Data Science

Course Overview

This practical Data Science course teaches you how to extract actionable insights from real‑world data using Python, statistics, and machine learning. You will learn to clean, explore, and visualise data, build predictive models, and communicate findings effectively. The curriculum covers the entire data science workflow – from data wrangling with pandas and NumPy to creating interactive dashboards and deploying models. Both online and physical modes include live coding sessions and a final capstone project. By the end, you’ll be ready to solve business problems with data and pursue roles such as Data Analyst or Junior Data Scientist.

Duration

3 Month(s)

Availability

Online & Physical (both available)

Language

English

Training Days (Online)

Mon, Wed & Fri

Training Days (Physical)

Mon, Wed & Fri

Certification

Recognised Certificate on Completion

What You'll Achieve

Upon completing this course, you will be able to:
1. Clean, manipulate, and explore large datasets using Python (pandas, NumPy) and SQL.
2. Create compelling visualizations with Matplotlib, Seaborn, and Plotly to uncover hidden patterns.
3. Apply statistical analysis (hypothesis testing, regression) and build machine learning models (classification, clustering) using scikit‑learn.
4. Evaluate model performance and tune hyperparameters for real‑world accuracy.
5. Present data‑driven insights through interactive dashboards and professional reports.
6. Complete a capstone project that solves a realistic business problem – ready for your portfolio.

Prerequisites

1. Basic computer literacy (file management, using web browsers).
2. No coding experience required – the course starts from fundamental Python programming.
3. A logical mindset and interest in working with numbers and data.
4. Optional but helpful: familiarity with spreadsheets (Excel) or basic mathematics.