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.
771 Courses

Course

Visualizing Geospatial Data in Python

  • IntermediateSkill Level
  • 4.7+
  • 344 reviews

Learn how to make attractive visualizations of geospatial data in Python using the geopandas package and folium maps.

Data Visualization

4 hours

Course

Develop for Azure Storage

  • IntermediateSkill Level
  • 4.7+
  • 96 reviews

Learn how to store, secure, scale, and process data in Azure using Blob Storage, Cosmos DB, queues, and event-driven services.

Cloud

3 hours

Course

String Manipulation with stringr in R

  • IntermediateSkill Level
  • 4.7+
  • 54 reviews

Learn how to pull character strings apart, put them back together and use the stringr package.

Software Development

4 hours

Course

Using Data Stores in AWS

  • IntermediateSkill Level
  • 4.7+
  • 32 reviews

Learn to choose, build with, and secure AWS data stores including DynamoDB and S3 through hands-on console exercises and real-world scenarios.

Cloud

3 hours

Course

Baseball Data Visualization in Power BI

  • BasicSkill Level
  • 4.8+
  • 197 reviews

Discover how to analyze and visualize baseball data using Power BI. Create scatter plots, tornado charts, and gauges to bring baseball insights alive.

Data Visualization

1 hour

Course

Efficient AI Model Training with PyTorch

  • AdvancedSkill Level
  • 4.8+
  • 104 reviews

Learn how to reduce training times for large language models with Accelerator and Trainer for distributed training

Artificial Intelligence

4 hours

Course

Dealing with Missing Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 184 reviews

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

Data Manipulation

4 hours

Course

Case Study: Ecommerce Analysis in Power BI

  • IntermediateSkill Level
  • 4.8+
  • 206 reviews

In ecommerce, increasing sales and reducing costs are key. Analyze data from an online pet supply company using Power BI.

Data Visualization

4 hours

Course

Case Study: Supply Chain Analytics in Power BI

  • BasicSkill Level
  • 4.8+
  • 185 reviews

Learn how to use Power BI for supply chain analytics in this case study. Create a make vs. buy analysis tool, calculate costs, and analyze production volumes.

Data Visualization

4 hours

Course

ARIMA Models in R

  • BasicSkill Level
  • 4.8+
  • 315 reviews

Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.

Probability & Statistics

4 hours

Course

Decoding Decision Modeling

  • BasicSkill Level
  • 4.7+
  • 189 reviews

Elevate decision-making skills with Decision Models, analysis methods, risk management, and optimization techniques.

Data Literacy

1 hour

Course

Statistical Thinking in Python (Part 2)

  • IntermediateSkill Level
  • 4.7+
  • 256 reviews

Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.

Probability & Statistics

4 hours

Course

Introduction to Julia

  • BasicSkill Level
  • 4.8+
  • 132 reviews

Julia is a new programming language designed to be the ideal language for scientific computing, machine learning, and data mining.

Software Development

4 hours

Course

Azure API Management

  • IntermediateSkill Level
  • 4.7+
  • 80 reviews

Learn to create, secure, and manage APIs with Azure API Management through hands-on practice.

Cloud

3 hours

Course

Case Study: Inventory Analysis in Power BI

  • IntermediateSkill Level
  • 4.7+
  • 171 reviews

This Power BI case study follows a real-world business use case on tackling inventory analysis using DAX and visualizations.

Data Visualization

5 hours

Course

Survival Analysis in R

  • IntermediateSkill Level
  • 4.7+
  • 198 reviews

Learn to work with time-to-event data. The event may be death or finding a job after unemployment. Learn to estimate, visualize, and interpret survival models!

Probability & Statistics

4 hours

Course

Introduction to Linear Modeling in Python

  • IntermediateSkill Level
  • 4.7+
  • 220 reviews

Explore the concepts and applications of linear models with python and build models to describe, predict, and extract insight from data patterns.

Probability & Statistics

4 hours

Course

Web Scraping in R

  • IntermediateSkill Level
  • 4.7+
  • 99 reviews

Learn how to efficiently collect and download data from any website using R.

Data Preparation

4 hours

Course

Case Study: Data Analysis in Databricks

  • AdvancedSkill Level
  • 4.6+
  • 87 reviews

Learn to analyze Airbnb data using SQL in Databricks, create dashboards, and derive actionable insights.

Importing & Cleaning Data

3 hours

Course

Google: Enterprise Agents and Use Cases

  • BasicSkill Level
  • 4.9+
  • 70 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

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