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Data Science

Statistical Analysis & Data Science with Python

Use Python and statistics to analyse real-world data, discover meaningful patterns and support data-driven decisions.

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Statistical Analysis & Data Science with Python

Level

Intermediate

Duration

6 weeks

Delivery

Physical & Live Online

Category

Data Science

Looking for a Python for Data Science course in Lagos with a strong statistics foundation? This 6-week intermediate programme at Corepoint Tech Academy teaches you to use Python and statistical methods together to analyse real data, uncover patterns, and support decisions with evidence — not just run code, but understand what the numbers mean.

Course overview

A practical, project-based programme designed to strengthen the statistical and analytical skills required for modern data science. Students learn how to work with real-world datasets using Python, perform exploratory data analysis, apply descriptive and inferential statistics, test hypotheses, analyse relationships between variables and communicate findings effectively. The course provides a strong foundation for advanced analytics and machine learning.

Who it's for: Data analysts, aspiring data scientists, researchers, business professionals, graduates and Python users who want to strengthen their statistical analysis and data science skills.

What you will learn

  • Understand the data science workflow from data collection to insight generation
  • Use Python to load, clean and analyse real-world datasets
  • Perform exploratory data analysis using Pandas and NumPy
  • Apply descriptive statistics to understand datasets
  • Understand probability and common probability distributions
  • Perform statistical hypothesis tests
  • Interpret p-values, confidence intervals and statistical significance
  • Analyse relationships between variables using correlation and regression
  • Identify patterns, trends, outliers and anomalies in datasets
  • Create effective statistical visualisations with Python
  • Communicate statistical findings to technical and non-technical audiences
  • Apply statistical techniques to real-world business problems
  • Build reproducible data analysis workflows using Python and Jupyter
  • Develop a portfolio-ready statistical data science project

Curriculum

Tools you'll use

PythonPandasNumPyMatplotlibSeabornSciPyStatsmodelsJupyter NotebookGit & GitHub

Projects you'll build

  • Customer Behaviour & Sales Analysis
  • Employee Performance & Workforce Analysis
  • Customer Satisfaction Statistical Analysis
  • Sales Forecasting & Trend Analysis
  • A/B Testing & Business Decision Analysis
  • End-to-End Statistical Data Science Capstone

Prerequisites

  • • Basic Python knowledge is recommended
  • • Basic understanding of spreadsheets is helpful
  • • Basic mathematics is recommended
  • • No previous statistics experience required

Frequently asked questions

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