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775 Courses

Course

Inference for Categorical Data in R

  • AdvancedSkill Level
  • 4.8+
  • 116 reviews

In this course youll learn how to leverage statistical techniques for working with categorical data.

Probability & Statistics

4 hours

Course

Generalized Linear Models in Python

  • AdvancedSkill Level
  • 4.7+
  • 147 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

Introduction to Security in the World of AI

  • IntermediateSkill Level
  • 4.8+
  • 28 reviews

This course equips security and data protection leaders with strategies to securely manage AI within their organizations.

Cloud

1 hour

Course

Credit Risk Modeling in R

  • IntermediateSkill Level
  • 4.7+
  • 88 reviews

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

Applied Finance

4 hours

Course

MLOps for Business

  • BasicSkill Level
  • 4.8+
  • 159 reviews

Learn about MLOps, including the tools and practices needed for automating and scaling machine learning applications.

Machine Learning

3 hours

Course

R For SAS Users

  • BasicSkill Level
  • 4.7+
  • 29 reviews

Learn how to translate your SAS knowledge into R and analyze data using this free and powerful software language.

Software Development

4 hours

Course

Inference for Numerical Data in R

  • AdvancedSkill Level
  • 4.8+
  • 113 reviews

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

Probability & Statistics

4 hours

Course

Quantitative Risk Management in R

  • BasicSkill Level
  • 4.8+
  • 85 reviews

Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.

Applied Finance

5 hours

Course

Programming with dplyr

  • IntermediateSkill Level
  • 4.7+
  • 52 reviews

Learn how to perform advanced dplyr transformations and incorporate dplyr and ggplot2 code in functions.

Data Manipulation

4 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 Transformation in KNIME

  • BasicSkill Level
  • 4.8+
  • 299 reviews

Enhance your KNIME skills with our course on data transformation, column operations, and workflow optimization.

Data Preparation

2 hours

Course

Google: Manage Agent Memory and State

  • IntermediateSkill Level
  • 4.6+
  • 31 reviews

Build stateful AI agents that maintain context and remember user preferences using session state, memory management, and personalization.

Cloud

1 hour 30 min

Course

Essential Google Cloud Infrastructure: Core Services

  • IntermediateSkill Level
  • 4.9+
  • 32 reviews

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

Cloud

8 hours 15 min

Course

Modeling with tidymodels in R

  • IntermediateSkill Level
  • 4.8+
  • 186 reviews

Learn to streamline your machine learning workflows with tidymodels.

Machine Learning

4 hours

Course

Defensive R Programming

  • IntermediateSkill Level
  • 4.8+
  • 90 reviews

Learn defensive programming in R to make your code more robust.

Software Development

4 hours

Course

AI Infrastructure: Networking Techniques

  • IntermediateSkill Level
  • 4.9+
  • 20 reviews

Design and deploy high-performance AI/ML solutions using Google Clouds AI Hypercomputer, GPUs, TPUs, Compute, and Google Kubernetes Engine.

Cloud

1 hour

Course

Conditional Formatting in Google Sheets

  • BasicSkill Level
  • 4.8+
  • 101 reviews

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

Data Manipulation

2 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

Time Series Analysis in PostgreSQL

  • IntermediateSkill Level
  • 4.8+
  • 101 reviews

Learn how to use PostgreSQL to handle time series analysis effectively and apply these techniques to real-world data.

Data Manipulation

4 hours

Course

HR Analytics: Exploring Employee Data in R

  • IntermediateSkill Level
  • 4.8+
  • 42 reviews

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

Exploratory Data Analysis

5 hours

Course

Developing R Packages

  • IntermediateSkill Level
  • 4.7+
  • 158 reviews

Learn to develop R packages and boost your coding skills. Discover package creation benefits, practice with dev tools, and create a unit conversion package.

Software Development

4 hours

Course

Visualizing Time Series Data in R

  • IntermediateSkill Level
  • 4.8+
  • 185 reviews

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

Data Visualization

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

Planning a Product Launch with Claude Cowork

  • IntermediateSkill Level
  • 4.5+
  • 11 reviews

Tired of launch week chaos? Plan and write a full product launch in a single session with Claude Cowork.

Artificial Intelligence

15 min

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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