Complete Python Data Analysis & Visualization Bootcamp 2025

Learn data analysis and visualization from scratch using Pandas and Matplotlib – no prior experience needed!

What you'll learn

Master the essentials of Pandas to clean, filter, and analyze real-world datasets effectively for meaningful insights

Perform powerful, practical data analysis tasks for business analytics and intelligence

Visualize data using Matplotlib to clearly communicate patterns and trends in your data

Build hands-on projects that combine analysis and visualization to solve real problems with data

Requirements

Basic knowledge and experience with Python Fundamentals - Enroll my free Udemy course to build a foundation

Description

Are you curious about data analysis but not sure where to begin? This beginner-friendly course is designed just for you!Check out what students have said about my courses:I’ve been taking this Python course and I genuinely love it! The content is super well-structured, making even complex topics easy to understand. The instructor explains everything clearly and gives tons of real-world examples that help solidify what you're learning. The hands-on projects are one of my favorite parts—they’re fun, practical, and really boost your confidence as you go. Whether you’re totally new to coding or just want to sharpen your Python skills, this course hits the sweet spot. Highly recommend it to anyone looking to learn Python the right way!The Python programming course provides an exceptionally comprehensive learning experience, offering detailed insights into best practices and potential pitfalls. The curriculum is thoughtfully designed to be accessible to beginners, effectively introducing programming concepts without requiring prior coding expertise.The tutor made great explanations of each aspect of the course throughout. Courses like this will undoubtedly give beginners a solid foundation.The best course for beginners, very quick and easy to learn.The Complete Python Data Analysis & Visualization Bootcamp 2025 is your step-by-step guide to turning raw data into powerful insights using Python – one of the most in-demand programming languages today. In this course, you'll:Explore essential tools like Numpy, Pandas, and MatplotlibCreate meaningful visualizations using Matplotlib to tell stories with dataBuild confidence with hands-on exercises and projectsComplete a project to apply what you've learned and get a taste of solving real-world data problemsYou don’t need any prior experience in data science. We’ll walk you through everything at a gentle pace, making sure you build a strong foundation.If you are new to Python, no worries! I’ve got you covered. I recommend starting with my free Python Fundamentals course on Udemy, which is perfect for absolute beginners. Go to my homepage and find the fundamental course there.Whether you're a student, a working professional, or simply curious about data – this course is a great starting point to unlock new skills.Enroll today and start your journey into data analysis – one line of code at a time! Happy Coding!

Overview

Section 1: Introduction

Lecture 1 Introduction to Google Colab

Lecture 2 Google Colab AI Features

Lecture 3 Python Fundamental Refresher - Part 1

Lecture 4 Python Fundamental Refresher - Part 2

Lecture 5 Overall Workflow of Data Analysis

Section 2: Data Structure

Lecture 6 Numpy Array

Lecture 7 Pandas Series and DataFrame

Section 3: Pandas: Load and Access Data

Lecture 8 Load Data from Files

Lecture 9 Access Columns in a DataFrame

Lecture 10 Access Data in a DataFrame Using loc

Lecture 11 Access Data in a DataFrame Using iloc

Lecture 12 Access Data in a DataFrame Using at & iat

Section 4: Project [Part 1] : Online Retail Data - Load and Access Data

Lecture 13 Project Requirement

Lecture 14 Project Solution

Section 5: Pandas: Clean and Prepare Data for Analysis

Lecture 15 dropna to Drop Rows based on Missing Values

Lecture 16 dropna to Drop Columns based on Missing Values

Lecture 17 fillna to Replace Missing Values

Lecture 18 Identify Missing Values in a DataFrame

Lecture 19 Commonly Used Steps in Handling Missing Values

Lecture 20 Drop Invalid Records

Lecture 21 Update Column Values

Lecture 22 Add Columns

Lecture 23 Drop Duplicates

Lecture 24 Drop Columns

Lecture 25 Rename Columns

Lecture 26 Change Column Types

Lecture 27 Apply & Map Functions

Lecture 28 Save Clean Data to Files

Section 6: Project [Part 2] : Online Retail Data - Clean and Prepare Data

Lecture 29 Project Requirement

Lecture 30 Project Solution

Section 7: Pandas: Reshape and Transform Data for Analysis

Lecture 31 Sort Data

Lecture 32 Rank Data

Lecture 33 Filter Data

Lecture 34 Find Unique Values

Lecture 35 Groupby

Lecture 36 Pivot Table and Pivot

Lecture 37 Concatenate Multiple Files

Section 8: Project [Part 3] : Online Retail Data - Analyze Data

Lecture 38 Project Requirement

Lecture 39 Project Solution

Section 9: MatPlotLib: Visualize Data

Lecture 40 Approach 1 - Bar Chart

Lecture 41 Approach 1 - Line Chart

Lecture 42 Approach 1 - Pie Chart

Lecture 43 Approach 1 - Limitation

Lecture 44 Approach 2 - Line Chart

Lecture 45 Approach 2 - Bar Chart

Lecture 46 Approach 2 - Pie Chart

Lecture 47 Approach 2 - Scatter Chart

Lecture 48 Draw Multiple Charts in One Figure

Lecture 49 Save Chart as Images or Pdf

Section 10: Project [Part 4] : Online Retail Data - Visualize Data

Lecture 50 Project Requirement

Lecture 51 Project Solution - Part 1

Lecture 52 Project Solution - Part 2

Section 11: Next Step: Continue Your Journey

Lecture 53 More Resources

Aspiring data analysts looking to build a comprehensive skill set from scratch,Individuals looking to start a career in data analysis and gain a comprehensive skill set from the ground up,Students and recent graduates aiming to enhance their job prospects in the data science industry,Anyone with an interest in data, who wants to learn how to analyze, visualize, and make data-driven decisions, whether for professional development or personal projects