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.
349 Courses

Course

Azure App Services

  • IntermediateSkill Level
  • 4.7+
  • 122 reviews

Build and deploy scalable web apps and serverless functions in Azure while mastering security, monitoring, and automation.

Cloud

3 hours

Course

Introduction to Bash Scripting

  • IntermediateSkill Level
  • 4.8+
  • 473 reviews

Bash scripting allows you to build analytics pipelines in the cloud and work with data stored across multiple files.

Software Development

4 hours

Course

Time Series Analysis in Python

  • IntermediateSkill Level
  • 4.8+
  • 134 reviews

In this four-hour course, you’ll learn the basics of analyzing time series data in Python.

Probability & Statistics

4 hours

Course

Introduction to Apache Kafka

  • IntermediateSkill Level
  • 4.7+
  • 854 reviews

Master Apache Kafka! From core concepts to advanced architecture, learn to create, manage, and troubleshoot Kafka for real-world data streaming challenges!

Data Engineering

2 hours

Course

Developing Python Packages

  • IntermediateSkill Level
  • 4.7+
  • 907 reviews

Learn to create your own Python packages to make your code easier to use and share with others.

Software Development

4 hours

Course

Intermediate SQL Server

  • IntermediateSkill Level
  • 4.8+
  • 230 reviews

In this course, you will use T-SQL, the flavor of SQL used in Microsofts SQL Server for data analysis.

Software Development

4 hours

Course

Introduction to BigQuery

  • IntermediateSkill Level
  • 4.8+
  • 428 reviews

Unlock BigQuerys power: grasp its fundamentals, execute queries, and optimize workflows for efficient data analysis.

Data Engineering

4 hours

Course

Sampling in R

  • IntermediateSkill Level
  • 4.7+
  • 831 reviews

Master sampling to get more accurate statistics with less data.

Probability & Statistics

4 hours

Course

End-to-End Machine Learning

  • IntermediateSkill Level
  • 4.7+
  • 342 reviews

Dive into the world of machine learning and discover how to design, train, and deploy end-to-end models.

Machine Learning

4 hours

Course

Input/Output and Streams in Java

  • IntermediateSkill Level
  • 4.8+
  • 384 reviews

Advance your Java skills by learning to handle files, process data, and build clean, reusable code using real-world techniques.

Software Development

4 hours

Course

Cluster Analysis in Python

  • IntermediateSkill Level
  • 4.8+
  • 960 reviews

In this course, you will be introduced to unsupervised learning through techniques such as hierarchical and k-means clustering using the SciPy library.

Machine Learning

4 hours

Course

Model Validation in Python

  • IntermediateSkill Level
  • 4.8+
  • 842 reviews

Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.

Machine Learning

4 hours

Course

Reshaping Data with tidyr

  • IntermediateSkill Level
  • 4.8+
  • 453 reviews

Transform almost any dataset into a tidy format to make analysis easier.

Data Manipulation

4 hours

Course

Writing Efficient R Code

  • IntermediateSkill Level
  • 4.7+
  • 135 reviews

Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.

Software Development

4 hours

Course

Introduction to MongoDB in Python

  • IntermediateSkill Level
  • 4.7+
  • 360 reviews

Learn to manipulate and analyze flexibly structured data with MongoDB.

Data Engineering

3 hours

Course

Credit Risk Modeling in Python

  • IntermediateSkill Level
  • 4.7+
  • 277 reviews

Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability.

Applied Finance

4 hours

Course

Reporting in SQL

  • IntermediateSkill Level
  • 4.8+
  • 786 reviews

Learn how to build your own SQL reports and dashboards, plus hone your data exploration, cleaning, and validation skills.

Reporting

4 hours

Course

Introduction to Databases in Python

  • IntermediateSkill Level
  • 4.7+
  • 268 reviews

In this course, youll learn the basics of relational databases and how to interact with them.

Data Manipulation

4 hours

Course

Introduction to Subagents

  • IntermediateSkill Level
  • 4.8+
  • 114 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

Introduction to Generative AI in Snowflake

  • IntermediateSkill Level
  • 4.8+
  • 345 reviews

Learn to build AI applications using Snowflake Cortexs built-in LLM functions for text analysis, generation, and multi-step workflows.

Artificial Intelligence

2 hours

Course

Hyperparameter Tuning in Python

  • IntermediateSkill Level
  • 4.8+
  • 789 reviews

Learn techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.

Machine Learning

4 hours

Course

Time Series Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 88 reviews

Learn the core techniques necessary to extract meaningful insights from time series data.

Probability & Statistics

4 hours

Course

Sentiment Analysis in Python

  • IntermediateSkill Level
  • 4.8+
  • 434 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

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