Learn Data Visualization & Analytics With Chatgpt And Colab

Turn data into insights with ChatGPT - create charts, analyze trends, and automate reporting using Google Colab & Python

What you'll learn

Beginners in data analysis who want to learn through hands-on practice without needing prior coding experience.

Marketing, product, or business professionals looking to turn raw data into visual insights using AI tools.

Students or career switchers who want to quickly build skills in Python, ChatGPT, and data storytelling

Anyone curious about how to automate data tasks and create clear, compelling visualizations using Google Colab and ChatGPT.

Requirements

You need to complete the “Beginner Guide to Data Visualization” lesson to learn the ADME method before taking this course

No prior coding experience is required - you’ll learn everything step by step.

A basic understanding of data (e.g. rows, columns, CSV files) is helpful but not necessary.

A free Google account to access Google Colab.

Optional: A free or Plus account on ChatGPT to use AI features during the course

Description

This beginner-friendly course teaches you how to analyze and visualize real-world datasets using ChatGPT and Google Colab. Whether you work in marketing, product, business analysis, or you’re simply data-curious, you’ll learn how to generate insights and communicate findings through clear, compelling visualizations.Using the ADME framework (Audience, Drawing, Message, Explanation), you’ll be guided step-by-step through interactive, hands-on projects. You’ll start by loading CSV files into Colab, explore the data with Python, and then use ChatGPT to assist in writing and interpreting code-even if you’ve never programmed before. With the help of AI, you’ll build insightful charts and segment customers based on behavior and spending patterns.What You’ll Learn:Work with real datasets directly in Google ColabUse ChatGPT to write, explain, and debug Python code-no experience neededCreate engaging charts like histograms, bar charts, scatter plots, and cluster mapsApply the ADME storytelling method to turn data into business-ready insightsAutomate your workflow to perform faster, repeatable analysisYou’ll also gain practical experience with tools used by analysts and data scientists every day, making it easier to bring data skills into your career. By the end of the course, you’ll confidently move from raw data to actionable decisions - using only your browser and smart prompts.No technical background? No problem. This course is designed to help you start fast, think critically, and work smarter with data.

Overview

Section 1: Introduction

Lecture 1 Course Overview & Target Audience

Lecture 2 What You'll Learn

Section 2: Setting Up Your Tools

Lecture 3 Introduction to Google Colab and ChatGPT

Lecture 4 Step-by-Step Setup Guide

Section 3: Understanding the Analysis Task

Lecture 5 Business Context & Problem Definition

Lecture 6 Dataset Overview & Key Questions

Section 4: Hands-on Data Exploration

Lecture 7 Loading and Inspecting Data

Lecture 8 Data Cleaning Essentials

Section 5: Visual Analysis with the ADME Method

Lecture 9 Basic Data Exploration (Describe & Summarize)

Lecture 10 Age Distribution Analysis

Lecture 11 Gender-based Purchase Analysis

Lecture 12 Age vs. Spending Patterns

Lecture 13 Identifying Customer Segments (KMeans)

Lecture 14 Creating Effective Summary Tables

Section 6: Communicating Your Insights Clearly

Lecture 15 How to Structure Your Findings (Using ADME)

Lecture 16 Effective Communication Tips for Marketing Teams

Section 7: Automating Your Workflow

Lecture 17 Automation Fundamentals

Lecture 18 Building an Automated Workflow (Flowchart & Examples)

Section 8: Course Wrap-up & Next Steps

Lecture 19 Course Summary and Review

Lecture 20 Continuing Your Data Journey (Resources & Next Steps)

This course is for beginners and non-coders who want to analyze data, create charts, and tell better stories using ChatGPT and Google Colab. It’s ideal for marketers, product managers, business analysts, students, and career changers looking to build practical data skills without writing complex code.