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.
711 Courses

Course

AI Agents with Hugging Face smolagents

  • AdvancedSkill Level
  • 4.8+
  • 230 reviews

Learn how to build intelligent agents that reason, act, and solve real-world tasks using Python.

Artificial Intelligence

3 hours

Course

Cleaning Data in PostgreSQL Databases

  • IntermediateSkill Level
  • 4.8+
  • 438 reviews

Learn to tame your raw, messy data stored in a PostgreSQL database to extract accurate insights.

Data Preparation

4 hours

Course

Introduction to Spark SQL in Python

  • AdvancedSkill Level
  • 4.7+
  • 132 reviews

Learn how to manipulate data and create machine learning feature sets in Spark using SQL in Python.

Data Manipulation

4 hours

Course

Power BI for End Users

  • BasicSkill Level
  • 4.7+
  • 300 reviews

Explore Power BI Service, master the interface, make informed decisions, and maximize the power of your reports.

Reporting

1 hour

Course

Digital Transformation with Google Cloud

  • BasicSkill Level
  • 4.8+
  • 75 reviews

This course provides an overview of the opportunities and challenges companies encounter in their digital transformation journey.

Cloud

2 hours

Course

Financial Analytics in Google Sheets

  • BasicSkill Level
  • 4.7+
  • 121 reviews

Learn how to build a graphical dashboard with Google Sheets to track the performance of financial securities.

Applied Finance

4 hours

Course

Intermediate Workflow Automation with n8n

  • IntermediateSkill Level
  • 4.7+
  • 34 reviews

Design resilient, production-ready n8n automations that fetch APIs, process data in batches, handle errors, and run unattended on a schedule.

Artificial Intelligence

4 hours

Course

Foundations of Probability in R

  • BasicSkill Level
  • 4.8+
  • 432 reviews

In this course, youll learn about the concepts of random variables, distributions, and conditioning.

Probability & Statistics

4 hours

Course

Foundations of Probability in Python

  • IntermediateSkill Level
  • 4.8+
  • 198 reviews

Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.

Probability & Statistics

5 hours

Course

Dealing With Missing Data in R

  • BasicSkill Level
  • 4.7+
  • 135 reviews

Make it easy to visualize, explore, and impute missing data with naniar, a tidyverse friendly approach to missing data.

Data Preparation

4 hours

Course

Introduction to Subagents

  • IntermediateSkill Level
  • 4.9+
  • 61 reviews

Learn how to use and create sub-agents in Claude Code to manage context, delegate tasks, and build workflows that keep your conversation clean and focused.

Artificial Intelligence

2 hours

Course

Ensemble Methods in Python

  • AdvancedSkill Level
  • 4.8+
  • 384 reviews

Learn how to build advanced and effective machine learning models in Python using ensemble techniques such as bagging, boosting, and stacking.

Machine Learning

4 hours

Course

Machine Learning with caret in R

  • IntermediateSkill Level
  • 4.9+
  • 41 reviews

This course teaches the big ideas in machine learning like how to build and evaluate predictive models.

Machine Learning

4 hours

Course

Introduction to TensorFlow in Python

  • IntermediateSkill Level
  • 4.8+
  • 52 reviews

Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.

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

Statistical Techniques in Tableau

  • IntermediateSkill Level
  • 4.8+
  • 628 reviews

Take your reporting skills to the next level with Tableau’s built-in statistical functions.

Probability & Statistics

4 hours

Course

Introduction to Portfolio Analysis in Python

  • AdvancedSkill Level
  • 4.8+
  • 327 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

Experimental Design in R

  • IntermediateSkill Level
  • 4.7+
  • 308 reviews

In this course youll learn about basic experimental design, a crucial part of any data analysis.

Probability & Statistics

4 hours

Course

Demystifying Decision Science

  • BasicSkill Level
  • 4.8+
  • 264 reviews

Solidify your decision science skills by designing data-informed frameworks and implementing efficient solutions.

Data Literacy

1 hour

Course

Supervised Learning in R: Regression

  • IntermediateSkill Level
  • 4.6+
  • 97 reviews

In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

Machine Learning

4 hours

Course

Data Types and Functions in Snowflake

  • IntermediateSkill Level
  • 4.8+
  • 457 reviews

Learn Snowflake data types and functions to manipulate text, numbers, and dates while building custom functions and pivot tables.

Data Manipulation

3 hours

Course

Monitoring Machine Learning Concepts

  • IntermediateSkill Level
  • 4.7+
  • 442 reviews

Learn about the challenges of monitoring machine learning models in production, including data and concept drift, and methods to address model degradation.

Machine Learning

2 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.