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

LegalSnippet.text
726 Courses

Course

Streaming Data with AWS Kinesis and Lambda

  • AdvancedSkill Level
  • 4.7+
  • 164 reviews

Learn how to work with streaming data using serverless technologies on AWS.

Cloud

4 hours

Course

Ensemble Methods in Python

  • AdvancedSkill Level
  • 4.8+
  • 388 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

Understanding Digital Transformation

  • BasicSkill Level
  • 4.8+
  • 534 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

Intermediate Importing Data in R

  • IntermediateSkill Level
  • 4.8+
  • 268 reviews

Parse data in any format. Whether its flat files, statistical software, databases, or data right from the web.

Data Preparation

3 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

Cluster Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 69 reviews

Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.

Machine Learning

4 hours

Course

Introduction to GCP

  • BasicSkill Level
  • 4.7+
  • 336 reviews

Get to know the Google Cloud Platform (GCP) with this course on storage, data handling, and business modernization using GCP.

Cloud

2 hours

Course

Foundations of PySpark

  • IntermediateSkill Level
  • 4.7+
  • 600 reviews

Learn to implement distributed data management and machine learning in Spark using the PySpark package.

Data Engineering

4 hours

Course

Demystifying Decision Science

  • BasicSkill Level
  • 4.8+
  • 265 reviews

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

Data Literacy

1 hour

Course

Data Modeling in Sigma

  • BasicSkill Level
  • 4.8+
  • 89 reviews

Stop rewriting the same joins and calculations, and dive into well-governed, scalable analytics using Sigma data models.

Reporting

2 hours

Course

Visualizing Time Series Data in R

  • IntermediateSkill Level
  • 4.8+
  • 174 reviews

Learn how to visualize time series in R, then practice with a stock-picking case study.

Data Visualization

4 hours

Course

Spoken Language Processing in Python

  • AdvancedSkill Level
  • 4.8+
  • 256 reviews

Learn how to load, transform, and transcribe speech from raw audio files in Python.

Data Manipulation

4 hours

Course

Fully Automated MLOps

  • IntermediateSkill Level
  • 4.8+
  • 322 reviews

Learn about MLOps architecture, CI/CD/CM/CT techniques, and automation patterns to deploy ML systems that can deliver value over time.

Machine Learning

4 hours

Course

RNA-Seq with Bioconductor in R

  • IntermediateSkill Level
  • 4.7+
  • 138 reviews

Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.

Probability & Statistics

4 hours

Course

Graph RAG with LangChain and Neo4j

  • AdvancedSkill Level
  • 4.7+
  • 97 reviews

Create more accurate and reliable RAG systems with Graph RAG and hybrid RAG.

Artificial Intelligence

3 hours

Course

Machine Learning with caret in R

  • IntermediateSkill Level
  • 4.8+
  • 42 reviews

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

Machine Learning

4 hours

Course

Multi-Modal Systems with the OpenAI API

  • IntermediateSkill Level
  • 4.8+
  • 435 reviews

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

Artificial Intelligence

2 hours

Course

Recommending Skincare Products

  • BasicSkill Level
  • 4.7+
  • 267 reviews

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

Artificial Intelligence

1 hour

Course

Introduction to Testing in Java

  • AdvancedSkill Level
  • 4.8+
  • 152 reviews

Learn how to write effective tests in Java using JUnit and Mockito to build robust, reliable applications with confidence.

Software Development

3 hours

Course

Window Functions in Snowflake

  • IntermediateSkill Level
  • 4.8+
  • 465 reviews

Discover Snowflake window functions to solve complex data problems with rankings, partitions, and rolling calculations.

Data Manipulation

3 hours

Course

Introduction to AWS Boto in Python

  • IntermediateSkill Level
  • 4.8+
  • 206 reviews

Learn about AWS Boto and harnessing cloud technology to optimize your data workflow.

Cloud

4 hours

Course

Corporate Finance Fundamentals

  • BasicSkill Level
  • 4.8+
  • 219 reviews

Learn key financial concepts such as capital investment, WACC, and shareholder value.

Applied Finance

2 hours

Course

Streaming Concepts

  • BasicSkill Level
  • 4.7+
  • 478 reviews

Learn about the difference between batching and streaming, scaling streaming systems, and real-world applications.

Data Engineering

2 hours

Course

Calculations in Sigma

  • BasicSkill Level
  • 4.9+
  • 135 reviews

Build dynamic Sigma calculations to explore data, automate logic, and uncover trends with practical business examples.

Data Manipulation

2 hours

Course

Introduction to AI Apps in Sigma

  • BasicSkill Level
  • 4.9+
  • 118 reviews

Build interactive AI apps in Sigma using user input, actions, and polished interfaces, no coding required.

Reporting

2 hours

Course

Dealing with Missing Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 178 reviews

Learn how to identify, analyze, remove and impute missing data in Python.

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.