PYTHON FOR DATA ANALYTICS

Overview

Course Description

Practical Python course focused on data analysis, not computer science. Covers Pandas for data manipulation, Matplotlib/Seaborn for visualization, and real-world analytics workflows. Uses GitHub Copilot to accelerate learning and productivity.

Prerequisites: Level 1 (or some programming background)

Career Relevance

Essential skill for modern analysts
Salary: Python-skilled analyst earns ₦3.5-5M annually
Next step: Machine Learning, Advanced Analytics, or Data Science specialization
Jobs: Data Analyst, Analytics Engineer, Data Science Associate

Module 1: Python Fundamentals & Jupyter
Python syntax and data types

Variables, functions, control flow

Jupyter notebooks and environment setup

Best practices for analytical code

Practice

Module 2: Data Manipulation with Pandas
Series and DataFrames

Indexing, slicing, and subsetting

Cleaning and transforming data

Merging and combining datasets

Grouping and aggregation

Practice

Module 3: Data Visualization
Matplotlib and Seaborn basics

Creating publication-quality plots

Interactive visualizations

Dashboard creation

Practice

Module 4: GitHub Copilot & AI-Assisted Coding
Using Copilot to generate code

Prompt engineering for data tasks

Testing and debugging with AI

Code efficiency and best practices

Practice

Module 5: Capstone & Portfolio
End-to-end analysis project

Capstone

Portfolio

Level:        Intermediate
Duration:     5 weeks
Physical Fee: ₦55,000
Virtual Fee:  ₦44,000

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PYTHON FOR DATA ANALYTICS

Course Description

Career Relevance

Certification Requirements

Vision Statement:

Mission Statement: