Skip to main content

Data, AI, and Cloud Courses

Master skills that matter

Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.

  • Learn at your own pace
  • Get hands-on experience
  • Complete bite-sized chapters

Create Your Free Account

Continue with GoogleShow more options

or

By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.
260 Courses

Course

Introduction to Functions in Python

  • BasicSkill Level
  • 4.8+
  • 1,237 reviews

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

Software Development

3 hours

Course

Software Engineering Principles in Python

  • BasicSkill Level
  • 4.7+
  • 670 reviews

Learn about modularity, documentation, and automated testing to help you solve data science problems more quickly and reliably.

Software Development

4 hours

Course

Writing Efficient Python Code

  • IntermediateSkill Level
  • 4.8+
  • 2,329 reviews

Learn to write efficient code that executes quickly and allocates resources skillfully to avoid unnecessary overhead.

Software Development

4 hours

Course

Hypothesis Testing in Python

  • IntermediateSkill Level
  • 4.7+
  • 3,363 reviews

Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests in Python.

Probability & Statistics

4 hours

Course

Multi-Agent Systems with LangGraph

  • AdvancedSkill Level
  • 4.8+
  • 461 reviews

Build powerful multi-agent systems by applying emerging agentic design patterns in the LangGraph framework.

Artificial Intelligence

2 hours 45 min

Course

Introduction to Microsoft Fabric

  • BasicSkill Level
  • 4.7+
  • 908 reviews

To understand Fabric’s main use cases, you will explore various tools in the seven Fabric experiences.

Other

4 hours

Course

Introduction to Bash Scripting

  • IntermediateSkill Level
  • 4.8+
  • 452 reviews

Bash scripting allows you to build analytics pipelines in the cloud and work with data stored across multiple files.

Software Development

4 hours

Course

Model Validation in Python

  • IntermediateSkill Level
  • 4.8+
  • 821 reviews

Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.

Machine Learning

4 hours

Course

Natural Language Processing with spaCy

  • IntermediateSkill Level
  • 4.7+
  • 565 reviews

Master the core operations of spaCy and train models for natural language processing. Extract information from unstructured data and match patterns.

Machine Learning

4 hours

Course

Math for Finance Professionals

  • BasicSkill Level
  • 4.8+
  • 287 reviews

Learn essential finance math skills with practical Excel exercises and real-world examples.

Applied Finance

3 hours

Course

Optimizing Code in Java

  • AdvancedSkill Level
  • 4.8+
  • 170 reviews

Learn key techniques to optimize Java performance, from algorithm efficiency to JVM tuning and multithreading.

Software Development

3 hours

Course

Marketing Analytics in Google Sheets

  • IntermediateSkill Level
  • 4.8+
  • 215 reviews

Learn how to ensure clean data entry and build dynamic dashboards to display your marketing data.

Reporting

4 hours

Course

Quantitative Risk Management in R

  • BasicSkill Level
  • 4.8+
  • 79 reviews

Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.

Applied Finance

5 hours

Course

Statistical Simulation in Python

  • IntermediateSkill Level
  • 4.8+
  • 28 reviews

Learn to solve increasingly complex problems using simulations to generate and analyze data.

Probability & Statistics

4 hours

Course

Parallel Programming with Dask in Python

  • IntermediateSkill Level
  • 4.8+
  • 61 reviews

Learn how to use Python parallel programming with Dask to upscale your workflows and efficiently handle big data.

Software Development

4 hours

Course

Introduction to Statistics in Python

  • IntermediateSkill Level
  • 4.7+
  • 7,843 reviews

Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data using Python.

Probability & Statistics

4 hours

Course

Introduction to Statistics in R

  • IntermediateSkill Level
  • 4.7+
  • 2,006 reviews

Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data.

Probability & Statistics

4 hours

FAQs

What is data science?

Data science is an area of expertise focused on gaining information from data. Using programming skills, scientific methods, algorithms, and more, data scientists analyze data to form actionable insights.

How can I learn data science?

You’ll need to learn a programming language such as Python or R and master the principles of math and statistics. Knowledge of data analysis methods and data science tools is also essential. There are many ways to learn data science. As well as formal means of education, such as a degree or university study, there are plenty of other resources to help you learn at your own pace. As well as online courses and tutorials, there are books, videos, and more.

What skills are required for data science?

As well as knowledge of mathematics and statistics, data scientists need programming skills in languages such as Python, R, and SQL. Additionally, data science requires the ability to work with large data sets, knowledge of data visualization, data wrangling, and database management. Skills in machine learning and deep learning can also be useful.

What can I use data science for?

In a professional capacity, almost every industry can use data science to some degree. Healthcare organizations use data science to detect and cure diseases, while finance companies use it to detect and prevent fraud. All kinds of industries use data science for marketing, such as building recommendation systems and analyzing customer churn.

Is data science a good career?

Yes, data science is among the fastest-growing sectors in the US and worldwide. It’s also one of the best-paid careers out there. According to data from Payscale, experience data scientists earn an average of $97,609 and have a satisfaction rating of four stars out of five in the US.

Is it difficult to become a data scientist?

There are a few things to consider here. First, data science degrees can be competitive to get onto, often requiring consistently high grades. Similarly, many of the skills required for data science require a lot of study and patience. It can take several months to master all of the necessary basics, as well as a lot of practical experience to secure an entry-level position.

Does data science require coding?

Yes, you’ll need some coding experience in languages such as Python, R, SQL, Java, and C/C++. However, due to its relatively simple syntax, Python programming language is often the preferred choice among newcomers.

How long does it take to become a data scientist?

For a person with no prior coding experience and/or mathematical background, it can typically take 7 to 12 months of intensive studies to be at the level of an entry-level data scientist. However, it is important to remember that learning only the theoretical basis of data science may not make you a real data scientist.

What topics can I study within data science?

Once you’ve mastered the foundations of data science, you can then specialize in a variety of areas, including machine learning, artificial intelligence, big data analysis, business analytics and intelligence, data mining, and more.

Grow your data skills with DataCamp for Mobile

Make progress on the go with our mobile courses and daily 5-minute coding challenges.