Name: Data Analyst in Python, Tableau, SQL & ChatGPT with Projects
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Créé parGraeme Gordon

Dernière mise à jour : 05/2025

Anglais

Ce que vous apprendrez

Understand MySQL and it's role in data storage and analysis
Gain hands-on experience in using Python libraries such as Pandas and Matplotlib for data manipulation, cleaning, visualization, and data analysis
Learn how to effectively use ChatGPT as an assistant in writing code and analyzing data
Study the Tableau topics required for the Tableau Certified Data Analyst and Certified Desktop Specialist exams and prepare with hands on tutorials
Build your own interactive dashboard in Tableau
Engage in practical projects involving SQL, Python, ChatGPT, and Tableau, gaining hands-on experience in each technology.
Prepare yourself for an exciting career in Data Analytics

Exercices de codage

Ce cours comprend nos exercices de codage mis à jour afin que vous puissiez mettre en pratique vos compétences tout en apprenant.

Contenu du cours

20 sections • 199 sessions • 21 h 31 min de durée totale

Introduction2:21
Download Course Files Here0:29

Download Anaconda4:50
Learn how to download and install Anaconda, a popular distribution for Python and R, which includes Jupyter Notebook and essential packages for data science.
Introduction to Jupyter Notebook8:03
Get introduced to Jupyter Notebook, an interactive web application that allows you to create and share documents containing live code, equations, visualizations, and narrative text.
Import Pandas and Matplotlib3:53
Understand how to import essential Python libraries like Pandas and Matplotlib, which are fundamental for data manipulation and visualization.
Loading CSV Files into Jupyter Notebook9:32
Learn how to load CSV files into Jupyter Notebook, a crucial step for data analysis, and explore various methods for importing data.
Markdown and Commenting Out Code5:47
Discover the use of Markdown for formatting text and learn how to comment out code in Jupyter Notebook to enhance readability and documentation.
Introducing Our Datasets9:47
Get an overview of the datasets you will be working with, understanding their structure, and the type of data they contain.
Essential Python Methods to Understand Datasets8:14
Explore essential Python methods that help you understand and analyze your datasets, laying the foundation for effective data analysis.
Renaming Columns in Pandas8:38
Learn how to rename columns in Pandas DataFrames to make your data more readable and easier to work with.
Selecting Specific Columns8:03
Understand how to select specific columns in a DataFrame, allowing you to focus on the most relevant data for your analysis.
Performing Basic Calculations7:00
Perform basic calculations on your data, such as mean, max, min, and sum, to derive meaningful insights.
Understanding Standard Deviation and Count4:50
Learn about standard deviation and count, two important statistical measures, and how to compute them using Pandas.
Descriptive Statistics with the Describe Method7:07
Use the describe method in Pandas to generate descriptive statistics, summarizing the central tendency, dispersion, and shape of your dataset’s distribution.
Analyzing Frequency with Value Counts6:49
Analyze the frequency of unique values in your data using the value_counts method, helping you understand data distribution and identify patterns.
Pandas Part One Quiz

Working with Indexes in Pandas9:45
Discover how to work with indexes in Pandas DataFrames.
Sorting Values in DataFrames6:28
Learn how to sort values in DataFrames based on different criteria, enabling you to organize and analyze your data more effectively.
Accessing Data with Loc and Iloc6:22
Understand how to access specific data points in your DataFrames using loc and iloc.
Advanced Indexing: Multi-Indexes and Slices8:19
Explore advanced indexing techniques such as multi-indexes and slices, which allow for more complex data manipulations.
From DataFrames to Plots7:02
Transition from data manipulation to data visualization by learning how to create plots from DataFrames using Matplotlib.
Pandas Part Two Quiz

Introduction to Matplotlib5:16
Creating Bar Plots and Adding Annotations5:32
Visualize Data Distribution with Histograms8:00
Display Data with Pie Charts6:28
Explore Relationships with Scatter Plots7:29
Scatter Plots using World Happiness Dataset5:22
Visualize Trends with Line Plots6:00
Structuring Visualizations with Figures6:00
Organize Plots using Subplot5:54
Visualizing Sales Data - Part One8:59
Visualizing Sales Data - Part Two10:37
Formatting Sales Plots - Part One11:47
Formatting Sales Plots - Part Two5:49

Downloading MySQL Workbench for Windows5:06
Downloading MySQL Workbench for Mac5:30
Introduction to MySQL Workbench4:11
What is SQL and Data Definition Language (DDL)10:26
Introduction to SQL: Insert Into Statements6:32
Importing our Databases8:53
Understanding the Data in the Database10:56
Select Data from the Database6:01
Filtering the Output with Where7:57
Applying Multiple Filters with In and Not In6:41
Select From Where
Finding Unique Values using Distinct8:24
Searching for Text Patterns in Strings using the Like Operator7:37
Distinct and Like
An Introduction to Joins4:01
Combining Tables using Inner Join7:57
Combining Tables using Left Join9:22
Combining Tables using Right Join4:17
Joining a Table to Itself6:23
Examples and Use Cases of Joins7:11
Inner Join
Left Join
Combining Data with Union and Union All7:30
Introduction to Aggregate Functions6:18
Grouping Aggregated Data using Group By9:00
Aggregate Functions
Using Subqueries in SQL10:04
Practice and Use Cases of Sub Queries5:05
Grouping Data using a Case Statement8:45
Transform Data using a Case Statement5:50
Case Statement

Prérequis

No programming experience required. We will start from scratch.
A PC or laptop with internet connection capable of installing MySQL Workbench

Description

Are you interested in starting a career in data analytics but have no experience? Become proficient in essential tools such as Python, SQL, Tableau, and ChatGPT with this beginner data analyst course, designed to prepare you with the skills necessary to tackle real-world challenges as a data analyst. Whether you are looking for a career change to a data analyst, or have some experience and want to build on it, this step by step course will help guide you.

What You Will Learn:

Python for Data Analysis: Start from the basics and advance to complex data manipulations with Pandas and Matplotlib.
SQL: Learn to manage and query databases efficiently, from simple commands to complex queries.
ChatGPT for Productivity: Enhance your coding and analysis efficiency with optimized ChatGPT prompts.
Tableau for Visualization: Create impactful visualizations and prepare to become a Tableau Certified Data Analyst.
Hands-On Projects: This is a project-based data analyst course - from analyzing LA crime statistics to exploring sales trends, apply what you've learned in practical projects.

Why This Course?

Comprehensive & Practical: Gain hands-on experience with real-world projects that prepare you for the job market.
Accessible to Beginners: No prior experience? No problem! We cater to all skill levels.
Flexible Learning: Study at your pace with lifetime access to all course materials.

Who Should Enroll?

Aspiring data analysts, career switchers, and professionals aiming to upskill in data analysis and visualization.

If you're ready to start your journey in data analysis, enroll now and begin transforming data into insights!

À qui ce cours s'adresse-t-il ?

Anyone with an interest in Data Analysis
Students looking to learn and practice the topics required for the Tableau Certified Data Analyst exam
Students who want to get a head start in using AI tools such as ChatGPT as an assistant in analyzing data

Ce que vous apprendrez

Découvrir les sujets associés

Exercices de codage

Contenu du cours

Introduction2 sessions • 3 min

Getting Started with Data Analysis in Python13 sessions • 1 h 33 min

Python - Indexes, Sorting Data, and Introduction to Plotting5 sessions • 38 min

Data Cleaning and Filtering Techniques in Pandas using Python8 sessions • 43 min

Date Handling, Grouping and Reshaping Data in Pandas using Python7 sessions • 50 min

Visualizing Data with Matplotlib using Python13 sessions • 1 h 33 min

Python Project - LA Crime10 sessions • 1 h 7 min

SQL25 sessions • 3 h

SQL Project - Classic Models Analysis9 sessions • 54 min

ChatGPT - Introduction to Writing Better Prompts6 sessions • 28 min

Prérequis

Description

À qui ce cours s'adresse-t-il ?