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Professional Diploma in Data Science






I. About AUST

The African University of Science and Technology (AUST) is a private, Pan-African, co-educational, research university located in Abuja, Nigeria. The mission of AUST is to advance knowledge through applied research and offering structured instruction with a focus on Science, Technology, Engineering and Mathematics (STEM) and applications to policy, business, administration, management and development. AUSTInspire is the business and innovation arm of the University under which professional courses are hosted.


II. Program Description

With the rapid growth of data worldwide, industries and government organizations require professional skills to enable them understand gigantic data from multiple sources and derive valuable insight to make intelligent data-driven decisions efficiently. This brings the need to learn a technology that is widely used in various domains, including healthcare, marketing, banking, policy work, finance, and many more.
Data science is the domain study that deals with vast volumes of data using modern tools and techniques to find unseen patterns, derive meaningful information, and make accurate business decisions. It uses machine learning algorithms to build predictive models. Data scientists are in constant demand because we are in a data-heavy world. Africa needs these growing breeds of professionals that are highly in demand nowadays.
Considering the advantages and wide coverage of data science, AUST is willing to make use of all of its available resources and the group of its professionals across the globe to ensure rapid production of African data scientists who could apply the acknowledge acquired to solving our domestic and global problems for nations building.


III. Program Content

After successful completion of the program the participants will learn:

  • Working knowledge of data science ecosystem.
  • Python programming basics required for predictive analytics and machine learning, which will include working with libraries and frameworks like TensorFlow, NumPy, SciPy and Pandas.
  • How to perform classification using various machine learning techniques such as logistic regression, softmax regression, K-Nearest Neighbours (KNN), decision tree, Support Vector Machine, Naïve Bayes, Random Forest, etc.
  • Solving data problems when truth values are available.
  • Using unsupervised clustering methods to provide an explanation of data using various machine learning techniques such as Expectation Minimization (EM), divisive clustering, agglomerative clustering, etc.
  • Concept of machine learning and look at a large class of machine learning called regression.
  • Creating interactive Jupyter notebooks for predictive analytics.
  • Relational Database fundamentals including Database design, creating Schemas, Table, Constraints, and working with MySQL.
  • Challenges associated with “Big Data” and current state-of-the-art solutions.
  • Cloud computing using AWS.


IV. Software and Hardware Requirements

Every participant is expected to be able to operate a computer, and have a computer with or that allows installation of Microsoft Excel, Python (Jupyter), MySQL, and can connect to internet.


V. Expected Outcomes

As you may already know, about 90% of data currently in circulation is created in last five years, the growing demand of data scientist will keep rising all over the globe and in particular in African countries. We design this program such that upon completion of the program, practitioners will be able to:
• Effectively create an interactive Jupyter notebook use for forecasting
• Create a classification model of a type used in mortgage approval, bank loan approval and university admissions.
• Create, update, and query company’s or institution’s database. (These skills are vital for our ministries’, banks’ and healthcare system digital transformation)
• Use the companies’ or institutions’ data to creating an interactive machine learning Jupyter notebook that can be use many times to highlight the progress of the enterprise.
• Interact with modern data storage systems including the cloud-based solutions. (These are most have skills in the e-world we live now)
VI. Program Duration: July 29-September 17, 2022 (8 weeks, Fridays and Saturdays only)

VII. About the Facilitators


Dr. Basiru Usman is a Teaching Assistant Professor in Poole College of Management at North Carolina State University, Raleigh, NC, USA. He currently teaches Data Engineering, Management and Warehousing in MBA program. He gave a series of Pro Tips talk about using machine learning to implement personalized product recommendations, see here. He received his PhD in Applied Mathematics and MS in Data Science from Auburn University in 2020. His research interest includes Hopfield neural networks and anomaly detection. He has published articles in peer-reviewed journals such as journal of Nonlinearity, Communication in Pure and Applied Mathematics, etc.

Dr. Ismail Abdulrashid is an Assistant Professor of Data Analytics in the Collins College of Business at the Tulsa University (TU) where he teaches Analytics, including Enterprise Data Systems and Leading & Managing Data Analytics Organizations. Prior to joining TU, Ismail taught graduate and undergraduate courses in Data Mining, Introduction to Data & Programming in the Welch College of Business at Sacred Heart University. He received his PhD in Applied Mathematics and MS in Data Science from Auburn University in 2020. His research interests include data mining and optimization, with particular emphasis to application of artificial intelligence and machine learning in healthcare. He has published numerous research articles in journals and Peer-reviewed International Conferences such as Annals of Operations Research, International Workshop on Data Mining in Bioinformatics (BIOKDD), etc.

Dr. Mohammed Hassan is a Senior Lecturer in the Department of Software Engineering, Bayero University Kano, Nigeria. He teaches Artificial Intelligence, Machine Learning, Software Engineering, and Programming courses. He obtained his Doctorate degree from The University of Aizu, Japan in 2018. His research interests include the area of machine learning, recommendation systems, software engineering, and learning technology. He has published several research articles in conference proceedings and many reputable peer-reviewed international journals.

VIII. How To Apply

To apply for the program click here or visit

IX. Contact
+234 806 976 9952 (Dr. Usman Bello, AUST)
+234 818 608 3878 (Miss Ejemen Salami, AUST)
+234 906 066 0628 (Miss Blessing Nwonu, AUST)