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778 Courses

Course

Modeling with tidymodels in R

  • IntermediateSkill Level
  • 4.8+
  • 188 reviews

Learn to streamline your machine learning workflows with tidymodels.

Machine Learning

4 hours

Course

Survival Analysis in Python

  • AdvancedSkill Level
  • 4.7+
  • 73 reviews

Use survival analysis to work with time-to-event data and predict survival time.

Probability & Statistics

4 hours

Course

Gemini for Application Developers

  • IntermediateSkill Level
  • 4.8+
  • 16 reviews

You learn how to prompt Gemini to explain code, recommend Google Cloud services, and generate code for your applications.

Cloud

1 hour 30 min

Course

Google Workspace End User: Gmail

  • BasicSkill Level
  • 4.8+
  • 37 reviews

Learn to compose, send, and manage email in Gmail, organize messages with labels, and configure settings like filters and signatures.

Cloud

7 hours 15 min

Course

Conditional Formatting in Google Sheets

  • BasicSkill Level
  • 4.8+
  • 102 reviews

Learn how to use conditional formatting with your data through built-in options and by creating custom formulas.

Data Manipulation

2 hours

Course

HR Analytics: Exploring Employee Data in R

  • IntermediateSkill Level
  • 4.8+
  • 43 reviews

Learn how to manipulate, visualize, and perform statistical tests through a series of HR analytics case studies.

Exploratory Data Analysis

5 hours

Course

Building AI Agents with Haystack

  • IntermediateSkill Level
  • 4.8+
  • 47 reviews

Create a healthcare AI agent using Haystack, an open-source framework for orchestrating LLMs and external components.

Artificial Intelligence

1 hour 30 min

Course

Data Visualization in KNIME

  • BasicSkill Level
  • 4.8+
  • 213 reviews

Learn to create compelling data visualizations with KNIME, covering charts, components, and dashboards.

Data Visualization

2 hours

Course

Analyzing US Census Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 67 reviews

Learn to use the Census API to work with demographic and socioeconomic data.

Exploratory Data Analysis

5 hours

Course

Getting Started with Google Kubernetes Engine

  • IntermediateSkill Level
  • 4.7+
  • 39 reviews

The goal of this course is to introduce the basics of Google Kubernetes Engine, or GKE, and how to get applications containerized and running in Google Cloud.

Cloud

5 hours 15 min

Course

Google: Add Agent Capabilities With Tools

  • IntermediateSkill Level
  • 4.7+
  • 36 reviews

Equip AI agents with tools for web search, code execution, database queries, and custom actions. Transform agents into capable assistants.

Cloud

3 hours

Course

Introduction to Gemini Enterprise

  • BasicSkill Level
  • 4.9+
  • 15 reviews

Gemini Enteprise brings together AI agents, enterprise search, NotebookLM, and intelligent data access to solve organizational challenges.

Cloud

2 hours 15 min

Course

AI Infrastructure: Cloud GPUs

  • IntermediateSkill Level
  • 4.9+
  • 25 reviews

Well explore how CPUs, GPUs, and TPUs make AI tasks super fast, what makes each one unique, and how AI software gets the most out of them.

Cloud

1 hour

Course

Visualizing Time Series Data in R

  • IntermediateSkill Level
  • 4.8+
  • 188 reviews

Learn how to visualize time series in R, then practice with a stock-picking case study.

Data Visualization

4 hours

Course

Bond Valuation and Analysis in Python

  • BasicSkill Level
  • 4.8+
  • 76 reviews

Learn how bonds work and how to price them and assess some of their risks using the numpy and numpy-financial packages.

Applied Finance

4 hours

Course

Case Study: Financial Analysis in KNIME

  • IntermediateSkill Level
  • 4.8+
  • 123 reviews

Apply financial analysis in KNIME with real-world data, enhancing data preparation and workflow skills.

Applied Finance

3 hours

Course

Case Study: Supply Chain Analytics in Tableau

  • IntermediateSkill Level
  • 4.7+
  • 72 reviews

Dive into our Tableau case study on supply chain analytics. Tackle shipment, inventory management, and dashboard creation to drive business improvements.

Data Visualization

4 hours

Course

Overturning Insurance Denials with Claude Cowork

  • IntermediateSkill Level
  • 4.7+
  • 17 reviews

A patients healthcare claim has been wrongly denied, and its your job to quickly synthesize the evidence and build an appeal—all using Claude Cowork!

Artificial Intelligence

15 min

Course

Financial Trading in R

  • IntermediateSkill Level
  • 4.8+
  • 81 reviews

This course covers the basics of financial trading and how to use quantstrat to build signal-based trading strategies.

Applied Finance

5 hours

Course

Working with DeepSeek in Python

  • BasicSkill Level
  • 4.7+
  • 107 reviews

Discover what all of the DeepSeek hype was really about! Build applications using DeepSeeks R1 and V3 models.

Artificial Intelligence

3 hours

Course

Create Generative AI Apps on Google Cloud

  • IntermediateSkill Level
  • 5
  • 14 reviews

Learn about Gen AI applications and how you can use prompt design and retrieval augmented generation (RAG) to build powerful applications using LLMs.

Cloud

4 hours

Course

Analyzing Social Media Data in R

  • IntermediateSkill Level
  • 4.8+
  • 93 reviews

Extract and visualize Twitter data, perform sentiment and network analysis, and map the geolocation of your tweets.

Data Manipulation

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.

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