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.
528 Courses

Course

Introduction to R for Finance

  • BasicSkill Level
  • 4.7+
  • 101 reviews

Learn essential data structures such as lists and data frames and apply that knowledge directly to financial examples.

Applied Finance

4 hours

Course

Dimensionality Reduction in Python

  • IntermediateSkill Level
  • 4.8+
  • 900 reviews

Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.

Machine Learning

4 hours

Course

Introduction to Bioconductor in R

  • IntermediateSkill Level
  • 4.7+
  • 124 reviews

Learn to use essential Bioconductor packages for bioinformatics using datasets from viruses, fungi, humans, and plants!

Probability & Statistics

4 hours

Course

NoSQL Concepts

  • IntermediateSkill Level
  • 4.8+
  • 550 reviews

In this conceptual course (no coding required), you will learn about the four major NoSQL databases and popular engines.

Data Engineering

2 hours

Course

Building a Go-To-Market Strategy

  • BasicSkill Level
  • 4.7+
  • 417 reviews

Create a go-to-market strategy with generative AI: target industries, generate leads, and optimize website keywords.

Artificial Intelligence

1 hour

Course

Reshaping Data with pandas

  • IntermediateSkill Level
  • 4.7+
  • 835 reviews

Reshape DataFrames from a wide to long format, stack and unstack rows and columns, and wrangle multi-index DataFrames.

Data Manipulation

4 hours

Course

Introduction to Portfolio Analysis in Python

  • AdvancedSkill Level
  • 4.8+
  • 376 reviews

Learn how to calculate meaningful measures of risk and performance, and how to compile an optimal portfolio for the desired risk and return trade-off.

Applied Finance

4 hours

Course

Math for Finance Professionals

  • BasicSkill Level
  • 4.8+
  • 313 reviews

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

Applied Finance

3 hours

Course

Understanding Digital Transformation

  • BasicSkill Level
  • 4.8+
  • 589 reviews

Dive into the world of digital transformation and equip yourself to be an agent of change in a rapidly evolving digital landscape.

Data Literacy

1 hour

Course

Transactions and Error Handling in SQL Server

  • IntermediateSkill Level
  • 4.8+
  • 329 reviews

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

Software Development

4 hours

Course

Time Series Analysis in SQL Server

  • IntermediateSkill Level
  • 4.7+
  • 421 reviews

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

Data Manipulation

5 hours

Course

Building Marketing Workflows with n8n

  • BasicSkill Level
  • 4.9+
  • 77 reviews

Build marketing workflows in n8n using AI agents. Automate campaign strategy, conversion optimization, and lead generation from scratch.

Artificial Intelligence

3 hours

Course

Visualizations in Sigma

  • BasicSkill Level
  • 4.8+
  • 230 reviews

Learn to build and customize Sigma charts to tell clear, compelling data stories—no coding required.

Data Visualization

2 hours

Course

Feature Engineering for NLP in Python

  • IntermediateSkill Level
  • 4.8+
  • 150 reviews

Learn techniques to extract useful information from text and process them into a format suitable for machine learning.

Machine Learning

4 hours

Course

Fraud Detection in Python

  • IntermediateSkill Level
  • 4.7+
  • 197 reviews

Learn how to detect fraud using Python.

Machine Learning

4 hours

Course

Machine Learning with PySpark

  • AdvancedSkill Level
  • 4.8+
  • 726 reviews

Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression, linear regression, ensembles, and pipelines.

Machine Learning

4 hours

Course

Statistical Thinking in Python (Part 1)

  • IntermediateSkill Level
  • 4.8+
  • 114 reviews

Build the foundation you need to think statistically and to speak the language of your data.

Probability & Statistics

3 hours

Course

Multi-Modal Systems with the OpenAI API

  • IntermediateSkill Level
  • 4.8+
  • 481 reviews

Create multi-modal systems using OpenAIs text and audio models, including an end-to-end customer support chatbot!

Artificial Intelligence

2 hours

Course

Quantitative Risk Management in Python

  • AdvancedSkill Level
  • 4.8+
  • 229 reviews

Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python.

Applied Finance

4 hours

Course

Recommending Skincare Products

  • BasicSkill Level
  • 4.7+
  • 307 reviews

Test a chatbot that matches customers with ideal skincare products using your prompting skills for personalized results.

Artificial Intelligence

1 hour

Course

Monitoring Machine Learning in Python

  • AdvancedSkill Level
  • 4.8+
  • 381 reviews

This course covers everything you need to know to build a basic machine learning monitoring system in Python

Machine Learning

3 hours

Course

Sentiment Analysis in Python

  • IntermediateSkill Level
  • 4.8+
  • 452 reviews

Are customers thrilled with your products or is your service lacking? Learn how to perform an end-to-end sentiment analysis task.

Machine Learning

4 hours

Course

Serverless Applications with AWS Lambda

  • IntermediateSkill Level
  • 4.7+
  • 38 reviews

Build, deploy, and optimize serverless apps with AWS Lambda. Master event processing, error handling, concurrency, and safe deployments in a live AWS Console.

Cloud

3 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.

Download on the App StoreGet it on Google Play