# Dataquest > Interactive data science, data analytics, and data engineering courses with real datasets and projects. No-video, learn-by-doing curriculum used by 1M+ learners. Dataquest teaches Python, SQL, R, Tableau, Power BI, machine learning, and AI through in-browser coding exercises and guided projects. Career Paths take a beginner to job-ready in 3–9 months; Skill Paths target a specific topic; Individual Courses are standalone modules. Every path includes a free first course. ## Start here - [Homepage](https://www.dataquest.io/): What Dataquest is, who it's for, where to start. - [Catalog](https://www.dataquest.io/catalog/): Browse all paths and courses. - [Career Paths](https://www.dataquest.io/catalog/career-paths/): Career-track paths (Data Analyst, Data Scientist, Data Engineer). - [Skill Paths](https://www.dataquest.io/catalog/skill-paths/): Topic-focused paths (Python, SQL, ML). - [Individual Courses](https://www.dataquest.io/catalog/individual-courses/): Standalone courses outside the structured paths. - [Pricing](https://www.dataquest.io/subscribe/): Free tier + paid plans. - [For Business](https://www.dataquest.io/for-business/): Team plans for upskilling employees. - [Learner Stories](https://www.dataquest.io/learner-stories/): Career outcomes — interviews with graduates. ## Career Paths - [Junior Data Analyst](https://www.dataquest.io/path/junior-data-analyst/): Beginner · 97 hrs · You'll begin with Excel, where you'll learn how to manipulate data using complex formulas, commands, and tools. Next, you'll transition into SQL, becoming familiar with querying, exploring, and handling data from multiple sources. Lastly, you'll dive into Python, learning the fundamentals of programming, statistical analysis, and data visualization. This progressive learning journey is designed for both aspiring data professionals and those looking to enhance their data skills. Best of all, you'll learn by doing - you'll write code and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [Data Scientist in Python Certificate Program](https://www.dataquest.io/path/data-scientist/): Beginner · 171 hrs · In this path, you'll develop key technical skills for data scientists, including object-oriented and functional programming with Python, along with libraries like scikit-learn, Matplotlib, NumPy, and pandas. You'll also learn web scraping, SQL queries, deep learning, machine learning, and predictive analysis. To help you stand out, you'll explore tools like the UNIX command line, Git, and GitHub for better collaboration. Best of all, you'll learn by doing - you'll write code and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [Data Analyst in Python](https://www.dataquest.io/path/data-analyst/): Beginner · 144 hrs · In this path, you'll learn the fundamentals of Python, as well as how to prepare and extract data by querying databases with SQL, how to create insightful data visualization, and how to perform descriptive and predictive statistical analysis. Best of all, you'll learn by doing - you'll write code and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [AI Engineer in Python](https://www.dataquest.io/path/ai-engineer/): Beginner · 183 hrs · In this path, you'll build the technical skills AI engineers need, including Python programming, working with LLM APIs, and prompt engineering. You'll learn to build and deploy AI applications using FastAPI and Docker, then go deeper into machine learning, deep learning with PyTorch, embeddings, vector databases, and RAG systems. You'll also pick up essential tooling like the command line, Git, and virtual environments. Best of all, you'll learn by doing - you'll write code and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [Data Engineer](https://www.dataquest.io/path/data-engineer/): Beginner · 143 hrs · In this path, you'll master the mandatory technical skills for modern data engineering, including Python programming, distributed computing, containerization, and cloud deployment. You'll learn how to work with production databases like PostgreSQL, Snowflake, and MongoDB, process data at scale with PySpark, orchestrate workflows with Apache Airflow, and deploy containerized applications to cloud platforms using Docker and Kubernetes. Best of all, you'll learn by doing - you'll write code and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [Data Analyst in R](https://www.dataquest.io/path/data-analyst-r/): Beginner · 85 hrs · In this path, you'll learn the fundamentals of R and build upon them with more advanced skills. You'll learn how to use RStudio, applications and tools, tidyverse, DataFrames, tibbles, operators, expressions, and much more - as well as data visualization, graphs, plots, and charts. Best of all, you'll learn by doing - you'll write code and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [Business Analyst with Power BI](https://www.dataquest.io/path/business-analyst-with-power-bi/): Beginner · 51 hrs · You'll learn the fundamentals of data analysis in Excel, including how to explore and extract data from datasets using SQL, how to perform descriptive statistical analysis, and how to present insights using dashboards and visualizations in Power BI. Best of all, you'll learn by doing - you'll practice and get feedback directly in the browser. You'll apply your skills to several guided projects with realistic business scenarios to build your portfolio and prepare for your next interview. By the end of the career path, you'll be ready for the official Microsoft Power BI Data Analyst certification PL-300, an in-demand assessment that certifies your skills in Power BI. - [Business Analyst with Tableau](https://www.dataquest.io/path/business-analyst-with-tableau/): Beginner · 46 hrs · You'll learn the fundamentals of data analysis in Excel, including how to explore and extract data from datasets using SQL. You'll also learn how to build informative data visualizations using a variety of chart types, as well as how to present insights to audiences using Tableau. Best of all, you'll learn by doing - you'll practice and get feedback directly in the browser. You'll apply your skills to several guided projects with realistic business scenarios to build your portfolio and prepare for your next interview. By the end of the career path, you'll be ready for the official Tableau Desktop Specialist Certification, an in-demand assessment that certifies your skills in Tableau. ## Skill Paths - [Probability and Statistics with Python](https://www.dataquest.io/path/probability-and-statistics-with-python/): Beginner · 77 hrs · In this path, you'll learn the foundations of statistics such as sampling, working with variables, and understanding frequency distribution tables and the fundamentals of probability and how to use them for analysis. You'll also learn how to create and test hypotheses with significance testing, and how to make forecasts based on patterns and trends with real-world data. Best of all, you'll learn by doing - you'll write code and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [Data Cleaning with Python](https://www.dataquest.io/path/data-cleaning-python/): Beginner · 64 hrs · In this path, you'll gain the fundamental skills to begin cleaning data, using the powerful tools offered by Python such as identifying and removing inaccurate records from a dataset. You'll learn how to manipulate, analyze, and visualize data using premier Python libraries such as Pandas and Numpy. Best of all, you'll learn by doing - you'll write code and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [Data Analysis and Visualization with Python](https://www.dataquest.io/path/data-analysis-and-visualization-with-python/): Beginner · 47 hrs · In this path, you will gain experience in manipulating, comparing, and presenting compelling and actionable data and you'll discover the best methods for visualizing data using line graphs, histograms, bar charts, scatter plots, and more. Best of all, you'll learn by doing - you'll write code and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [Learn Python](https://www.dataquest.io/path/learn-python/): Beginner · 21 hrs · In this path, you'll explore the basics of Python programming from preparing data all the way to predicting trends from real-world data. You'll learn the fundamentals of Python, how to use Jupyter notebooks, work with numerical and text data and basic object-oriented programming. Best of all, you'll learn by doing - you'll write code and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [Data Literacy and Introduction to Data Analysis using Excel](https://www.dataquest.io/path/introduction-to-data-analysis-with-excel/): Beginner · 22 hrs · We designed this skill path for aspiring data professionals with little experience, and learners who use basic Excel in their daily jobs. You'll learn how to manipulate data using complex formulas, commands, and tools, such as macros, pivot tables, and advanced graphs. Best of all, you'll learn by doing - you'll write code and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [R Basics for Data Analysis](https://www.dataquest.io/path/r-basics-for-data-analysis/): Beginner · 15 hrs · In this path, you'll explore the basics of R and work through the entire data analysis workflow , learn how to use packages and why they are essential in any data analysis process, and how to repeat code efficiently with iterations. Best of all, you'll learn by doing - you'll write code and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [Learn SQL Skills for Data Analysis](https://www.dataquest.io/path/sql-skills/): Beginner · 21 hrs · In this path, you'll become familiar with SQL syntax and master the frequently used commands. You'll also learn how to use string patterns and ranges to query data, how to sort and group data, and how to write perfect queries to extract and analyze data from real SQL databases. Best of all, you'll learn by doing - you'll write code and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [APIs and Web Scraping with Python](https://www.dataquest.io/path/apis-and-web-scraping-with-python-skill-path/): Intermediate · 3 hrs · In this path, you'll learn how to use Python and Beautiful Soup to scrape the web and download data from APIs. If you've worked with Python and would like to add another powerful tool to your skill set, this is the perfect path for you. Best of all, you'll learn by doing - you'll write code and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [CLI and Git](https://www.dataquest.io/path/cli-git-skill/): Beginner · 11 hrs · In this path, you'll learn the command line and Git skills essential for data engineering. You'll go from basic shell navigation through advanced command line techniques and version control with Git, applying everything to practical, real-world data engineering workflows. - [Generative AI Fundamentals in Python](https://www.dataquest.io/path/generative-ai-fundamentals-skill-track/): Beginner · 32 hrs · Gain the skills necessary for working with AI, from automating tasks to engaging with LLMs via API in Python, and progress to building AI-driven applications. This path is essential for professionals aiming to integrate AI into their toolkit. - [Production Databases](https://www.dataquest.io/path/production-databases-skill/): Intermediate · 18 hrs · In this path, you'll learn how to work with the production database systems used in modern data engineering. You'll gain hands-on experience with PostgreSQL, Snowflake, and MongoDB through practical, real-world data engineering scenarios. - [Machine Learning Using Python](https://www.dataquest.io/path/machine-learning-in-python/): Intermediate · 25 hrs · In this path, you'll gain a strong understanding of supervised and unsupervised machine learning algorithms. You'll also learn some of the most important and used algorithms and techniques to build, customize, train, test and optimize your predictive models such as linear regression modeling, gradient descent, logistic regression modeling and decision tree and random forest modeling. Finally, you'll learn optimization techniques that will help you to improve efficiency and accuracy. Best of all, you'll learn by doing - you'll practice and get feedback directly in the browser. You'll apply your skills to several guided projects with realistic business scenarios to build your portfolio and prepare for your next interview. - [Data Pipelines with Airflow](https://www.dataquest.io/path/data-pipelines-airflow-skill/): Intermediate · 12 hrs · In this path, you'll learn how to build data pipelines in Python and orchestrate them with Apache Airflow. You'll go from foundational pipeline concepts to automating complex workflows through hands-on, real-world scenarios. - [LLM Fundamentals in Python](https://www.dataquest.io/path/llm-fundamentals-python-skill/): Intermediate · 17 hrs · Learn to work with large language models through APIs, prompt engineering, and advanced patterns like function calling and MCP. Then put your skills to work building interactive AI-powered web applications with Streamlit. - [Data Visualization with R](https://www.dataquest.io/path/data-visualization-with-r/): Intermediate · 4 hrs · In this path, you will gain experience in manipulating, comparing, and presenting compelling and actionable data and you'll discover the best methods for visualizing data using line graphs, histograms, bar charts, scatter plots, and more. You'll learn how to use R programming and ggplot2 to create meaningful data visualizations. Ggplot2, which is a part of tidyverse, is an R package for data visualization. It's one of the most versatile and easy-to-use tools for creating elegant graphics using R, and it's the main focus of this path. Best of all, you'll learn by doing - you'll write code and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [Analyzing Data with Microsoft Power BI](https://www.dataquest.io/path/analyzing-data-with-microsoft-power-bi-skill-path/): Beginner · 10 hrs · In this path, developed in collaboration with Microsoft, you'll learn how to use Microsoft Power BI to analyze, clean, explore, and visualize data. By completing the path, you'll be prepared to take the PL-300 exam. With this certification in hand, you'll let existing or future employers know that you carry Microsoft's stamp of approval when it comes to Power BI. Best of all, you'll learn by doing - you'll write code and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [Probability and Statistics with R](https://www.dataquest.io/path/probability-and-statistics-with-r/): Intermediate · 10 hrs · In this path, you'll learn the foundations of statistics such as sampling, working with variables, and understanding frequency distribution tables and the fundamentals of probability and how to use them for analysis. You'll also learn how to create and test hypotheses with significance testing, and how to make forecasts based on patterns and trends with real-world data. Best of all, you'll learn by doing - you'll write code and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [Zero to GPT](https://www.dataquest.io/path/zero-to-gpt-skill/): Intermediate · 0 hrs · This course stars with the fundamentals - neural network architectures and training methods. Later in the course, we'll explore complex topics like transformers, GPU programming, and distributed training. You'll need to understand Python to take this course, including for loops, functions, and classes. The first part of this Dataquest path will teach you what you need. To get the most out of this course, go through each chapter sequentially. Read the lessons or watch the optional videos - they have the same information. Look through the implementations to solidify your understanding, and recreate them on your own. - [Data Visualization with Tableau](https://www.dataquest.io/path/data-visualization-with-tableau/): Beginner · 12 hrs · In this path, you'll gain the Tableau foundation you need to prepare, explore, create, and analyze data visualizations. Not only will you learn the best practices and formatting techniques to create charts and interpret them in various business scenarios, but you'll also learn to build dashboards and master techniques to communicate your insights and tell a story. Best of all, you'll learn by doing - you'll practice and get feedback directly in the browser. We'll help you apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [Deep Learning in TensorFlow](https://www.dataquest.io/path/deep-learning-in-tensorflow-skill/): Intermediate · 23 hrs · On this path, you'll learn all about deep learning, including how to build, train, and evaluate models with the TensorFlow framework.  You'll then learn how to conduct forecasts on real data by applying sequential neural network models to time series forecasting.  Next, you'll learn how to use TensorFlow tools and libraries to work on a range of NLP use cases, including text visualization, sentiment analysis models, and more. Finally, you'll learn how to apply convolutional neural networks (CNNs) to computer vision tasks so that you can teach computers to see and interpret digital images. Best of all, you'll learn by doing - you'll practice and get feedback directly in the browser. You'll apply your skills to several guided projects with realistic business scenarios to build your portfolio and prepare for your next interview.  - [APIs and Web Scraping with R](https://www.dataquest.io/path/apis-and-web-scraping-with-r/): Intermediate · 4 hrs · In this path, you'll learn how to use application program interfaces (APIs) and powerful web scraping tools to create truly unique and targeted datasets. You'll also learn how to automate the process of putting unstructured data into an organized and understandable dataset. Best of all, you'll learn by doing - you'll write code and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [Distributed Data Processing with PySpark](https://www.dataquest.io/path/distributed-data-processing-pyspark-skill/): Intermediate · 9 hrs · In this path, you'll learn how to use PySpark and Apache Spark to process data at scale. You'll work with RDDs, DataFrames, and Spark SQL to build and optimize production ETL pipelines through hands-on, real-world data engineering scenarios. - [Containerization and Infrastructure with Docker and Kubernetes](https://www.dataquest.io/path/containerization-infrastructure-docker-kubernetes-skill/): Intermediate · 12 hrs · In this path, you'll learn how to use Docker and Kubernetes to containerize and orchestrate data engineering applications. You'll build reproducible environments, manage multi-service deployments, and prepare production-ready containerized systems through practical, real-world exercises. - [Introduction to Cloud Computing](https://www.dataquest.io/path/introduction-cloud-computing-skill/): Intermediate · 8 hrs · In this path, you'll learn the fundamentals of cloud computing and how to deploy data engineering systems to cloud platforms. You'll gain hands-on experience with cloud services through practical, real-world scenarios involving realistic data engineering workloads. - [Data Literacy and AI Fundamentals](https://www.dataquest.io/path/data-literacy-and-ai-fundamentals/): Beginner · 12 hrs · Build practical data literacy skills and learn how AI fits into everyday data work. This short skill path is designed for non-technical professionals who want to understand, explain, and work with data more confidently—and use AI as a helpful support tool without writing code. - [Data Transformation with dbt](https://www.dataquest.io/path/data-transformation-dbt-skill/): Intermediate · 8 hrs · In this path, you'll learn how to use dbt to transform raw data into analytics-ready datasets. You'll go from foundational dbt concepts through production patterns including incremental models, testing, and deployment workflows — all through hands-on, real-world scenarios. ## Popular Courses - [Introduction to Python Programming](https://www.dataquest.io/course/introduction-to-python/): Beginner · 2 hrs · This interactive Python course for beginners develops fundamental data science skills to help you begin your journey to become a successful data professional.In this course, you'll learn to do basic arithmetic; write code using Python syntax; work with different types of data; and perform basic Python operations such as working with variables, processing numerical and text data, and manipulating lists. Best of all, you'll learn by doing - you'll write code and get feedback directly in the browser. - [Introduction to Pandas and NumPy for Data Analysis](https://www.dataquest.io/course/pandas-fundamentals/): Intermediate · 13 hrs · In this course, you'll learn to use NumPy and pandas for data exploration, preparation, and analysis. You'll start this course by learning how NumPy can streamline your data science workflow with vectorized operations, ndarrays, and Boolean indexing. You'll then discover how pandas can super-charge your data exploration, preparation, and analysis. Finally, you'll bring everything you've learned to a data analysis project to test your skills. Best of all, you'll learn by doing - you'll practice and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [Python Functions and Jupyter Notebook](https://www.dataquest.io/course/python-functions-jupyter-notebook/): Beginner · 7 hrs · This course expands on our Introduction to Python  course, and our Basic Operators and Data Structures in Python course. You'll learn how to write Python functions, build functions that employ multiple return statements and return multiple variables, as well as installing and using Jupyter Notebook. You'll complete the course by creating a portfolio project on Profitable App Profiles for the App Store and Google Play Markets. Best of all, you'll learn by doing - you'll practice and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [Basic Operators and Data Structures in Python](https://www.dataquest.io/course/basic-operators-and-data-structures-in-python/): Beginner · 5 hrs · This course builds upon the fundamentals of Python taught in Introduction to Python. You'll learn to repeat a process using "for loops"; how to use conditional statements such as if, else, and elif; how to employ logical operators and comparison operators. You'll also learn how to create Python dictionaries, which are important data structures in Python that help gather elements for identification using a key. Finally, you'll build frequency tables, which help to display the frequencies of different categories (particularly useful for understanding the distribution of values in a dataset). Best of all, you'll learn by doing - you'll practice and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [Intermediate Python for Data Science](https://www.dataquest.io/course/python-for-data-science-intermediate/): Beginner · 8 hrs · This course builds upon Introduction to Python Programming, For Loops and Conditional Statements in Python, Dictionaries, Frequency Tables, and Functions in Python, and Python Functions and Jupyter Notebook. You'll not only learn how to manipulate text, clean messy data, and more but also how to work with object-oriented programming concepts, dates, and times in Python. Best of all, you'll learn by doing - you'll practice and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [Introduction to Python for Data Engineering](https://www.dataquest.io/course/python-fundamentals-de/): Beginner · 4 hrs · This Python course for beginners teaches Python fundamentals and helps you take your first steps to becoming a successful data engineer. In this course, you'll learn to write code using Python syntax; work with different types of data; and perform basic Python operations, such as working with variables, processing numerical and text data, and manipulating lists. Best of all, you'll learn by doing - you'll write code and get feedback directly in the browser. - [Introduction to Data Analysis in Excel](https://www.dataquest.io/course/data-foundations/): Beginner · 3 hrs · This course will help you gain the practical skills in Excel to perform data analysis and visualization - and ultimately help organizations make more-informed decisions. We designed it for aspiring data professionals with little experience or learners who use basic Excel in their daily jobs and want to enhance their skills. Best of all, you'll learn by doing - you'll practice and get feedback directly in the browser. - [Introduction to Data Analysis in R](https://www.dataquest.io/course/intro-to-r-rewrite/): Beginner · 3 hrs · This interactive R course for beginners teaches fundamental data analysis skills and helps you begin your journey to become a successful data professional. In this course, you'll learn to use basic arithmetic; write code using R syntax; and work with different data types, values, and vectors in the data analysis workflow, including data exploration, manipulation, analysis, and visualization with R. Best of all, you'll learn by doing - you'll write code and get feedback directly in the browser. - [Introduction to SQL and Databases](https://www.dataquest.io/course/introduction-to-sql/): Beginner · 4 hrs · This interactive SQL course for beginners will teach you how to code and perform fundamental data science tasks using SQL - and it will help you begin your journey to become a successful data professional.  In this course, you'll learn how to write data queries and how to use statements and clauses - as well as the critical role of SQL in routine data science tasks.  Best of all, you'll learn by doing - you'll write code and get feedback directly in the browser. You'll apply your skills to several guided projects involving real-world scenarios to build your portfolio and prepare for your next interview. - [Data Cleaning and Analysis in Python](https://www.dataquest.io/course/python-datacleaning/): Intermediate · 11 hrs · This course is for intermediate Python users, and it builds upon the essentials covered in our previous Python lessons. You'll learn how to leverage Python to supercharge your data analysis workflow. You'll learn how to manipulate, combine, transform, and merge data; manipulate strings; and work with missing values in Python - as well as new concepts and techniques to improve the speed and efficiency of your Python code. Best of all, you'll learn by doing - you'll practice and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [Introduction to Statistics in Python](https://www.dataquest.io/course/statistics-fundamentals/): Intermediate · 8 hrs · In this course, you'll learn several techniques for sampling data, such as random sampling and cluster sampling; you'll also learn concepts such as discrete variables and random variables in the context of frequency distributions - and the different types of charts and graphs you might use to visualize frequency distributions. Best of all, you'll learn by doing - you'll practice and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. In the guided project, you'll investigate Fandango Movie Ratings to determine if Fandango is inflating movie ratings on its site. This project is a chance for you to apply the statistics skills you've learned and overcome common setbacks in practical data analysis. - [Command Line for Data Science](https://www.dataquest.io/course/command-line-elements/): Intermediate · 4 hrs · In this course, you'll learn how to navigate the filesystem, how to alter permissions for different users, and how to create and run a Python script from the command line. You'll also learn how to use the terminal on UNIX machines and how to use the command line's powerful text processing tools like awk and sed. The lack of a graphical user interface (GUI) also makes the command line faster than other approaches for many tasks. Best of all, you'll learn by doing - you'll practice and get feedback directly in the browser. When you finish the course, you'll have enough hands-on practice that you'll be comfortable using the command line in your day-to-day data analysis tasks. - [Introduction to Data Visualization in Python](https://www.dataquest.io/course/data-visualization-fundamentals/): Intermediate · 7 hrs · In this course, you'll learn how to balance graph creation and statistics in your visualizations using tools such as Matplotlib and Seaborn. Throughout this course, you'll learn the most common methods and techniques to visualize data using a variety of Python libraries. Best of all, you'll learn by doing - you'll practice and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [Data Cleaning Project Walkthrough](https://www.dataquest.io/course/data-cleaning/): Intermediate · 7 hrs · In your data science career, you'll rarely get a dataset that is in precisely the state you want. That's why data cleaning is such an invaluable skill in data science. This course builds on our previous Advanced Data Cleaning course and will make you a valuable asset to any data science team. After learning how to prepare the data for analysis, the real fun begins - you'll complete two data analysis and visualization guided projects using data from some of the biggest names in film culture. - [PostgreSQL for Data Engineering](https://www.dataquest.io/course/postgres-for-data-engineers/): Intermediate · 7 hrs · In this course, you'll learn about the SQL database management system PostgreSQL and what differentiates it from SQLite. You'll learn about proper data types for your data and why they're important. You'll also install PostgreSQL on your own machine and learn how to work with psycopg2, a Python database API for PostgreSQL that allows you to interact with PostgreSQL databases using Python. Best of all, you'll learn by doing - you'll practice and get feedback directly in the browser. At the end of the course, you'll complete a project that asks you to work on a real-life example - storing storm data in a PostgreSQL database. - [Advanced Data Cleaning in Python](https://www.dataquest.io/course/python-data-cleaning-advanced/): Intermediate · 8 hrs · This course builds on basic data cleaning knowledge and requires intermediate familiarity with Python for data science. You'll learn how to clean and manipulate text data using basic and advanced regular expressions, how to resolve missing data, and how to employ lambda functions and list comprehension with pandas. Best of all, you'll learn by doing - you'll practice and get feedback directly in the browser. - [Telling Stories Using Data Visualization and Information Design](https://www.dataquest.io/course/storytelling-information-design/): Intermediate · 5 hrs · This particular course is for intermediate Python users, and it builds upon the essentials covered in our previous Python visualization lessons. You'll learn how to use Python libraries like Matplotlib and Seaborn to transform raw data into compelling and actionable visualizations. You'll learn the most common data visualization techniques, and you'll use Python to generate beautiful, insightful, and meaningful visuals that will give new life to your data. Best of all, you'll learn by doing - you'll practice and get feedback directly in the browser. You'll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview. - [Dictionaries and Functions in Python](https://www.dataquest.io/course/python-fundamentals-de-ii/): Beginner · 3 hrs · In this course, you'll explore the world of Python data engineering. You'll learn basic Python concepts such as dictionaries, functions, and default arguments. Best of all, you'll learn by doing - you'll practice and get feedback directly in the browser. The course will conclude with two guided projects: The first one teaches you to learn and install Jupyter Notebook The second one asks you to perform practical data analysis on profitable app profiles for the App Store and Google Play Market - [Text Processing for Data Science](https://www.dataquest.io/course/text-processing-cli/): Intermediate · 4 hrs · This course builds on the Command Line for Data Science course. You'll learn how to read documentation, how to inspect files, how to perform basic text processing using the command line, how to redirect and pipe output, and how to access documentation for different commands if you get stuck. Best of all, you'll learn by doing - you'll practice and get feedback directly in the browser. - [Introduction to Supervised Machine Learning in Python](https://www.dataquest.io/course/introduction-to-supervised-machine-learning-in-python/): Intermediate · 7 hrs · In this course, you'll learn how to develop a machine learning workflow for classification tasks using scikit-learn. You'll learn how to build and implement the k-nearest neighbors algorithm using pandas and scikit-learn. Finally, you'll learn to train, validate, and improve your machine learning model for better performance and accuracy using techniques like tuning hyperparameters. Best of all, you'll learn by doing - you'll practice and get feedback directly in the browser. At the end of the course, you'll combine your new skills to complete a project to predict heart disease. ## Tutorials - [Advanced Data Cleaning in Python](https://www.dataquest.io/tutorial/advanced-data-cleaning-in-python/): Learn advanced data cleaning in Python with regular expressions, list comprehensions, lambda functions, and missing data strategies. - [Basic Operators and Data Structures in Python](https://www.dataquest.io/tutorial/basic-operators-and-data-structures-in-python/): Learn to harness Python’s basic operators and data structures for efficient data analysis with loops, conditionals, and dictionaries. - [Combining Tables in SQL](https://www.dataquest.io/tutorial/combining-tables-in-sql-tutorial/) - [Data Cleaning and Analysis in Python](https://www.dataquest.io/tutorial/data-cleaning-and-analysis-in-python/): Learn data cleaning and analysis in Python techniques, including handling missing data, cleaning messy datasets, and extracting insights. - [Data Cleaning Project Walk-through](https://www.dataquest.io/tutorial/data-cleaning-project-walk-through/): Follow along as we learn how to clean messy data through a hands-on data cleaning project walk-through using Python and pandas. - [Introduction to Data Visualization in Python](https://www.dataquest.io/tutorial/data-visualization-in-python/): Create impactful data visualizations in Python using Matplotlib, seaborn, and pandas to uncover patterns and communicate insights. - [Intermediate Python for Data Science](https://www.dataquest.io/tutorial/intermediate-python-for-data-science/): Explore essential skills in intermediate Python for data science, including data preparation, OOP, and advanced time manipulation techniques. - [Introduction to Python Programming](https://www.dataquest.io/tutorial/introduction-to-python-programming/): Learn how Python enhances data manipulation, automation, and analysis in this introduction to Python programming for data professionals. - [Introduction to SQL and Databases](https://www.dataquest.io/tutorial/introduction-to-sql-and-databases-tutorial/): Wondering what to learn first? Discover why SQL is the foundation of all data work and why it should be your first step in data science. - [Introduction to NumPy and pandas for Data Analysis](https://www.dataquest.io/tutorial/numpy-and-pandas-for-data-analysis/): Discover how NumPy and pandas transform Python data analysis, boosting speed and efficiency for large datasets while streamlining processing. - [Python Functions and Jupyter Notebook](https://www.dataquest.io/tutorial/python-functions-and-jupyter-notebook/): Explore how Python functions and Jupyter Notebook can streamline your data analysis, making complex tasks faster and more efficient. - [Querying Databases with SQL and Python](https://www.dataquest.io/tutorial/querying-sql-in-python-tutorial/) - [SQL Subqueries](https://www.dataquest.io/tutorial/sql-subqueries-tutorial/) - [Summarizing Data in SQL](https://www.dataquest.io/tutorial/summarizing-data-in-sql-tutorial/): Learn SQL to summarize data with aggregate functions and GROUP BY, helping you analyze large datasets and make data-driven decisions. - [Telling Stories Using Data Visualization and Information Design](https://www.dataquest.io/tutorial/telling-data-stories-with-python-using-information-design/): Create compelling visuals with Matplotlib, using styles like FiveThirtyEight and Gestalt principles to tell clear, engaging data stories. - [Window Functions in SQL](https://www.dataquest.io/tutorial/window-functions-in-sql-tutorial/) ## Cheat Sheets - [Git Command Line Cheat Sheet](https://www.dataquest.io/cheat-sheet/command-line-git-cheat-sheet/): Download our Git Command Line Cheat Sheet with commands for terminal tasks and Git workflows. Perfect for developers and data professionals. - [Microsoft Excel Cheat Sheet](https://www.dataquest.io/cheat-sheet/excel-cheat-sheet/): Download our Excel Cheat Sheet with examples for VLOOKUP, IF, MATCH, and more—organized by category for easy reference. - [Matplotlib Cheat Sheet](https://www.dataquest.io/cheat-sheet/matplotlib-cheat-sheet/): Download our matplotlib cheat sheet for essential plotting commands, plus Seaborn and pandas commands for fast, customized visualizations. - [NumPy Cheat Sheet PDF](https://www.dataquest.io/cheat-sheet/numpy-cheat-sheet/): Download our NumPy cheat sheet for quick access to essential array creation, reshaping, and key operations for efficient data analysis. - [Pandas Cheat Sheet PDF](https://www.dataquest.io/cheat-sheet/pandas-cheat-sheet/): Download our pandas cheat sheet for essential commands on cleaning, manipulating, and visualizing data, with practical examples. - [Power BI Cheat Sheet PDF](https://www.dataquest.io/cheat-sheet/power-bi-cheat-sheet/): Discover essential Power BI features, DAX formulas, and data modeling tips in our Power BI Cheat Sheet. Available for download as a PDF! - [Python Cheat Sheet PDF](https://www.dataquest.io/cheat-sheet/python-cheat-sheet/): Download our essential introduction to Python cheat sheet covering variables, control flow, functions, data structures, OOP, and dates. - [R Programming Cheat Sheet](https://www.dataquest.io/cheat-sheet/r-programming-cheat-sheet/): Download our R Programming Cheat Sheet for essential commands in data manipulation, visualization, and analysis. Perfect for R users! - [Python Regex Cheat Sheet](https://www.dataquest.io/cheat-sheet/regular-expressions-cheat-sheet/): Download our Python regular expressions cheat sheet for syntax, character classes, groups, and re module functions—ideal for pattern matching. - [SQL Cheat Sheet PDF](https://www.dataquest.io/cheat-sheet/sql-cheat-sheet/): Quickly reference essential commands and syntax with this SQL cheat sheet. Perfect for streamlining your database queries. ## Recent Blog Posts - [How to Learn Python in 2026 (Verified by 10K+ Students)](https://www.dataquest.io/blog/how-to-learn-python/): How to learn Python in 2026: skip the syntax grind, build real projects early, and avoid the mistakes that keep most beginners stuck. - [Best AI Projects to Build in 2026 (Sequenced for Hiring)](https://www.dataquest.io/blog/ai-projects/): The 10 best AI projects for 2026, sequenced beginner to portfolio-ready, with insight from Dataquest's AI Engineering experts. - [DataCamp vs Coursera: Which Is Worth It in 2026?](https://www.dataquest.io/blog/datacamp-vs-coursera/): A full comparison of DataCamp vs Coursera covering courses, pricing, learning experience, career outcomes, and portfolio building for data learners. - [Data Scientist Roadmap for Beginners (2026–2027)](https://www.dataquest.io/blog/data-scientist-roadmap-for-beginners/): A data scientist roadmap built on insights from Dataquest’s CTO. What to learn, in what order, and how long it really takes in 2026–2027. - [Project Tutorial: Build a Multi-Provider LLM Gateway](https://www.dataquest.io/blog/build-a-multi-provider-llm-gateway/): Build a multi-provider LLM gateway in Python and learn API integration, response normalization, and error handling across AI providers. - [10 Best Data Science Courses for Beginners in 2026](https://www.dataquest.io/blog/best-data-science-courses/): The 10 best data science courses for beginners and career changers in 2026, ranked by learner goal. Includes free options, certificates, and project-heavy paths. - [Best Data Analytics Courses in 2026](https://www.dataquest.io/blog/best-data-analytics-courses/): Compare 10 of the best data analytics courses in 2026 by cost, time, tools, and who each is for. Honest limitations and a goal-based decision guide. - [Project Tutorial: Build a Food Ordering App with Python](https://www.dataquest.io/blog/build-a-food-ordering-app-with-python/): Build a food ordering app with Python using dictionaries, functions, and loops while learning how real applications are structured. - [Best LLM Courses in 2026](https://www.dataquest.io/blog/best-llm-courses/): Compare the top 10 LLM courses in 2026. Organized by goal, with honest reviews, real costs, and clear guidance on which course fits where you are now. - [Best Data Science Programs in 2026](https://www.dataquest.io/blog/best-data-science-programs/): Compare the best data science programs, including degrees, bootcamps, certificates, and online platforms, to find the right fit for your goals and budget. - [Best Data Engineering Courses in 2026](https://www.dataquest.io/blog/best-data-engineering-courses/): Compare 10 of the best data engineering courses in 2026 by cost, time, format, and stack. Organized by track, with honest limitations on every pick. - [Python Function Calling: How to Give LLMs Access to Real-World Tools](https://www.dataquest.io/blog/python-function-calling/): Learn how function calling works in Python. Understand the mental model, see the full request-response loop, and build a working example. - [Best Machine Learning Courses in 2026](https://www.dataquest.io/blog/best-machine-learning-courses/): Compare 10 of the best machine learning courses in 2026 by cost, time, format, and framework. Organized by track, with honest limitations on every pick. - [Best Deep Learning Courses in 2026](https://www.dataquest.io/blog/best-deep-learning-courses/): Compare 10 of the best deep learning courses in 2026 by cost, time, framework, and what you'll build. Organized by goal, with honest reviews of every pick. - [Best SQL Courses in 2026 (Ranked and Compared )](https://www.dataquest.io/blog/best-sql-courses/): Compare 9 of the best SQL courses in 2026, with cost, format, and skill outcomes for absolute beginners, analysts, engineers, and free-track learners. - [Best Generative AI Courses in 2026](https://www.dataquest.io/blog/best-generative-ai-courses/): Compare 9 of the best generative AI courses for developers in 2026, ranked for engineers building LLM applications, RAG systems, and agents. - [Best AI Courses in 2026: From Using AI to Building It](https://www.dataquest.io/blog/best-ai-courses/): Compare 10 of the best AI courses in 2026, organized by whether you want to use AI tools at work or build AI systems from scratch. - [Project Tutorial: Cleaning and Analyzing Used Car Listings from eBay Kleinanzeigen](https://www.dataquest.io/blog/cleaning-and-analyzing-used-car-listings-from-ebay-kleinanzeigen/): Learn how to clean messy eBay car listing data with pandas, handle outliers and invalid values, and analyze how brand and mileage affect used car prices. - [Best Python Courses in 2026 — From Foundations to Career-Ready Skills](https://www.dataquest.io/blog/best-python-courses/): The best Python courses in 2026 ranked by depth, format, and goal. Find the right path, whether you're starting from zero or building career-ready skills. - [Power BI Tutorial: Create Your First Dashboard](https://www.dataquest.io/blog/power-bi-tutorial/): Power BI tutorial for beginners: clean data, build a model, create visuals, and publish your first interactive dashboard to the cloud using real data. - [All posts](https://www.dataquest.io/blog/) ## Learner Stories (sample) - [Aaron Melton](https://www.dataquest.io/learners/aaron-melton/): Aaron Melton was the first one on his team at a power plant to realize they had no business using Excel for their reports. - [Adam Zabrodski Changed His Career Learning Python with Dataquest](https://www.dataquest.io/learners/adam-zabrodski/): Adam Zabrodski didn't plan to be a data scientist, but after working at Uber and investment banking, he knew he needed a change. - [Ana Santana's Data Analytics Career Journey](https://www.dataquest.io/learners/ana-santanas-data-analytics-career-journey/): Explore Ana's story of career growth in data analytics and how the right learning path in data can significantly boost your job prospects and advance your data career. - [How Dataquest Helped an SEO Expert Save Tons of Time](https://www.dataquest.io/learners/antoine-eripret/): Antoine Eripret decided to learn Python for SEO because he realized he was wasting time. - [How Ashray Adappa Found a Better Approach to Mathematics at Dataquest](https://www.dataquest.io/learners/ashray-adappa/): Chemical engineer-in-training Ashray Adappa realized that his degree program was taking a narrow approach to teaching math. He decided he wanted more. - [Liana Ahrens Teixeira: Building a Data-Focused Future in Financial Services](https://www.dataquest.io/learners/building-a-data-focused-future-in-financial-services/): In this blog, learn how Liana, with a strong background in physics and financial planning, used Dataquest to enhance her business and analytical skills. Find tips for aspiring learners and see how data science can be a game-changer for your career. - [Christian L’Heureux on the Importance of Data Science Projects](https://www.dataquest.io/learners/christian-lheureux/): Christian L'Heureux credits Dataquest with helping him complete the projects he needed to land a job in data science. - [Facing Hard Truths: Dilara Karabey on Changing Her Career Path](https://www.dataquest.io/learners/dilara-karabey/): Dilara Karabey thought she wanted to work in linguistics, but the global pandemic forced her to face some hard truths. - [Dong Zhou on Landing a Job He Loves Using Dataquest](https://www.dataquest.io/learners/dong-zhou/): After four years of working in postdoc positions, Dong Zhou was starting to re-evaluate academia. That's when he found Dataquest. - [From Priest to Data Engineer: Eddie Kirkland's Dataquest Story](https://www.dataquest.io/learners/eddie-kirkland/): Eddie Kirkland went from priest to data engineer in just six months with Dataquest. Here's the story of his incredible journey. - [From Hostess to Data Scientist: Elizaveta Gorelova's Success Story](https://www.dataquest.io/learners/elizaveta-gorelova/): Elizaveta Gorelova went from restaurant hostess to data scientist using the Dataquest platform. Here's her success story. - [Eric Sales De Andrade: Getting Real with Data at Dataquest](https://www.dataquest.io/learners/eric-salesdeandrade/): Eric Sales De Andrade came to Dataquest via Quora after reading a post by Dataquest CEO Vik Paruchuri. Here's his story. - [All learner stories](https://www.dataquest.io/learner-stories/) ## Optional - [Full content dump](https://www.dataquest.io/llms-full.txt): Concatenated markdown of every path / course / tutorial / cheat-sheet description for one-fetch ingestion. - [Sitemap (XML)](https://www.dataquest.io/sitemap_index.xml): Machine-readable sitemap for search engines.