  3. Two Passport Photographs.
  4. A Letter of Sponsorship, stating the commitment to pay the prescribed fees.
  5. National Identification Number (NIN)
  6. A Reference Letter from a spiritual mentor, vouching for your character

Candidates applying for Direct Entry into 200 level must possess the following

  1. Jamb direct entry form
  2. A/L, IJMB, OND or NCE in the relevant courses.
  3. SSCE/NECO Result (Awaiting Result Accepted)
  4. Two Passport Photographs.
  5. A Letter of Sponsorship, stating the commitment to pay the prescribed fees.
  6. National Identification Number (NIN)
  7. A Reference Letter from a spiritual mentor, vouching for your character.

Fees and Funding

The course fees you’ll pay and the funding available to you depends on factors such as your nationality, location, personal circumstances and the course you are studying. Visit the links below to find the Undergraduate section.

 
More information

Find out about grants, bursaries, scholarships and living costs in our undergraduate taught fees and funding section.

Get Inspired

Our alumni are breaking boundaries and redefining success. Read their stories and get inspired to start your own journey.

Aisha Oiza Shaibu

  • B.Sc. (Hons.) Biochemistry
  • 2019

Nash Fom Joseph

  • BSc Accounting; MSc Accounting
  • 2022

Ogaji Emmanuel Victor

  • BSc (Hons) Accounting
  • 2019

Mary Funto Ogunkola

  • BSc (Hons) Accounting
  • 2019

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