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

Introduction to Generative AI in Snowflake

  • IntermediateSkill Level
  • 4.8+
  • 322 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

Gemini in Google Sheets

  • BasicSkill Level
  • 4.8+
  • 130 reviews

Analyze data smarter with Gemini in Google Sheets. Use AI-powered insights, formula suggestions, and automation to simplify spreadsheets and boost productivity.

Artificial Intelligence

30 min

Course

User-Oriented Design in Power BI

  • IntermediateSkill Level
  • 4.7+
  • 397 reviews

Learn how to design Power BI visualizations and reports with users in mind.

Data Visualization

2 hours

Course

Statistical Thinking in Python (Part 1)

  • IntermediateSkill Level
  • 4.8+
  • 106 reviews

Build the foundation you need to think statistically and to speak the language of your data.

Probability & Statistics

3 hours

Course

Introduction to Oracle SQL

  • BasicSkill Level
  • 4.8+
  • 239 reviews

Sharpen your skills in Oracle SQL including SQL basics, aggregating, combining, and customizing data.

Data Manipulation

4 hours

Course

Introduction to Polars

  • BasicSkill Level
  • 4.8+
  • 377 reviews

Learn how to efficiently transform, clean, and analyze data using Polars, a Python library for fast data manipulation.

Data Manipulation

3 hours

Course

Deep Reinforcement Learning in Python

  • AdvancedSkill Level
  • 4.8+
  • 264 reviews

Learn and use powerful Deep Reinforcement Learning algorithms, including refinement and optimization techniques.

Artificial Intelligence

4 hours

Course

AI for Sales

  • BasicSkill Level
  • 4.7+
  • 87 reviews

Tackle your sales work in an AI-first way! Learn to automate prospecting, draft personalized emails, and streamline CRM tasks using AI.

Artificial Intelligence

1 hour 40 min

Course

Introduction to Optimization in Python

  • IntermediateSkill Level
  • 4.7+
  • 181 reviews

Learn to solve real-world optimization problems using Pythons SciPy and PuLP, covering everything from basic to constrained and complex optimization.

Software Development

4 hours

Course

Financial Trading in Python

  • IntermediateSkill Level
  • 4.8+
  • 271 reviews

Learn to implement custom trading strategies in Python, backtest them, and evaluate their performance!

Applied Finance

4 hours

Course

Building a Go-To-Market Strategy

  • BasicSkill Level
  • 4.7+
  • 359 reviews

Create a go-to-market strategy with generative AI: target industries, generate leads, and optimize website keywords.

Artificial Intelligence

1 hour

Course

Case Study: Analyzing Job Market Data in Power BI

  • BasicSkill Level
  • 4.8+
  • 308 reviews

Help a fictional company in this interactive Power BI case study. You’ll use Power Query, DAX, and dashboards to identify the most in-demand data jobs!

Data Manipulation

4 hours

Course

Unsupervised Learning in R

  • IntermediateSkill Level
  • 4.7+
  • 96 reviews

This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

Machine Learning

4 hours

Course

Foundations of Inference in R

  • IntermediateSkill Level
  • 4.7+
  • 50 reviews

Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.

Probability & Statistics

4 hours

Course

Quantitative Risk Management in Python

  • AdvancedSkill Level
  • 4.8+
  • 206 reviews

Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python.

Applied Finance

4 hours

Course

Generalized Linear Models in R

  • IntermediateSkill Level
  • 4.8+
  • 182 reviews

The Generalized Linear Model course expands your regression toolbox to include logistic and Poisson regression.

Probability & Statistics

4 hours

Course

Gemini in Google Drive

  • BasicSkill Level
  • 4.8+
  • 128 reviews

Organize and manage files with Gemini in Google Drive. Use AI-powered search to quickly find information, streamline collaboration, and boost productivity.

Artificial Intelligence

30 min

Course

Introduction to Agent Skills

  • IntermediateSkill Level
  • 4.9+
  • 37 reviews

Learn how to build, configure, and share Skills in Claude Code — reusable markdown instructions that Claude automatically applies to tasks at the right time.

Artificial Intelligence

2 hours 30 min

Course

Improving Query Performance in SQL Server

  • IntermediateSkill Level
  • 4.8+
  • 380 reviews

In this course, students will learn to write queries that are both efficient and easy to read and understand.

Software Development

4 hours

Course

Cleaning Data in PostgreSQL Databases

  • IntermediateSkill Level
  • 4.8+
  • 434 reviews

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

Data Preparation

4 hours

Course

Foundations of Probability in R

  • BasicSkill Level
  • 4.8+
  • 431 reviews

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

Probability & Statistics

4 hours

Course

Visualizations in Sigma

  • BasicSkill Level
  • 4.8+
  • 155 reviews

Learn to build and customize Sigma charts to tell clear, compelling data stories—no coding required.

Data Visualization

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.