
R Programming for Data Science
Learn R for data analysis, statistical modelling, visualisation and data-driven decision-making using real-world datasets.
View courseMaster the complete data workflow with Excel, SQL, Python, SPSS, Power BI and Tableau. From raw data to analysis, visualisation and business insight.
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Level
Beginner to Advanced
Duration
10 weeks
Delivery
Physical & Live Online
Category
Data Science
Looking for a Data Science course in Lagos that actually takes you from beginner to job-ready? The Full-Stack Data Science programme at Corepoint Tech Academy is a 10-week, project-based course covering the entire modern data workflow — Excel, SQL, Python, SPSS, Power BI and Tableau — so you learn to work with data the way real analysts and data scientists do, not just watch tutorials. Whether you're a graduate starting out, a data analyst looking to add Python and machine learning to your toolkit, or a career changer in Nigeria aiming for a data science role, this course is built to get you from raw data to real, portfolio-ready insight.
A comprehensive, project-based Data Science programme designed to take learners from foundational data analysis to advanced data science workflows. Students work with industry-relevant tools including Microsoft Excel, SQL, Python, SPSS, Power BI and Tableau while developing practical skills in data cleaning, statistical analysis, exploratory data analysis, data visualisation, business intelligence and predictive analytics. Throughout the programme, learners work with real-world datasets and complete portfolio projects that demonstrate their ability to transform raw data into actionable insights.
Who it's for: Aspiring data scientists, data analysts, business intelligence professionals, graduates, researchers, business professionals and career changers who want comprehensive practical skills across the modern data analytics and data science ecosystem.

Learn R for data analysis, statistical modelling, visualisation and data-driven decision-making using real-world datasets.
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Use Python and statistics to analyse real-world data, discover meaningful patterns and support data-driven decisions.
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