Data Analyst in Python, Tableau, SQL & ChatGPT with Projects

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Download Course Files Here

Chapter 2: Getting Started with Data Analysis in Python

Lecture 1: Download Anaconda

Lecture 2: Introduction to Jupyter Notebook

Lecture 3: Import Pandas and Matplotlib

Lecture 4: Loading CSV Files into Jupyter Notebook

Lecture 5: Markdown and Commenting Out Code

Lecture 6: Introducing Our Datasets

Lecture 7: Essential Python Methods to Understand Datasets

Lecture 8: Renaming Columns in Pandas

Lecture 9: Selecting Specific Columns

Lecture 10: Performing Basic Calculations

Lecture 11: Understanding Standard Deviation and Count

Lecture 12: Descriptive Statistics with the Describe Method

Lecture 13: Analyzing Frequency with Value Counts

Chapter 3: Python – Indexes, Sorting Data, and Introduction to Plotting

Lecture 1: Working with Indexes in Pandas

Lecture 2: Sorting Values in DataFrames

Lecture 3: Accessing Data with Loc and Iloc

Lecture 4: Advanced Indexing: Multi-Indexes and Slices

Lecture 5: From DataFrames to Plots

Chapter 4: Data Cleaning and Filtering Techniques in Pandas using Python

Lecture 1: Handling Missing Values: Dealing with NULLs

Lecture 2: Unique and Nunique Methods

Lecture 3: Filtering Data with the Between Method

Lecture 4: Applying Multiple Filter Conditions

Lecture 5: Advanced Filtering with Isin and Or

Lecture 6: Understanding the Tilde (~) Operator for Bitwise Negation

Lecture 7: Creating and Dropping Columns in DataFrames

Lecture 8: Generating Dynamic Columns

Chapter 5: Date Handling, Grouping and Reshaping Data in Pandas using Python

Lecture 1: Working with Dates: Converting to Datetime

Lecture 2: Replacing Values in a DataFrame

Lecture 3: Type Conversion using astype

Lecture 4: Extracting Date Components with .dt

Lecture 5: Grouping Data using Groupby

Lecture 6: Aggregation with .agg Method

Lecture 7: Reshaping DataFrames with Stack and Unstack

Chapter 6: Visualizing Data with Matplotlib using Python

Lecture 1: Introduction to Matplotlib

Lecture 2: Creating Bar Plots and Adding Annotations

Lecture 3: Visualize Data Distribution with Histograms

Lecture 4: Display Data with Pie Charts

Lecture 5: Explore Relationships with Scatter Plots

Lecture 6: Scatter Plots using World Happiness Dataset

Lecture 7: Visualize Trends with Line Plots

Lecture 8: Structuring Visualizations with Figures

Lecture 9: Organize Plots using Subplot

Lecture 10: Visualizing Sales Data – Part One

Lecture 11: Visualizing Sales Data – Part Two

Lecture 12: Formatting Sales Plots – Part One

Lecture 13: Formatting Sales Plots – Part Two

Chapter 7: Python Project – LA Crime

Lecture 1: Getting Dataset and Importing to Jupyter Notebook

Lecture 2: Understand and Prepare Data – Part One

Lecture 3: Understand and Prepare Data – Part Two

Lecture 4: Feature Understanding & Analysis – Part One

Lecture 5: Feature Understanding & Analysis – Part Two

Lecture 6: Feature Understanding & Analysis – Part Three

Lecture 7: Time Taken to Report Crime

Lecture 8: Average Victim Age per Crime

Lecture 9: Areas with Most Crime

Lecture 10: Crime Count by Time of Day

Chapter 8: SQL

Lecture 1: Downloading MySQL Workbench for Windows

Lecture 2: Downloading MySQL Workbench for Mac

Lecture 3: Introduction to MySQL Workbench

Lecture 4: What is SQL and Data Definition Language (DDL)

Lecture 5: Introduction to SQL: Insert Into Statements

Lecture 6: Importing our Databases

Lecture 7: Understanding the Data in the Database

Lecture 8: Select Data from the Database

Lecture 9: Filtering the Output with Where

Lecture 10: Applying Multiple Filters with In and Not In

Lecture 11: Finding Unique Values using Distinct

Lecture 12: Searching for Text Patterns in Strings using the Like Operator

Lecture 13: An Introduction to Joins

Lecture 14: Combining Tables using Inner Join

Lecture 15: Combining Tables using Left Join

Lecture 16: Combining Tables using Right Join

Lecture 17: Joining a Table to Itself

Lecture 18: Examples and Use Cases of Joins

Lecture 19: Combining Data with Union and Union All

Lecture 20: Introduction to Aggregate Functions

Lecture 21: Grouping Aggregated Data using Group By

Lecture 22: Using Subqueries in SQL

Lecture 23: Practice and Use Cases of Sub Queries

Lecture 24: Grouping Data using a Case Statement

Lecture 25: Transform Data using a Case Statement