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.
299 Courses

Course

Case Study: Exploratory Data Analysis in R

  • BasicSkill Level
  • 4.9+
  • 48 reviews

Use data manipulation and visualization skills to explore the historical voting of the United Nations General Assembly.

Exploratory Data Analysis

4 hours

Course

Google: Enterprise Agents and Use Cases

  • BasicSkill Level
  • 4.9+
  • 45 reviews

Map agent types to your KPIs and explore use cases that solve problems, learn how Gemini Enterprise empowers you to build and orchestrate the right agents.

Cloud

45 min

Course

Data Transformation in KNIME

  • BasicSkill Level
  • 4.8+
  • 284 reviews

Enhance your KNIME skills with our course on data transformation, column operations, and workflow optimization.

Data Preparation

2 hours

Course

Quantitative Risk Management in R

  • BasicSkill Level
  • 4.8+
  • 81 reviews

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

Applied Finance

5 hours

Course

Programming Paradigm Concepts

  • BasicSkill Level
  • 4.8+
  • 131 reviews

Explore a range of programming paradigms, including imperative and declarative, procedural, functional, and object-oriented programming.

Software Development

2 hours

Course

Python for Spreadsheet Users

  • BasicSkill Level
  • 4.8+
  • 34 reviews

Use your knowledge of common spreadsheet functions and techniques to explore Python!

Software Development

4 hours

Course

Google: Agent Fundamentals

  • BasicSkill Level
  • 4.8+
  • 22 reviews

Learn AI agent fundamentals — how they differ from LLMs, when to use them, and explore agent architecture, orchestration, and tools.

Cloud

1 hour

Course

Data Manipulation with data.table in R

  • BasicSkill Level
  • 4.6+
  • 21 reviews

Master core concepts about data manipulation such as filtering, selecting and calculating groupwise statistics using data.table.

Data Manipulation

4 hours

Course

Data Visualization in KNIME

  • BasicSkill Level
  • 4.8+
  • 198 reviews

Learn to create compelling data visualizations with KNIME, covering charts, components, and dashboards.

Data Visualization

2 hours

Course

Introduction to Data Engineering on Google Cloud

  • BasicSkill Level
  • 4.7+
  • 9 reviews

Learn the data engineering role on Google Cloud. Explore data sources, storage solutions, ETL/ELT architectures, BigQuery, Dataform, and Dataproc.

Cloud

3 hours 41 min

Course

Data Manipulation in KNIME

  • BasicSkill Level
  • 4.8+
  • 244 reviews

Automate data manipulation with KNIME, mastering merging, aggregation, database workflows, and advanced file handling.

Data Manipulation

3 hours

Course

Building Dashboards with shinydashboard

  • BasicSkill Level
  • 4.6+
  • 74 reviews

Learn to create interactive dashboards with R using the powerful shinydashboard package. Create dynamic and engaging visualizations for your audience.

Reporting

4 hours

Course

MLOps for Business

  • BasicSkill Level
  • 4.8+
  • 139 reviews

Learn about MLOps, including the tools and practices needed for automating and scaling machine learning applications.

Machine Learning

3 hours

Course

Python for MATLAB Users

  • BasicSkill Level
  • 4.7+
  • 29 reviews

Transition from MATLAB by learning some fundamental Python concepts, and diving into the NumPy and Matplotlib packages.

Software Development

4 hours

Course

Conditional Formatting in Google Sheets

  • BasicSkill Level
  • 4.8+
  • 97 reviews

Learn how to use conditional formatting with your data through built-in options and by creating custom formulas.

Data Manipulation

2 hours

Course

Dimensionality Reduction in R

  • BasicSkill Level
  • 4.7+
  • 96 reviews

Learn dimensionality reduction techniques in R and master feature selection and extraction for your own data and models.

Machine Learning

4 hours

Course

Working with DeepSeek in Python

  • BasicSkill Level
  • 4.7+
  • 98 reviews

Discover what all of the DeepSeek hype was really about! Build applications using DeepSeeks R1 and V3 models.

Artificial Intelligence

3 hours

Course

Google: Build and Deploy Agents in Production

  • BasicSkill Level
  • 4.8+
  • 22 reviews

Explore multi-agent system architecture and deployment using Googles ADK and Google Cloud infrastructure for production-grade agent applications.

Cloud

30 min

Course

R For SAS Users

  • BasicSkill Level
  • 4.7+
  • 27 reviews

Learn how to translate your SAS knowledge into R and analyze data using this free and powerful software language.

Software Development

4 hours

Course

Google Cloud Fundamentals: Core Infrastructure

  • BasicSkill Level
  • 4.8+
  • 7 reviews

Learn Google Cloud essentials including computing, storage, networking, and resource management through videos and hands-on labs in this foundational course.

Cloud

5 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