Unleash Your Potential: Discover Opportunities in Data Science

Data science is the field of discovery, interpretation, and communication of meaningful patterns in data. At the heart of this dynamic and exciting field is the data scientist, armed with an arsenal of scientific methods, algorithms, and systems to extract valuable insights from both structured and unstructured data. Whether you're looking to become a data analyst, data engineer, data architect, business analyst, or machine learning expert, the possibilities for a fulfilling and rewarding career in data science are virtually endless. Join the ranks of the data science elite and start making a real impact in your organization today!


2 Months

Learning Options:


Course Fee

₦200,000 NGN


Computing & Math knowledge

Next Start Date

1st July 2024


AfriHUB Data Scientist

Course Outline

Introduction to Data Science and Tools

This module provides an introduction to data science and essential tools, including Python, Pandas, Scikit-learn, NumPy, Keras, and more. Participants will gain a foundational understanding of the tools required for data analysis and modeling..

Statistics and Data Visualization

This module combines statistics and data visualization. It covers statistical topics such as sampling, probability distributions, descriptive statistics, correlation, and hypothesis testing. Participants will also learn how to create captivating data visualizations using Seaborn, Matplotlib, and Plotly.

Dashboard Design and Practical Application

This module focuses on designing interactive dashboards using Google Data Studio or Microsoft PowerBI. Participants will apply their skills by working on real-world data analysis and statistical case studies.

Machine Learning and Predictive Modeling

In this module, participants delve into machine learning theory, covering regression, decision trees, random forests, K-nearest neighbors, support vector machines, and more. They will learn how to build and evaluate predictive models.

Data Science in Specific Domains

This module explores data science applications in marketing and retail. It covers modeling engagement rates, A/B testing in marketing, and customer segmentation, lifetime value, and product analytics in retail.

Big Data and PySpark

This module addresses big data challenges, including Hadoop, MapReduce, Spark, and PySpark. Participants will learn about RDDs, data transformations, actions, and machine learning with PySpark (MLlib). Data cleaning and manipulation at scale are also covered.