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.
778 Courses

Course

Google Workspace End User: Google Sheets

  • BasicSkill Level
  • 4.8+
  • 18 reviews

Learn to create and edit spreadsheets in Google Sheets, work with data, build formulas, and collaborate in real time.

Cloud

6 hours 30 min

Course

DataLab with SQL

  • BasicSkill Level
  • 4.8+
  • 45 reviews

Elevate your analysis with this hands-on course using SQL with DataLab workbooks.

Reporting

1 hour

Course

Google Workspace End User: Google Calendar

  • BasicSkill Level
  • 4.8+
  • 18 reviews

Learn to create and manage events, schedule meetings, share calendars, and use tasks and reminders to stay organized.

Cloud

4 hours 45 min

Course

Case Study: Analyzing Fitness Data in Alteryx

  • IntermediateSkill Level
  • 4.8+
  • 57 reviews

Advance your Alteryx skills with real fitness data to develop targeted marketing strategies and innovative products!

Data Preparation

3 hours

Course

AI Infrastructure: Networking Techniques

  • IntermediateSkill Level
  • 4.8+
  • 12 reviews

Design and deploy high-performance AI/ML solutions using Google Clouds AI Hypercomputer, GPUs, TPUs, Compute, and Google Kubernetes Engine.

Cloud

1 hour

Course

Production Machine Learning Systems

  • IntermediateSkill Level
  • 5
  • 8 reviews

Learn how to implement the various flavors of ML: static, dynamic, and continuous training; static and dynamic inference; and batch and online processing.

Cloud

16 hours

Course

Defensive R Programming

  • IntermediateSkill Level
  • 4.8+
  • 78 reviews

Learn defensive programming in R to make your code more robust.

Software Development

4 hours

Course

Building Dashboards with flexdashboard

  • IntermediateSkill Level
  • 4.7+
  • 51 reviews

In this course youll learn how to create static and interactive dashboards using flexdashboard and shiny.

Reporting

4 hours

Course

Intermediate Regular Expressions in R

  • IntermediateSkill Level
  • 4.8+
  • 34 reviews

Manipulate text data, analyze it and more by mastering regular expressions and string distances in R.

Software Development

4 hours

Course

Intermediate Julia

  • BasicSkill Level
  • 4.7+
  • 83 reviews

Take your Julia skills to the next level with our intermediate Julia course. Learn about loops, advanced data structures, timing, and more.

Software Development

4 hours

Course

Google Workspace End User: Google Docs

  • BasicSkill Level
  • 4.8+
  • 18 reviews

Learn to create, format, and collaborate on documents in real time using Google Docs, stored securely in the cloud.

Cloud

4 hours 30 min

Course

Joining Data with data.table in R

  • IntermediateSkill Level
  • 4.8+
  • 73 reviews

This course will show you how to combine and merge datasets with data.table.

Data Manipulation

4 hours

Course

Google Workspace End User: Google Meet

  • BasicSkill Level
  • 4.8+
  • 19 reviews

Learn to schedule, host, and manage video meetings in Google Meet, including screen sharing and collaboration tools.

Cloud

5 hours 30 min

Course

Introduction to Gemini Enterprise

  • BasicSkill Level
  • 4.9+
  • 14 reviews

Gemini Enteprise brings together AI agents, enterprise search, NotebookLM, and intelligent data access to solve organizational challenges.

Cloud

2 hours 15 min

Course

Analyzing US Census Data in R

  • IntermediateSkill Level
  • 4.8+
  • 38 reviews

Learn to rapidly visualize and explore demographic data from the United States Census Bureau using tidyverse tools.

Exploratory Data Analysis

4 hours

Course

Analyzing Social Media Data in R

  • IntermediateSkill Level
  • 4.8+
  • 90 reviews

Extract and visualize Twitter data, perform sentiment and network analysis, and map the geolocation of your tweets.

Data Manipulation

4 hours

Course

Architecting with Google Kubernetes Engine: Production

  • IntermediateSkill Level
  • 4.8+
  • 11 reviews

Secure and monitor GKE production environments. Learn access control, logging, monitoring, CI/CD pipelines, and managed storage integration on Google Cloud.

Cloud

3 hours 30 min

Course

Manage Scalable Workloads in GKE

  • AdvancedSkill Level
  • 4.7+
  • 8 reviews

Scale and manage multi-cluster GKE environments. Master fleets, Cloud Service Mesh, identity management, CI/CD at scale, and GKE Enterprise capabilities.

Cloud

7 hours 20 min

Course

Practicing Statistics Interview Questions in R

  • AdvancedSkill Level
  • 4.7+
  • 23 reviews

In this course, youll prepare for the most frequently covered statistical topics from distributions to hypothesis testing, regression models, and much more.

Probability & Statistics

4 hours

Course

Work with Gemini Models in BigQuery

  • IntermediateSkill Level
  • 4.8+
  • 15 reviews

Work with Gemini AI models in BigQuery for sentiment analysis. Analyze customer reviews using SQL and Python notebooks with Gemini.

Cloud

1 hour

Course

Bayesian Modeling with RJAGS

  • AdvancedSkill Level
  • 4.8+
  • 51 reviews

In this course, youll learn how to implement more advanced Bayesian models using RJAGS.

Probability & Statistics

4 hours

Course

AI Infrastructure: Cloud GPUs

  • IntermediateSkill Level
  • 5
  • 8 reviews

Well explore how CPUs, GPUs, and TPUs make AI tasks super fast, what makes each one unique, and how AI software gets the most out of them.

Cloud

1 hour

Course

Optimizing R Code with Rcpp

  • IntermediateSkill Level
  • 4.9+
  • 12 reviews

Use C++ to dramatically boost the performance of your R code.

Software Development

4 hours

Course

Pandas Joins for Spreadsheet Users

  • IntermediateSkill Level
  • 4.7+
  • 55 reviews

Learn how to effectively and efficiently join datasets in tabular format using the Python Pandas library.

Data Manipulation

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.

Download on the App StoreGet it on Google Play