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

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

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

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

pandas is the world's most popular Python library, used for everything from data manipulation to data analysis. In this course, you'll learn how to manipulate DataFrames, as you extract, filter, and transform real-world datasets for analysis. Using pandas you’ll explore all the core data science concepts. Using real-world data, including Walmart sales figures and global temperature time series, you’ll learn how to import, clean, calculate statistics, and create visualizations—using pandas to add to the power of Python!

Use the world’s most popular Python data science package to manipulate data and calculate summary statistics.

Data Manipulation with pandas

SQL is an essential skill for data scientists, and Microsoft SQL Server is one of the world's most popular database systems. In this course, you'll start with simple SELECT statements, and refine these queries with ORDER BY and WHERE clauses. You'll learn how to group and aggregate your results, and also how to work with strings.  You'll also cover the most common way to join tables, how to create tables, and inserting and updating data. You'll mainly work with the Chinook digital media database, representing sales of various artists and tracks. The music theme continues with the classic rock and Eurovision datasets, while we also look at trends in power outages in the US. Overall, you'll become proficient in the most common data manipulation tasks in SQL Server and build a solid foundation for the upcoming T-SQL courses here on DataCamp!

Become proficient at using SQL Server to perform common data manipulation tasks.

Learn how to use SQL Server to do common data manipulation tasks, like insert data, joining tables,  group and aggregate results, and work with strings.

Introduction to SQL Server

Start your journey to becoming a DAX master with this introductory course on DAX. You’ll learn fundamental concepts and best practices for implementing DAX in your reports. You’ll learn to write DAX code to generate calculated columns, measures, and tables while learning supporting knowledge around ‘context’ in Power BI. Finally, we’ll round off the course by introducing time-intelligence functions and show you how to use Quick Measures to create complex DAX code. Let’s take the first step in your DAX mastery journey!

Enhance your Power BI knowledge, by learning the fundamentals of Data Analysis Expressions (DAX) such as calculated columns, tables, and measures. 

Introduction to DAX in Power BI

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 any 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. You'll also learn how to analyze time series, visualize your data, and spot trends. Lastly, 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.

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!

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.

Data Analysis in Power BI

Being able to combine and work with multiple datasets is an essential skill for any aspiring Data Scientist. pandas is a crucial cornerstone of the Python data science ecosystem, with Stack Overflow recording 5 million views for pandas questions. Learn to handle multiple DataFrames by combining, organizing, joining, and reshaping them using pandas. You'll work with datasets from the World Bank and the City Of Chicago. You will finish the course with a solid skillset for data-joining in pandas.

Learn to combine data from multiple tables by joining data together using pandas.

Learn to handle multiple DataFrames by combining, organizing, joining, and reshaping them using Pandas. You'll gain a solid skillset for data-joining.

Joining Data with pandas

Power BI has extraordinary visuals that can be used in reports and dashboards.
In this Power BI course, you’ll learn to create insightful visualizations through built-in and customized charts and conditional formatting. You’ll discover how to create a plethora of visualizations such as scatter plots, tornado charts, gauges, and how to visualize everything without overwhelming your audience.

Power BI is a powerful data visualization tool that can be used in reports and dashboards.

Learn how to use Power BI to create insightful dashboards and reports, as well as data visualization best practices.

Data Visualization in Power BI

You’ve already used SQL to query data from databases. But did you know that there's a lot more you can do with databases? You can model different phenomena in your data, as well as the relationships between them. This gives your data structure and consistency, which results in better data quality. In this course, you'll experience this firsthand by working with a real-life dataset that was used to investigate questionable university affiliations. Column by column, table by table, you'll get to unlock and admire the full potential of databases. You'll learn how to create tables and specify their relationships, as well as how to enforce data integrity. You'll also discover other unique features of database systems, such as constraints.

Learn how to create one of the most efficient ways of storing data - relational databases! 

Learn how to create tables and specify their relationships in SQL, as well as how to enforce data integrity and other unique features of database systems.

Introduction to Relational Databases in SQL

The Unix command line has survived and thrived for almost 50 years because it lets people do complex things with just a few keystrokes. Sometimes called "the universal glue of programming," it helps users combine existing programs in new ways, automate repetitive tasks, and run programs on clusters and clouds that may be halfway around the world. This course will introduce its key elements and show you how to use them efficiently.

The Unix command line helps users combine existing programs in new ways, automate repetitive tasks, and run programs on clusters and clouds. 

Discover the Unix command line and how to use it to combine existing programs, automate repetitive tasks, and run programs on clusters and clouds in Shell.

Introduction to Shell

A majority of data is stored in databases and knowing the necessary tools needed to analyze and clean data directly in databases is indispensable. This course focuses on T-SQL, the version of SQL used in Microsoft SQL Server, needed for data analysis. You will learn several concepts in this course such as dealing with missing data, working with dates, and calculating summary statistics using advanced queries. After completing this course, you will have the skills needed to analyze data and provide insights quickly and easily.

In this course, you will use T-SQL, the flavor of SQL used in Microsoft's SQL Server for data analysis.

Learn concepts for working in  T-SQL, such as dealing with missing data, working with dates, and calculating summary statistics using advanced queries.

Intermediate SQL Server

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 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

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.

Exploratory Data Analysis in Power BI

It is critical to know how to handle errors and manage transactions when programming SQL scripts. Unhandled errors can be very harmful and can cause unexpected situations, such as inconsistent data in your database, or even worse, errors can lead you to make wrong business decisions.
In this course, you will learn how to handle errors and discover how to manage transactions in case of an error. Additionally, you will study what happens when two or more people interact at the same time with the same data. You will practice all these concepts using two datasets, one of them based on bank accounts and the other one on an electric bike store.

Learn to write scripts that will catch and handle errors and control for multiple operations happening at once.

Transactions and Error-Handling in SQL Server

Transactions and Error Handling in SQL Server

In this course you learn how to design with users in mind. You’ll also learn to use R and Python to create unique visualizations, adding custom chart types that would otherwise not be available in Power BI. You’ll get introduced to some best practices in data visualization and optimize your visualizations to be more accessible to visually impaired individuals. This course also teaches you how to create paginated reports, a prerequisite for the official PL-300 exam!

Learn how to design Power BI visualizations and reports with users in mind.

User-oriented Design in Power BI

User-Oriented Design 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

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

SQL Server has a robust set of tools to prepare, aggregate, and query time series data. This course will show you how to build and work with dates, parse dates from strings (and deal with invalid strings), and format dates for reporting. From there, you will see how SQL Server's built-in aggregation operators and window functions can solve important business problems like calculating running totals, finding moving averages, and displaying month-over-month differences using realistic sample data sets. You will also see how taking a different perspective on your data can solve difficult problems.

Explore ways to work with date and time data in SQL Server for time series analysis

Time Series Analysis in SQL Server

A good database design is crucial for a high-performance application. Just like you wouldn't start building a house without the benefit of a blueprint, you need to think about how your data will be stored beforehand. Taking the time to design a database saves time and frustration later on, and a well-designed database ensures ease of access and retrieval of information. While choosing a design, a lot of considerations have to be accounted for. In this course, you'll learn how to process, store, and organize data in an efficient way. You'll see how to structure data through normalization and present your data with views. Finally, you'll learn how to manage your database and all of this will be done on a variety of datasets from book sales, car rentals, to music reviews.

Learn to design databases using star and snoflake schemas, and OLTP and OLAP. You will gain essential skills for creating and managing databases in SQL.

Database Design

In this Power BI case study, you’ll explore a real-world job posting dataset to uncover insights for a fictional recruitment company called DataSearch. Using what you’ve learned from previous courses, you’ll use Power Query to investigate and clean the data to find out what skills are most in-demand for data scientists, data analysts, and data engineers. You’ll then use DAX to build insightful visualizations of your findings. Finally, you’ll bring it all together using everything Power BI has to offer to create a business dashboard so that you can answer questions for the DataSearch team.

Help a fictional company in this interactive Power BI case study. You’ll use Power Query, DAX, and dashboards to identify the most in-demand data jobs!

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