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.
179 Courses

Course

Financial Trading in Python

  • IntermediateSkill Level
  • 4.8+
  • 311 reviews

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

Applied Finance

4 hours

Course

Building AI Agents with Google ADK

  • IntermediateSkill Level
  • 4.8+
  • 594 reviews

Build a customer-support assistant step-by-step with Google’s Agent Development Kit (ADK).

Artificial Intelligence

1 hour

Course

Introduction to Portfolio Analysis in Python

  • AdvancedSkill Level
  • 4.8+
  • 408 reviews

Learn how to calculate meaningful measures of risk and performance, and how to compile an optimal portfolio for the desired risk and return trade-off.

Applied Finance

4 hours

Course

Regular Expressions in Python

  • BasicSkill Level
  • 4.7+
  • 221 reviews

Learn about string manipulation and become a master at using regular expressions.

Software Development

4 hours

Course

Image Processing in Python

  • IntermediateSkill Level
  • 4.8+
  • 226 reviews

Learn to process, transform, and manipulate images at your will.

Machine Learning

4 hours

Course

Introduction to Portfolio Risk Management in Python

  • IntermediateSkill Level
  • 4.8+
  • 385 reviews

Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.

Applied Finance

4 hours

Course

End-to-End Machine Learning

  • IntermediateSkill Level
  • 4.7+
  • 398 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

Extreme Gradient Boosting with XGBoost

  • IntermediateSkill Level
  • 4.8+
  • 282 reviews

Learn the fundamentals of gradient boosting and build state-of-the-art machine learning models using XGBoost to solve classification and regression problems.

Machine Learning

4 hours

Course

A/B Testing in Python

  • IntermediateSkill Level
  • 4.7+
  • 411 reviews

Learn the practical uses of A/B testing in Python to run and analyze experiments. Master p-values, sanity checks, and analysis to guide business decisions.

Probability & Statistics

4 hours

Course

Cluster Analysis in Python

  • IntermediateSkill Level
  • 4.8+
  • 1,094 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

Analyzing Marketing Campaigns with pandas

  • BasicSkill Level
  • 4.8+
  • 446 reviews

Build up your pandas skills and answer marketing questions by merging, slicing, visualizing, and more!

Exploratory Data Analysis

4 hours

Course

Credit Risk Modeling in Python

  • IntermediateSkill Level
  • 4.7+
  • 313 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

Data Transformation with Polars

  • IntermediateSkill Level
  • 4.8+
  • 162 reviews

Take Polars further with text manipulation, rolling statistics, DataFrame joins, and advanced analytics.

Data Manipulation

4 hours

Course

Developing Python Packages

  • IntermediateSkill Level
  • 4.7+
  • 1,022 reviews

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

Software Development

4 hours

Course

Model Validation in Python

  • IntermediateSkill Level
  • 4.8+
  • 994 reviews

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

Machine Learning

4 hours

Course

Dimensionality Reduction in Python

  • IntermediateSkill Level
  • 4.8+
  • 981 reviews

Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.

Machine Learning

4 hours

Course

Statistical Thinking in Python (Part 1)

  • IntermediateSkill Level
  • 4.8+
  • 120 reviews

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

Probability & Statistics

3 hours

Course

Introduction to Databases in Python

  • IntermediateSkill Level
  • 4.8+
  • 316 reviews

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

Data Manipulation

4 hours

Course

Quantitative Risk Management in Python

  • AdvancedSkill Level
  • 4.8+
  • 255 reviews

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

Applied Finance

4 hours

Course

Building AI Agents with CrewAI

  • IntermediateSkill Level
  • 4.7+
  • 113 reviews

Build AI teams that work together, automate workflows, and generate content with CrewAI.

Artificial Intelligence

1 hour

Course

Natural Language Processing with spaCy

  • IntermediateSkill Level
  • 4.7+
  • 682 reviews

Master the core operations of spaCy and train models for natural language processing. Extract information from unstructured data and match patterns.

Machine Learning

4 hours

Course

Market Basket Analysis in Python

  • IntermediateSkill Level
  • 4.8+
  • 303 reviews

Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations.

Machine Learning

4 hours

Course

Feature Engineering for NLP in Python

  • IntermediateSkill Level
  • 4.8+
  • 157 reviews

Learn techniques to extract useful information from text and process them into a format suitable for machine learning.

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