Python Data Analysis

What you'll learn

• Use NumPy for fast and efficient numerical calculations
• Work with arrays and perform operations on entire datasets
• Create charts and graphs using Matplotlib
• Visualize data with bar charts, line graphs, and pie charts
• Edit and manipulate images using Pillow (PIL)
• Apply filters, transformations, and text overlays to images
• Combine data analysis, visualization, and design into one project
• Build real-world data reports using Python

This course includes:

• 2 Data & Visualization Projects
• 6 Hours Live Classes (4 Sessions)
• Online / Onsite (Physical)
• Practice Datasets & Code Files
• Final Project (Class Data Report)
• Certificate of Completion

Course Content

Session 1 — NumPy: Working with Numbers Fast

Duration: 90 Minutes

Topics Covered:
• Installing NumPy
• Introduction to NumPy Arrays
• Array Creation and Operations
• Mathematical Functions: mean(), max(), min(), sum()
• Comparing NumPy vs Standard Python

Key Learning Objectives:
• Understand array-based computation
• Perform calculations efficiently
• Analyze datasets quickly
• Recognize real-world applications in science and AI

Activities:
• Create array of 10 test scores
• Calculate average, highest, lowest in one line
• Compare with traditional loop method
• Build class grade calculator using NumPy

Session 2 — Matplotlib: Charts & Graphs

Duration: 90 Minutes

Topics Covered:
• Installing Matplotlib
• Creating Bar Charts, Line Graphs, Pie Charts
• Adding Titles and Axis Labels
• Customizing Colors and Styles
• Data Visualization Basics

Key Learning Objectives:
• Present data visually
• Choose appropriate chart types
• Customize graphs for clarity
• Interpret visual data effectively

Activities:
• Collect class survey data
• Create bar chart (favourite subjects)
• Plot line graph (weekly temperature)
• Build pie chart (weekend activities)

Session 3 — Pillow: Image Editing with Code

Duration: 90 Minutes

Topics Covered:
• Installing Pillow (PIL)
• Opening and Displaying Images
• Image Transformations (Resize, Crop, Rotate, Flip)
• Applying Filters (Blur, Sharpen, Grayscale, Contour)
• Adding Text to Images
• Saving Edited Images

Key Learning Objectives:
• Understand image processing basics
• Manipulate images programmatically
• Apply creative effects
• Combine coding with digital design

Activities:
• Open and edit an image
• Apply grayscale and blur filters
• Resize image to half size
• Add name text overlay
• Save and compare before/after

Session 4 — Combined Mini Project: Class Data Report

Duration: 90 Minutes

Topics Covered:
• Integrating NumPy, Matplotlib, and Pillow
• Data Analysis Workflow
• Creating Visual Reports
• Presenting Findings

Key Learning Objectives:
• Combine multiple libraries in one project
• Analyze and visualize real data
• Create professional-looking outputs
• Develop presentation skills

Activities:
• Collect class survey data (10 questions)
• Analyze data using NumPy
• Create 3 charts using Matplotlib
• Design title/banner using Pillow
• Compile into a final report
• Present findings to class

Practice Projects for Real-World Skills

• Grade Analyzer (NumPy)
• Data Visualization Dashboard (Matplotlib)
• Image Editing Tool (Pillow)
• Final Project: Class Data Report

Requirements

• Completion of Python Intermediate Modules 1 & 2
• Understanding of Python basics (loops, functions, lists)
• Laptop/PC with Python installed
• Willingness to work with data and visuals

Description

This module introduces students to data science and creative computing using Python. Students will learn how to analyze numerical data, visualize insights through charts, and manipulate images programmatically.

By combining powerful libraries like NumPy, Matplotlib, and Pillow, learners will gain practical experience in handling real-world data and creating visually appealing outputs.

Why Choose This Course?

• Introduction to Data Science Concepts
• Hands-On Data Analysis & Visualization
• Combines Coding with Creativity
• Real-World Applications
• Builds Analytical Thinking Skills

Activities During Class

• Performing fast numerical calculations
• Creating charts and graphs
• Editing and transforming images
• Combining tools into real projects
• Presenting data insights

Who Is This Course For?

• Students who completed Python Intermediate Level
• Learners interested in data science
• Students who enjoy visual and creative coding
• Anyone curious about data and image processing

Course Highlights

• Multi-Library Learning Approach
• Real Data Projects
• Visual and Creative Outputs
• Interactive Sessions
• Certificate of Completion

Enroll Today!

Step into the world of data science and creative computing. Learn how to analyze, visualize, and present data using powerful Python tools and build projects that combine logic with creativity.