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.
772 Courses

Course

Transactions and Error Handling in PostgreSQL

  • IntermediateSkill Level
  • 4.8+
  • 99 reviews

Ensure data consistency by learning how to use transactions and handle errors in concurrent environments.

Software Development

4 hours

Course

Generative AI Essentials with Snowflake

  • IntermediateSkill Level
  • 4.5+
  • 14 reviews

Build generative AI apps on Snowflake with Cortex LLM functions, prompt engineering, and fine-tuning.

Artificial Intelligence

3 hours

Course

Case Study: Mortgage Trading Analysis in Power BI

  • IntermediateSkill Level
  • 4.8+
  • 277 reviews

In this Power BI case study you’ll play the role of a junior trader, analyzing mortgage trading and enhancing your data modeling and financial analysis skills.

Applied Finance

3 hours

Course

Case Study: Exploratory Data Analysis in R

  • BasicSkill Level
  • 4.9+
  • 48 reviews

Use data manipulation and visualization skills to explore the historical voting of the United Nations General Assembly.

Exploratory Data Analysis

4 hours

Course

Machine Learning in the Tidyverse

  • IntermediateSkill Level
  • 4.8+
  • 114 reviews

Leverage tidyr and purrr packages in the tidyverse to generate, explore, and evaluate machine learning models.

Machine Learning

5 hours

Course

Introduction to Linear Modeling in Python

  • IntermediateSkill Level
  • 4.7+
  • 218 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

Building Chatbots in Python

  • IntermediateSkill Level
  • 4.7+
  • 149 reviews

Learn the fundamentals of how to build conversational bots using rule-based systems as well as machine learning.

Machine Learning

4 hours

Course

Analyzing Financial Statements in Python

  • IntermediateSkill Level
  • 4.7+
  • 112 reviews

Learn to analyze financial statements using Python. Compute ratios, assess financial health, handle missing values, and present your analysis.

Applied Finance

4 hours

Course

Machine Learning for Marketing in Python

  • IntermediateSkill Level
  • 4.8+
  • 172 reviews

From customer lifetime value, predicting churn to segmentation - learn and implement Machine Learning use cases for Marketing in Python.

Machine Learning

4 hours

Course

Modeling with tidymodels in R

  • IntermediateSkill Level
  • 4.8+
  • 178 reviews

Learn to streamline your machine learning workflows with tidymodels.

Machine Learning

4 hours

Course

End-to-End RAG with Weaviate

  • IntermediateSkill Level
  • 4.6+
  • 18 reviews

Master RAG with Weaviate! Embed text and images for retrieval, and experiment with vector, BM25, and hybrid search.

Artificial Intelligence

2 hours

Course

Credit Risk Modeling in R

  • IntermediateSkill Level
  • 4.7+
  • 86 reviews

Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.

Applied Finance

4 hours

Course

Monitor and Troubleshoot Azure Solutions

  • IntermediateSkill Level
  • 4.7+
  • 74 reviews

Learn how to monitor, diagnose, and optimize Azure applications using Azure Monitor, Application Insights, and Log Analytics.

Cloud

3 hours

Course

A/B Testing in R

  • IntermediateSkill Level
  • 4.8+
  • 90 reviews

Learn the basics of A/B testing in R, including how to design experiments, analyze data, predict outcomes, and present results through visualizations.

Probability & Statistics

4 hours

Course

Handling Missing Data with Imputations in R

  • AdvancedSkill Level
  • 4.7+
  • 104 reviews

Diagnose, visualize and treat missing data with a range of imputation techniques with tips to improve your results.

Data Manipulation

4 hours

Course

Programming Paradigm Concepts

  • BasicSkill Level
  • 4.8+
  • 134 reviews

Explore a range of programming paradigms, including imperative and declarative, procedural, functional, and object-oriented programming.

Software Development

2 hours

Course

Building Dashboards with shinydashboard

  • BasicSkill Level
  • 4.7+
  • 78 reviews

Learn to create interactive dashboards with R using the powerful shinydashboard package. Create dynamic and engaging visualizations for your audience.

Reporting

4 hours

Course

Importing Data in Java

  • IntermediateSkill Level
  • 4.8+
  • 58 reviews

Learn to import, manipulate, and transform data in Java using the Tablesaw library. Work with CSV files, tabular structures, and complex JSON formats.

Software Development

3 hours

Course

Advanced Data Engineering with Snowflake

  • IntermediateSkill Level
  • 4.8+
  • 18 reviews

Build reliable Snowflake pipelines with DevOps and observability: Git, CI/CD, and Snowflake Trail monitoring.

Data Engineering

3 hours

Course

Querying a PostgreSQL Database in Java

  • AdvancedSkill Level
  • 4.8+
  • 90 reviews

Connect Java to PostgreSQL with JDBC. Write secure queries, manage transactions, and handle large datasets efficiently.

Software Development

3 hours

Course

Python for R Users

  • IntermediateSkill Level
  • 4.7+
  • 79 reviews

This course is for R users who want to get up to speed with Python!

Software Development

5 hours

Course

Generalized Linear Models in Python

  • AdvancedSkill Level
  • 4.7+
  • 144 reviews

Extend your regression toolbox with the logistic and Poisson models and learn to train, understand, and validate them, as well as to make predictions.

Probability & Statistics

5 hours

Course

Inference for Numerical Data in R

  • AdvancedSkill Level
  • 4.8+
  • 106 reviews

In this course youll learn techniques for performing statistical inference on numerical data.

Probability & Statistics

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