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711 Courses

Course

Advanced AI-Assisted Coding for Developers

  • AdvancedSkill Level
  • 4.9+
  • 40 reviews

Learn to use AI as a senior engineering partner for code analysis, performance optimization, security, and software architecture decisions.

Artificial Intelligence

1 hour 30 min

Course

Data Modeling in Sigma

  • BasicSkill Level
  • 4.8+
  • 76 reviews

Stop rewriting the same joins and calculations, and dive into well-governed, scalable analytics using Sigma data models.

Reporting

2 hours

Course

ARIMA Models in Python

  • AdvancedSkill Level
  • 4.8+
  • 381 reviews

Learn about ARIMA models in Python and become an expert in time series analysis.

Machine Learning

4 hours

Course

Google: Introduction to AI Agents

  • BasicSkill Level
  • 4.8+
  • 75 reviews

Gain an overview of AI Agents. Discover how AI Agents use autonomous action and reasoning to solve complex problems.

Cloud

20 min

Course

Data Processing in Shell

  • IntermediateSkill Level
  • 4.8+
  • 476 reviews

Learn powerful command-line skills to download, process, and transform data, including machine learning pipeline.

Data Manipulation

4 hours

Course

Visualizing Geospatial Data in Python

  • IntermediateSkill Level
  • 4.7+
  • 325 reviews

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

Data Visualization

4 hours

Course

Introduction to AI Apps in Sigma

  • BasicSkill Level
  • 4.9+
  • 103 reviews

Build interactive AI apps in Sigma using user input, actions, and polished interfaces, no coding required.

Reporting

2 hours

Course

Anomaly Detection in Python

  • IntermediateSkill Level
  • 4.8+
  • 169 reviews

Detect anomalies in your data analysis and expand your Python statistical toolkit in this four-hour course.

Probability & Statistics

4 hours

Course

Calculations in Sigma

  • BasicSkill Level
  • 4.9+
  • 121 reviews

Build dynamic Sigma calculations to explore data, automate logic, and uncover trends with practical business examples.

Data Manipulation

2 hours

Course

Factor Analysis in R

  • AdvancedSkill Level
  • 4.7+
  • 141 reviews

Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.

Probability & Statistics

4 hours

Course

Monte Carlo Simulations in Python

  • IntermediateSkill Level
  • 4.7+
  • 153 reviews

Learn to design and run your own Monte Carlo simulations using Python!

Probability & Statistics

4 hours

Course

Introduction to Subagents

  • IntermediateSkill Level
  • 4.9+
  • 41 reviews

Learn how to use and create sub-agents in Claude Code to manage context, delegate tasks, and build workflows that keep your conversation clean and focused.

Artificial Intelligence

2 hours

Course

Fundamentals of Bayesian Data Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 199 reviews

Learn what Bayesian data analysis is, how it works, and why it is a useful tool to have in your data science toolbox.

Probability & Statistics

4 hours

Course

Optimizing Code in Java

  • AdvancedSkill Level
  • 4.8+
  • 154 reviews

Learn key techniques to optimize Java performance, from algorithm efficiency to JVM tuning and multithreading.

Software Development

3 hours

Course

Bayesian Data Analysis in Python

  • IntermediateSkill Level
  • 4.7+
  • 249 reviews

Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!

Probability & Statistics

4 hours

Course

Window Functions in Snowflake

  • IntermediateSkill Level
  • 4.8+
  • 448 reviews

Discover Snowflake window functions to solve complex data problems with rankings, partitions, and rolling calculations.

Data Manipulation

3 hours

Course

Web Scraping in R

  • IntermediateSkill Level
  • 4.7+
  • 86 reviews

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

Data Preparation

4 hours

Course

Gen AI Apps: Transform Your Work

  • BasicSkill Level
  • 4.7+
  • 68 reviews

This course introduces Google’s gen AI applications, such as Google Workspace with Gemini and NotebookLM.

Cloud

1 hour 15 min

Course

Introduction to Network Analysis in Python

  • IntermediateSkill Level
  • 4.7+
  • 205 reviews

This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library.

Probability & Statistics

4 hours

Course

Case Study: Ecommerce Analysis in Power BI

  • IntermediateSkill Level
  • 4.8+
  • 195 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: Mortgage Trading Analysis in Power BI

  • IntermediateSkill Level
  • 4.8+
  • 265 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

Gen AI: Unlock Foundational Concepts

  • BasicSkill Level
  • 4.8+
  • 72 reviews

You unlock the foundational concepts of generative AI by exploring the differences between AI, ML, and gen AI.

Cloud

1 hour 30 min

Course

Data Fluency

  • BasicSkill Level
  • 4.8+
  • 268 reviews

Master data fluency! Learn skills for individuals and organizations, understand behaviors, and build a data-fluent culture.

Data Literacy

2 hours

Course

Time Series Analysis in SQL Server

  • IntermediateSkill Level
  • 4.7+
  • 355 reviews

Explore ways to work with date and time data in SQL Server for time series analysis

Data Manipulation

5 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.

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Make progress on the go with our mobile courses and daily 5-minute coding challenges.