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

Scalable AI Models with PyTorch Lightning

  • IntermediateSkill Level
  • 4.7+
  • 105 reviews

Streamline your AI projects by building modular models and mastering advanced optimization with PyTorch Lightning!

Artificial Intelligence

3 hours

Course

Intermediate Power Automate

  • IntermediateSkill Level
  • 4.8+
  • 12 reviews

Build reliable Power Automate cloud flows with triggers, branching, approvals, error handling, and production handover.

Artificial Intelligence

3 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

Generalized Linear Models in R

  • IntermediateSkill Level
  • 4.8+
  • 196 reviews

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

Probability & Statistics

4 hours

Course

Python for Spreadsheet Users

  • BasicSkill Level
  • 4.8+
  • 35 reviews

Use your knowledge of common spreadsheet functions and techniques to explore Python!

Software Development

4 hours

Course

Intermediate R for Finance

  • BasicSkill Level
  • 4.8+
  • 41 reviews

Learn about how dates work in R, and explore the world of if statements, loops, and functions using financial examples.

Applied Finance

5 hours

Course

Machine Learning with caret in R

  • IntermediateSkill Level
  • 4.8+
  • 43 reviews

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

Machine Learning

4 hours

Course

Concepts in Computer Science

  • BasicSkill Level
  • 4.7+
  • 178 reviews

Learn how computers work, design efficient algorithms, and explore computational theory to solve real-world problems.

Software Development

3 hours

Course

GARCH Models in Python

  • IntermediateSkill Level
  • 4.8+
  • 191 reviews

Learn about GARCH Models, how to implement them and calibrate them on financial data from stocks to foreign exchange.

Applied Finance

4 hours

Course

Building Data Pipelines with Airflow

  • AdvancedSkill Level
  • 4.6+
  • 12 reviews

Author Dags with the TaskFlow API, asset-based scheduling, and deferrable sensors, and run an end-to-end SQL ETL pipeline with quality checks.

Data Engineering

4 hours

Course

Case Study: Exploratory Data Analysis in R

  • BasicSkill Level
  • 4.9+
  • 49 reviews

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

Exploratory Data Analysis

4 hours

Course

Advanced Data Engineering with Snowflake

  • IntermediateSkill Level
  • 4.8+
  • 21 reviews

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

Data Engineering

3 hours

Course

Cleaning Data in SQL Server Databases

  • IntermediateSkill Level
  • 4.8+
  • 187 reviews

Develop the skills you need to clean raw data and transform it into accurate insights.

Data Preparation

4 hours

Course

Analyzing Social Media Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 32 reviews

In this course, youll learn how to collect Twitter data and analyze Twitter text, networks, and geographical origin.

Data Manipulation

4 hours

Course

Image Modeling with Keras

  • AdvancedSkill Level
  • 4.8+
  • 90 reviews

Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.

Artificial Intelligence

4 hours

Course

Introduction to Redshift

  • IntermediateSkill Level
  • 4.8+
  • 107 reviews

Master Amazon Redshifts SQL, data management, optimization, and security.

Data Engineering

4 hours

Course

Advanced Probability: Uncertainty in Data

  • AdvancedSkill Level
  • 4.8+
  • 155 reviews

Develop a better intuition for advanced probability, risk assessment, and simulation techniques to make data-driven business decisions with confidence.

Probability & Statistics

2 hours

Course

Essential Google Cloud Infrastructure: Foundation

  • IntermediateSkill Level
  • 4.8+
  • 36 reviews

This course introduces the comprehensive and flexible infrastructure and platform services provided by Google Cloud with a focus on Infrastructure Foundations.

Cloud

4 hours 45 min

Course

Introduction to Scala

  • IntermediateSkill Level
  • 4.8+
  • 141 reviews

Begin your journey with Scala, a popular language for scalable applications and data engineering infrastructure.

Software Development

3 hours

Course

Categorical Data in the Tidyverse

  • BasicSkill Level
  • 4.7+
  • 173 reviews

Get ready to categorize! In this course, you will work with non-numerical data, such as job titles or survey responses, using the Tidyverse landscape.

Data Manipulation

4 hours

Course

Machine Learning for Marketing in Python

  • IntermediateSkill Level
  • 4.8+
  • 174 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

Writing Efficient Code with pandas

  • IntermediateSkill Level
  • 4.7+
  • 156 reviews

Learn efficient techniques in pandas to optimize your Python code.

Software Development

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