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

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

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

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 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

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

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

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

Have you ever wondered how data professionals use SQL to solve real-world business problems, like generating rankings, calculating moving averages and running totals, deduplicating data, or performing time intelligence? If you already know how to select, filter, order, join and group data with SQL, this course is your next step. By the end, you will be writing queries like a pro! You will learn how to create queries for analytics and data engineering with window functions, the SQL secret weapon! Using flights data, you will discover how simple it is to use window functions, and how flexible and efficient they are.

Learn how to create queries for analytics and data engineering with window functions, the SQL secret weapon! 

PostgreSQL Summary Stats and Window Functions

This course will provide you an understanding of how to use built-in PostgreSQL functions in your SQL queries to manipulate different types of data including strings, character, numeric and date/time. We'll travel back to a time where Blockbuster video stores were on every corner and if you wanted to
watch a movie, you actually had to leave your house to rent a DVD! You'll also get an introduction into the robust full-text search capabilities which provides a powerful tool for indexing and matching keywords in a PostgreSQL document. And finally, you'll learn how to extend these features by using PostgreSQL extensions.

Learn the most important PostgreSQL functions for manipulating, processing, and transforming data. 

Learn how to use built-in PostgreSQL functions in your SQL queries to manipulate different types of data like strings, character, numeric and date/time.

Functions for Manipulating Data in PostgreSQL

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

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

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

In this course, you will learn how to make use of the most important functions for manipulating data provided by SQL Server.  You can use these functions for processing and transforming data to get the results you want.

Learn the most important functions for manipulating, processing, and transforming data in SQL Server.

Learn how to use the most important functions for manipulating data in SQL Server to manipulate, process, and transform data to get the results you want.

Functions for Manipulating Data in SQL Server

Take your SQL Server programming to the next level. First, we demystify how to manipulate datetime data by performing temporal exploratory data analysis with the Washington DC BikeShare transactional dataset. Then, you’ll master how to create, update, and execute user-defined functions and stored procedures. You will learn the proper context for each modular programming tool and best practices. In the final chapter, you will apply all of your new skills to solve a real-world business case identifying the New York City yellow taxi utilization for each borough, and which pickup locations should be scheduled for each driver shift.

Master SQL Server programming by learning to create, update, and execute functions and stored procedures.

Writing Functions and Stored Procedures in SQL Server

A mission critical assignment is depending on your SQL coding skills. You’ve been given some code to fix.  It is giving the results you need but it’s running too slow, and it’s poorly formatted making it hard to read.  The deadline is tomorrow.  You’ll need to reformat the code and try different methods to improve performance.  The pressure is on!!!  In this course we’ll be using SQL on real world datasets, from sports and geoscience, to look at good coding practices and different ways how we can can improve the performance of queries to achieve the same outcome.

In this course, students will learn to write queries that are both efficient and easy to read and understand.

Discover how you can reformat code and try different methods to improve the performance of queries in SQL. Then apply your skills to real-world datasets.

Improving Query Performance in SQL Server

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

Auditing your SQL Server database and keeping data integrity can be a challenging task for DBAs and database developers. SQL Server triggers are special types of stored procedures designed to help you achieve consistency and integrity of your database. This course will teach you how to work with triggers and use them in real-life examples. Specifically, you will learn about the use cases and limitations of triggers and get practice designing and implementing them. You will also learn to optimize triggers to fit your specific needs.

Learn how to design and implement triggers in SQL Server using real-world examples.

Building and Optimizing Triggers in SQL Server

Gain the fundamental skills you need to interact with and query your data in SQL—a powerful language used by data-driven businesses large and small to explore and manipulate their data to extract meaningful insights.

In this track, you'll learn the skills you need to level up your data skills and leave Excel behind you. Through hands-on exercises, you’ll discover how to quickly summarize, join tables, and use window functions and built-in PostgreSQL functions to analyze your data. 

Learn the fundamental business skills you need to write SQL queries and start analyzing your data using this powerful language.

SQL Fundamentals

Gain the starting SQL Server skills you need to summarize data, join tables, and analyze data using built-in SQL Server functions. 

In this track, you’ll discover how SQL Server is like a supercharged Microsoft Excel. Through interactive exercises, you’ll learn how to access, query, and extract huge amounts of data from multiple databases. Using real-world data you’ll also learn how to perform powerful cross-database analyses that you can then apply in your own role. 

Gain the starting SQL Server skills you need to summarize data, join tables, and analyze your data using SQL Server functions. 

SQL Server Fundamentals

Data is one of your business’s most valuable commodities. In this track you’ll learn the key skills you need to set-up, design, maintain, and monitor your team’s database. Dive in and learn the key SQL Server skills you need to securely manage access and monitor database performance using SQL server.

Dive in and learn the key SQL Server skills you need to securely set-up, design, and maintain your business’s database.

SQL Server for Database Administrators

Learn the basics of database design and the different SQL data types. Then master the core concepts for the exam. In this track, you’ll learn how to write queries, functions, and stored procedures. You’ll also find out how to manage transactions, handle errors, and improve query performance. 

Gain the SQL Server skills you need to write, troubleshoot, and optimize your queries using SQL Server. 

with SQL Server

 Data Analyst

It's time to push forward and develop your Python chops even further. There are tons of fantastic functions in Python and its library ecosystem. However, as a data scientist, you'll constantly need to write your own functions to solve problems that are dictated by your data. You will learn the art of function writing in this first Python Data Science Toolbox course. You'll come out of this course being able to write your very own custom functions, complete with multiple parameters and multiple return values, along with default arguments and variable-length arguments. You'll gain insight into scoping in Python and be able to write lambda functions and handle errors in your function writing practice. And you'll wrap up each chapter by using your new skills to write functions that analyze Twitter DataFrames.

Learn the art of writing your own functions in Python, as well as key concepts like scoping and error handling.

Python Data Science Toolbox (Part 1)

In this course, you'll learn how to use Spark from Python! Spark is a tool for doing parallel computation with large datasets and it integrates well with Python. PySpark is the Python package that makes the magic happen. You'll use this package to work with data about flights from Portland and Seattle. You'll learn to wrangle this data and build a whole machine learning pipeline to predict whether or not flights will be delayed. Get ready to put some Spark in your Python code and dive into the world of high-performance machine learning!

Learn to implement distributed data management and machine learning in Spark using the PySpark package.

Learn to wrangle data and build a machine learning pipeline to make predictions with  PySpark Python package. Practice your skills with real-world data.

Introduction to PySpark

In this course, you will learn how to use SQL to support decision making. It is based on a case study about an online movie rental company with a database about customer information, movie ratings, background information on actors and more. You will learn to apply SQL queries to study for example customer preferences, customer engagement, and sales development. This course also covers SQL extensions for online analytical processing (OLAP), which makes it easier to obtain key insights from multidimensional aggregated data.

Learn how to analyze a SQL table and report insights to management.

Data-Driven Decision Making in SQL

Oracle SQL is one of the most widely used database management system around the world. It's well suited to power primarily commercial and enterprise applications, and is particularly popular at large companies with mission-critical databases. Mastering Oracle SQL is therefore guaranteed to open exciting opportunities.
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In this course, you will get a complete introduction to Oracle SQL solving business problems for a digital media store. You will first learn how to access, retrieve and restrict data. You will then perform aggregation and combine tables. The last chapter will have you handle missing values and convert data. By the end of this course, you will understand how Oracle processes SQL queries and will have a solid foundation in Oracle SQL.

Learn how to import and manipulate data with Oracle SQL.

Discover Oracle SQL, what it is, and how you can use it to access, retrieve, convert, and restrict data to perform aggregation and handle missing values.

Introduction to Oracle SQL

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.

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