Dataquest is an online data learning portal that provides thousands of material and quizzes that can improve your data science skills like Python, R, SQL, Git, and more!

Learn by watching videos coding!

Most people learn best by doing, yet many data science courses only ask you to memorize information, never to apply it. We took a different approach:

In interactive lessons, you'll learn a new concept, write code to apply it, and get feedback all on the same screen.
In guided projects, you'll use the concepts you just learned to answer real-world questions on real datasets.
In a typical Dataquest session, you won't go more than five minutes without writing code!

Skill Paths

[🔍] [❌] SQL Fundamentals

Module Lists

[❌] [🔍] [❌] Fundamentals of SQL I
[❌] [🔍] [❌] Fundamentals of SQL II
[❌] [🔍] [❌] From Reports to Insights with SQL

[🔍] [📃] Python Basics for Data Analysis

Module Lists

[📂] [🔍] [📃] Python for Data Science: Fundamentals
[📂] [🔍] [📃] Python for Data Science: Intermediate

[🔍] [❌] R Basics for Data Analysis

Module Lists

[📂] [🔍] [📃] Introduction to Data Analysis in R
[📂] [🔍] [📃] Data Structures in R
[📂] [🔍] [📃] Control Flow, Iteration and Functions in R
[📂] [🔍] [📃] Specialized Data Processing in R: Strings and Dates

[🔍] [❌] Data Analysis and Visualization with Python

Module Lists

[📂] [🔍] [📃] Data Visualization Fundamentals
[📂] [🔍] [📃] Exploratory Data Visualization
[📂] [🔍] [📃] Storytelling Data Visualization and Information Design
[📂] [🔍] [📃] Data Cleaning and Analysis
[📂] [🔍] [📃] Data Cleaning in Python: Advanced
[📂] [🔍] [📃] Data Cleaning Project Walkthrough

[🔍] [📃] Data Visualization with R

Module Lists

[📂] [🔍] [📃] Data Visualization in R

[🔍] [📃] APIs and Web Scraping with Python

Module Lists

[📂] [🔍] [📃] APIs and Web Scraping in Python

[🔍] [❌] APIs and Web Scraping with R

Module Lists

[❌] [🔍] [❌] APIs in R

[🔍] [❌] Machine Learning Introduction with Python

Module Lists

[📂] [🔍] [📃] Machine Learning Fundamentals
[📂] [🔍] [📃] Calculus For Machine Learning
[📂] [🔍] [📃] Linear Algebra For Machine Learning
[📂] [🔍] [📃] Linear Regression For Machine Learning
[📂] [🔍] [📃] Machine Learning in Python: Intermediate
[📂] [🔍] [📃] Decision Trees

[🔍] [📃] Machine Learning Intermediate with Python

Module Lists

[📂] [🔍] [📃] Deep Learning Fundamentals
[📂] [🔍] [📃] Machine Learning Project
[📂] [🔍] [📃] Kaggle Fundamentals

[🔍] [📃] Probability and Statistics with Python

Module Lists

[📂] [🔍] [📃] Statistics Fundamentals
[📂] [🔍] [📃] Statistics Intermediate: Averages and Variability
[📂] [🔍] [📃] Probability: Fundamentals
[📂] [🔍] [📃] Conditional Probability
[📂] [🔍] [📃] Hypothesis Testing: Fundamentals

[🔍] [📃] Probability and Statistics with R

Module Lists

[📂] [🔍] [📃] Statistics Fundamentals in R
[📂] [🔍] [📃] Statistics Intermediate in R Averages and Variability
[📂] [🔍] [📃] Probability Fundamentals in R
[📂] [🔍] [📃] Conditional Probability in R
[📂] [🔍] [📃] Hypothesis Testing in R

Career Paths

[🔍] [📃] Data Analyst in Python

Material Lists

Step 1 - Introduction to Python

Module Lists

[📂] [🔍] [📃] Python for Data Science: Fundamentals
[📂] [🔍] [📃] Python for Data Science: Intermediate

Step 2 - Intermediate Python and Pandas

Module Lists

[📂] [🔍] [📃] Pandas and NumPy Fundamentals
[📂] [🔍] [📃] Exploratory Data Visualization
[📂] [🔍] [📃] Storytelling Through Data Visualization
[📂] [🔍] [📃] Data Cleaning and Analysis
[📂] [🔍] [📃] Data Cleaning in Python: Advanced
[📂] [🔍] [📃] Data Cleaning Project Walkthrough

Step 3 - The Command Line

Module Lists

[📂] [🔍] [📃] Elements of the Command Line
[📂] [🔍] [📃] Text Processing in the Command Line

Step 4 - Working with Data Sources

Module Lists

[📂] [🔍] [📃] SQL Fundamentals
[📂] [🔍] [📃] Intermediate SQL for Data Analysis
[📂] [🔍] [📃] APIs and Web Scraping in Python
[📂] [🔍] [📃] Data Analysis in Business

Step 5 - Probability and Statistics

Module Lists

[📂] [🔍] [📃] Statistics Fundamentals
[📂] [🔍] [📃] Statistics Intermediate: Averages and Variability
[📂] [🔍] [📃] Probability: Fundamentals
[📂] [🔍] [📃] Conditional Probability
[📂] [🔍] [📃] Hypothesis Testing: Fundamentals

Step 6 - Advanced Topics in Data Analysis

Module Lists

[📂] [🔍] [📃] Command Line: Intermediate
[📂] [🔍] [📃] Git and Version Control

[🔍] [📃] Data Scientist In Python

Material Lists

Step 1 - Python Introduction

Module Lists

[📂] [🔍] [📃] Python for Data Science: Fundamentals
[📂] [🔍] [📃] Python for Data Science: Intermediate

Step 2 - Data Analysis and Visualization

Module Lists

[📂] [🔍] [📃] Pandas and NumPy Fundamentals
[📂] [🔍] [📃] Exploratory Data Visualization
[📂] [🔍] [📃] Storytelling Through Data Visualization
[📂] [🔍] [📃] Data Cleaning and Analysis
[📂] [🔍] [📃] Data Cleaning in Python: Advanced
[📂] [🔍] [📃] Data Cleaning Project Walkthrough

Step 3 - The Command Line

Module Lists

[📂] [🔍] [📃] Elements of the Command Line
[📂] [🔍] [📃] Text Processing in the Command Line

Step 4 - Working with Data Sources

Module Lists

[📂] [🔍] [📃] SQL Fundamentals
[📂] [🔍] [📃] Intermediate SQL for Data Analysis
[📂] [🔍] [📃] APIs and Web Scraping in Python
[📂] [🔍] [📃] Data Analysis in Business

Step 5 - Probability and Statistics

Module Lists

[📂] [🔍] [📃] Statistics Fundamentals
[📂] [🔍] [📃] Statistics Intermediate: Averages and Variability
[📂] [🔍] [📃] Probability: Fundamentals
[📂] [🔍] [📃] Conditional Probability
[📂] [🔍] [📃] Hypothesis Testing: Fundamentals

Step 6 - Machine Learning Introduction

Module Lists

[📂] [🔍] [📃] Machine Learning Fundamentals
[📂] [🔍] [📃] Calculus For Machine Learning
[📂] [🔍] [📃] Linear Algebra For Machine Learning
[📂] [🔍] [📃] Linear Regression For Machine Learning
[📂] [🔍] [📃] Machine Learning in Python: Intermediate
[📂] [🔍] [📃] Decision Trees

Step 7 - Machine Learning Intermediate

Module Lists

[📂] [🔍] [📃] Deep Learning Fundamentals
[📂] [🔍] [📃] Machine Learning Project
[📂] [🔍] [📃] Kaggle Fundamentals

Step 8 - Advanced Topics in Data Science

Module Lists

[📂] [🔍] [📃] Functions: Advanced
[📂] [🔍] [📃] Command Line: Intermediate
[📂] [🔍] [📃] Git and Version Control
[📂] [🔍] [📃] Spark and Map-Reduce

[🔍] [❌] Data Engineer

Material Lists

Step 1 - Introduction to Python

Module Lists

[❌] [🔍] [❌] Python Fundamentals
[❌] [🔍] [❌] Python Intermediate
[❌] [🔍] [❌] Programming Concepts with Python

Step 2 - Introduction to Algorithms

Module Lists

[❌] [🔍] [❌] Algorithm Complexity

Step 3 - Working with Data Sources

Module Lists

[❌] [🔍] [📃] SQL Fundamentals
[❌] [🔍] [❌] Intermediate SQL

Step 4 - Production Databases

Module Lists

[❌] [🔍] [❌] Postgres for Data Engineers
[❌] [🔍] [❌] Optimizing Postgres Databases

Step 5 - Handling Large Data Sets in Python

Module Lists

[❌] [🔍] [❌] Numpy for Data Engineers
[❌] [🔍] [❌] Processing Large Datasets In Pandas
[❌] [🔍] [❌] Parallel Processing
[❌] [🔍] [❌] Data Structures Fundamentals
[❌] [🔍] [❌] Recursion and Trees

Step 6 - Data Pipelines

Module Lists

[❌] [🔍] [❌] Building a Data Pipeline

[🔍] [📃] Data Analyst in R

Material Lists

Step 1 - Introduction to R

Module Lists

[📂] [🔍] [📃] Introduction to Data Science with R
[📂] [🔍] [📃] Data Structures in R
[📂] [🔍] [📃] Control Flow, Iteration and Functions in R
[📂] [🔍] [📃] Specialized Data Processing in R Strings and Dates

Step 2 - Data Visualization in R

Module Lists

[📂] [🔍] [📃] Data Visualization in R

Step 3 - Data Cleaning in R

Module Lists

[📂] [🔍] [📃] Data Cleaning in R
[📂] [🔍] [📃] Data Cleaning in R Advanced

Step 4 - Working with Data Sources

Module Lists

[📂] [🔍] [📃] SQL Fundamentals
[📂] [🔍] [📃] Intermediate SQL in R

Step 5 - Probability and Statistics

Module Lists

[📂] [🔍] [📃] Statistics Fundamentals in R
[📂] [🔍] [📃] Statistics Intermediate in R Averages and Variability
[📂] [🔍] [📃] Probability Fundamentals in R
[📂] [🔍] [📃] Conditional Probability in R
[📂] [🔍] [📃] Hypothesis Testing in R

Step 6 - Predictive Modeling and Machine Learning in R

Module Lists

[📂] [🔍] [📃] Linear Regression Modeling in R
[📂] [🔍] [📃] Machine Learning Fundamentals in R

myarist / dataquest Goto Github PK

dataquest's Introduction

Learn by watching videos coding!

Skill Paths

[🔍] [❌] SQL Fundamentals

[🔍] [📃] Python Basics for Data Analysis

[🔍] [❌] R Basics for Data Analysis

[🔍] [❌] Data Analysis and Visualization with Python

[🔍] [📃] Data Visualization with R

[🔍] [📃] APIs and Web Scraping with Python

[🔍] [❌] APIs and Web Scraping with R

[🔍] [❌] Machine Learning Introduction with Python

[🔍] [📃] Machine Learning Intermediate with Python

[🔍] [📃] Probability and Statistics with Python

[🔍] [📃] Probability and Statistics with R

Career Paths

[🔍] [📃] Data Analyst in Python

Step 1 - Introduction to Python

Step 2 - Intermediate Python and Pandas

Step 3 - The Command Line

Step 4 - Working with Data Sources

Step 5 - Probability and Statistics

Step 6 - Advanced Topics in Data Analysis

[🔍] [📃] Data Scientist In Python

Step 1 - Python Introduction

Step 2 - Data Analysis and Visualization

Step 3 - The Command Line

Step 4 - Working with Data Sources

Step 5 - Probability and Statistics

Step 6 - Machine Learning Introduction

Step 7 - Machine Learning Intermediate

Step 8 - Advanced Topics in Data Science

[🔍] [❌] Data Engineer

Step 1 - Introduction to Python

Step 2 - Introduction to Algorithms

Step 3 - Working with Data Sources

Step 4 - Production Databases

Step 5 - Handling Large Data Sets in Python

Step 6 - Data Pipelines

[🔍] [📃] Data Analyst in R

Step 1 - Introduction to R

Step 2 - Data Visualization in R

Step 3 - Data Cleaning in R

Step 4 - Working with Data Sources

Step 5 - Probability and Statistics

Step 6 - Predictive Modeling and Machine Learning in R

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