The role of a data scientist is to turn raw data into actionable insights. Much of the world's raw data—from electronic medical records to customer transaction histories—lives in organized collections of tables called relational databases. To be an effective data scientist, you must know how to wrangle and extract data from these databases using a language called SQL . This course teaches syntax in SQL shared by many types of databases, such as PostgreSQL, MySQL, SQL Server, and Oracle. This course teaches you everything you need to know to begin working with databases today!

Master the basics of querying tables in relational databases such as MySQL, SQL Server, and PostgreSQL.

Learn the basics of syntax in SQL, how to extract and wrangle data, and use querying tables in relational databases like MySQL, SQL Server, and PostgreSQL.

Introduction to SQL

Begin your journey into Data Science! Even if you've never written a line of code in your life, you'll be able to follow this course and witness the power of Python to perform Data Science. You'll use data to solve the mystery of Bayes, the kidnapped Golden Retriever, and along the way you'll become familiar with basic Python syntax and popular Data Science modules like Matplotlib (for charts and graphs) and pandas (for tabular data).

Dive into data science using Python and learn how to effectively analyze and visualize your data. No coding experience or skills needed.

Dive into data science using Python and learn how to effectively analyze and visualize your data using Pandas and Matplotlib. No coding experience needed.

Introduction to Data Science in Python

What is data science, why is it so popular, and why did the Harvard Business Review hail it as the “sexiest job of the 21st century”? In this non-technical course, you’ll be introduced to everything you were ever too afraid to ask about this fast-growing and exciting field, without needing to write a single line of code. Through hands-on exercises, you’ll learn about the different data scientist roles, foundational topics like A/B testing, time series analysis, and machine learning, and how data scientists extract knowledge and insights from real-world data. So don’t be put off by the buzzwords. Start learning, gain skills in this hugely in-demand field, and discover why data science is for everyone!

An introduction to data science with no coding involved.

Discover what data science is, why it's so popular, and learn how to do it with hand-on exercises. There is no code required in this introductory course. 

Data Science for Everyone

Gain a 360° overview of exploring and using Power BI to build impactful reports. In this course, you’ll go from zero to hero as you discover how to use this popular business intelligence platform through hands-on exercises. Before diving into creating visualizations using Power BI's drag-and-drop functionality, you’ll first learn how to confidently load and transform data using Power Query and the importance of data models. You’ll also learn to drill down into reports and make your reports fully interactive. You've got the power!

Gain a 360° overview of how to explore and use Power BI to build impactful reports.

Learn how to use the Power BI platform to load and transform data, create visualzations, run DAX formulas, and create reports through hands-on exercises.

Introduction to Power BI

Now that you've learned the basics of SQL in our <a href="https://learn.datacamp.com/courses/introduction-to-sql">Introduction to SQL</a> course,  it's time to supercharge your queries using joins and relational set theory. In this course, you'll learn all about the power of joining tables while exploring interesting features of countries and their cities throughout the world. You will master inner and outer joins, as well as self joins, semi joins, anti joins and cross joins—fundamental tools in any PostgreSQL wizard's toolbox. Never fear set theory again after learning all about unions, intersections, and except clauses through easy-to-understand diagrams and examples. Lastly, you'll be introduced to the challenging topic of subqueries. You will be able to visually grasp these ideas by using Venn diagrams and other linking illustrations.

Join two or three tables together into one, combine tables using set theory, and work with subqueries in PostgreSQL.

Discover all the fundamental in PostgreSQL, like inner, outer self, semi, anti, and cross joins, as well as unions, intersections, and except clauses.

Joining Data in SQL

In 2019, the average salary for data engineers overtook data scientists. How did this happen? Companies wanting to find the gold within their data realized it wasn’t possible if they hadn’t yet built the mine. Data engineers lay the foundations that make data science possible.
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In this course, you’ll learn about a data engineer’s core responsibilities, how they differ from data scientists, and facilitate the flow of data through an organization. Through hands-on exercises you’ll follow Spotflix, a fictional music streaming company, to understand how their data engineers collect, clean, and catalog their data. By the end of the course, you’ll understand what your company's data engineers do, be ready to have a conversation with a data engineer, and have a solid foundation to start your own data engineer journey.


Discover how data engineers lay the groundwork that makes data science possible. No coding involved!

Data Engineering for Everyone

What's behind the machine learning hype? In this non-technical course, you’ll learn everything you’ve been too afraid to ask about machine learning. There’s no coding required. Hands-on exercises will help you get past the jargon and learn how this exciting technology powers everything from self-driving cars to your personal Amazon shopping suggestions.

How does machine learning work, when can you use it, and what is the difference between AI and machine learning? They’re all covered. Gain skills in this hugely in-demand and influential field, and discover why machine learning is for everyone!


An introduction to machine learning with no coding involved.

Discover what machine learning is, how it works, and how you can use it through hands-on exercise. There is no need to know how to code to learn about ML.

Machine Learning for Everyone

Visualizing data using charts, graphs, and maps is one of the most impactful ways to communicate complex data. In this course, you’ll learn how to choose the best visualization for your dataset, and how to interpret common plot types like histograms, scatter plots, line plots and bar plots. You'll also learn about best practices for using colors and shapes in your plots, and how to avoid common pitfalls. Through hands-on exercises, you'll visually explore over 20 datasets including global life expectancies, Los Angeles home prices, ESPN's 100 most famous athletes, and the greatest hip-hop songs of all time.

An introduction to data visualization with no coding involved.

Learn how to visualize your data using charts, graphs and maps as well as how to interpret common plot time, best practices for colors, shapes, and more.

Data Visualization for Everyone

Every day we interact with the cloud—whether it’s using Google Drive, apps like Salesforce, or accessing our favorite websites. Cloud computing has become the norm for many companies, but what exactly is the cloud and why is everyone rushing to adopt it? Designed for absolute novices, this course breaks down what the cloud is and explains terminology such as scalability, latency, and high-availability. You'll learn about the many advantages including ease of remote collaboration, how there are no hardware limitations, and reliable disaster recovery. You'll also discover the range of tools provided by major cloud providers such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud. By the end of this course, you'll be able to confidently explain how cloud tools can increase productivity and save money, as well as ask the right questions about how to optimize your use of cloud tools.

A non-coding introduction to the world of cloud computing.

Discover what the cloud is, how it works, and what its benefits are. You’ll also learn about terminology like scalability, latency, and high availability.

Cloud Computing for Everyone

In this interactive Power BI course, you’ll learn how to use Power Query Editor to transform and shape your data to be ready for analysis. You’ll also get to grips with advanced Power BI topics, including how to use M language and the Advanced Editor, to help you be even more efficient in data preparation.

In this interactive Power BI course, you’ll learn how to use Power Query Editor to transform and shape your data to be ready for analysis.

Data Preparation in Power BI

DAX, or Data Analysis eXpressions, is a formula language used in Microsoft Power BI to create calculated columns, measures, and custom tables. Once mastered, DAX gives you powerful control over visuals and reports, allowing for better performance and more flexibility. In this course, you'll get to grips with a wide range of DAX calculations and learn best practices for how to use them in your projects.

This course will be split into two smaller courses of 3 hours on Tue 26 April in light of a brand-new Power BI track. Course completion will be transferred to these two new courses, so please complete the course in due time. Alternatively, you can wait a few days until the new courses are live!

Data Analysis Expressions (DAX) allow you to take your Power BI skills to the next level by writing custom functions.

Discover a wide range of DAX calculations and learn how to use them in in Microsoft Power BI to create calculated columns, measures, and custom tables.

DAX in Power BI

DAX, or Data Analysis eXpressions, is a formula language used in Microsoft Power BI to create calculated columns, measures, and custom tables. Once mastered, DAX gives you powerful control over visuals and reports, allowing for better performance and more flexibility. This course covers the core concepts such as row query and filter context, with exercises focusing on filtering, counting, ranking, and iterating functions.

DAX Functions in Power BI

Proper data modeling is the foundation of data analysis and creating reports in Power BI. This course lets you explore a toolbox of data cleaning, shaping, and loading techniques, which you can apply to your data. You'll get to know how to choose between Power Query and Power BI, and discover the foundations of data modeling by going into star and snowflake schemas. You'll apply all of this to real-world datasets issued by the United States Census Bureau.

Learn the key concepts of data modeling on Power BI.


Learn how to set up and load data into Power BI and Power Query to be able to perform dimensional modeling, Kimball modeling, and advanced data modeling.

Data Modeling in Power BI

In this course, you’ll learn all about table transformations in Power BI. You’ll learn how to (un)pivot, transpose, and append tables. You’ll also get introduced to joins and discover when it makes sense to use them. Finally, you’ll gain power with custom columns, including how to use M language and the Advanced Editor, to help you be even more efficient in data preparation.

You’ll learn how to (un)pivot, transpose, append and join tables. Gain power with custom columns, M language, and the Advanced Editor.

Data Transformation in Power BI

In this course, you’ll extend your knowledge about facts, dimensions, and their relationships. You learn about the cardinality of relationships and how you can use bi-directional cross-filtering in your model.
You’ll also explore the use of quick measures and hierarchies and write DAX to fully customize your data model. Finally, you’ll get introduced to Power BI reporting best practices to improve the performance of your reports.

Intermediate Data Modeling in Power BI

This course introduces you to new DAX functions and its many use cases. First of all, you expand your core DAX knowledge by learning how to write logical functions. Secondly, you’ll discover how you can write DAX functions for row-level security (RLS) purposes and how to use DAX to manipulate tables and create nested functions. Those time-intelligence quick measures will be building themselves before you know it!

Discover a wide range of DAX calculations and learn how to use them in in Microsoft Power BI.

Intermediate DAX in Power BI

Data connections are an essential part of Power BI. In this course, you will be introduced to the many different options for connecting to data. You’ll learn the differences between Power BI Desktop and Power BI Service when it comes to data connections. You’ll also learn about the different ways that Power BI stores data when connecting to a source, and how you are able to amend connections after they have been made. Finally, you’ll learn how you can use parameters and M Language in Power BI Desktop to level up your handling of data import processes.

Discover the different ways you can enhance your Power BI data importing skills.

Data Connections in Power BI

In this course, you’ll learn how to analyze time series, visualize your data, and spot trends. You’ll build new date variables, discover run charts, and get into calculating rolling averages. Finally, you’ll find out how to identify which variables exhibit the most influence on the target variable using Power BI's decomposition trees and key influencers.

Enhance your reports with trend analysis techniques such as time series, decomposition trees, and key influencers.

Trend Analysis in Power BI

Learn how to deploy and maintain assets in Power BI. Through hands-on exercises, you’ll get to grips with the Power BI Service interface and key elements in it like workspaces. You’ll learn how to securely report access by managing access to datasets, implementing row-level security, or applying sensitivity labels to prevent unauthorized data re-use or exfiltration. You’ll also discover how to promote and certify content in Power BI before learning how to save time by subscribing to reports and setting up data alerts—making it easy to keep on top of changes to data in your reports.

Learn how to deploy and maintain assets in Power BI. You’ll get to grips with the Power BI Service interface and key elements in it like workspaces. 

Deploying and Maintaining Assets in Power BI

Python is a general-purpose programming language that is becoming ever more popular for data science. Companies worldwide are using Python to harvest insights from their data and gain a competitive edge. Unlike other Python tutorials, this course focuses on Python specifically for data science. In our Introduction to Python course, you’ll learn about powerful ways to store and manipulate data, and helpful data science tools to begin conducting your own analyses. Start DataCamp’s online Python curriculum now.

Master the basics of data analysis in Python. Expand your skillset by learning scientific computing with NumPy.

Discover how to use Python for data science, learning about the ways to store and manipulate data in the environment to begin conducting your own analyses.

Introduction to Python

Learning Python is crucial for any aspiring data science practitioner. Learn to visualize real data with Matplotlib's functions and get acquainted with data structures such as the dictionary and the pandas DataFrame. After covering key concepts such as boolean logic, control flow, and loops in Python, you'll be ready to blend together everything you've learned to solve a case study using hacker statistics.

Level up your data science skills by creating visualizations using Matplotlib and manipulating DataFrames with pandas.

In this intermediate Python course, learn to visualize real data with Matplotlib's functions and get to know new data structures such as the pandas DataFrame.

Intermediate Python

So you've learned how to aggregate and join data from tables in your database—now what? How do you manipulate, transform, and make the most sense of your data? This intermediate-level course will teach you several key functions necessary to wrangle, filter, and categorize information in a relational database, expand your SQL toolkit, and answer complex questions. You will learn the robust use of CASE statements, subqueries, and window functions—all while discovering some interesting facts about soccer using the European Soccer Database.

Master the complex SQL queries necessary to answer a wide variety of data science questions and prepare robust data sets for analysis in PostgreSQL.

Intermediate SQL

Enhance your reports with Power BI's Exploratory Data Analysis (EDA). You'll start by using descriptive statistics to spot outliers, identify missing data, and apply imputation techniques to fill gaps in your dataset. You’ll then learn how EDA in Power BI can help you discover the relationships between variables—both categorical and continuous— by using basic statistical measures and box and scatter plots.

Enhance your reports with Power BI's Exploratory Data Analysis (EDA). Learn what EDA is for Power BI and how it can help you extract insights from your data.

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