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774 Courses

Course

Google: Optimize Agent Behavior

  • IntermediateSkill Level
  • 4.8+
  • 37 reviews

Turn a basic AI agent into a sophisticated assistant using advanced instructions, model selection, planning capabilities, and structured output.

Cloud

2 hours

Course

Discrete Event Simulation in Python

  • AdvancedSkill Level
  • 4.7+
  • 80 reviews

Discover the power of discrete-event simulation in optimizing your business processes. Learn to develop digital twins using Pythons SimPy package.

Probability & Statistics

4 hours

Course

Handling Missing Data with Imputations in R

  • AdvancedSkill Level
  • 4.7+
  • 105 reviews

Diagnose, visualize and treat missing data with a range of imputation techniques with tips to improve your results.

Data Manipulation

4 hours

Course

Foundations of Inference in Python

  • AdvancedSkill Level
  • 4.8+
  • 230 reviews

Get hands-on experience making sound conclusions based on data in this four-hour course on statistical inference in Python.

Probability & Statistics

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

Analyzing IoT Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 115 reviews

Learn how to import, clean and manipulate IoT data in Python to make it ready for machine learning.

Data Manipulation

4 hours

Course

Financial Forecasting in Python

  • IntermediateSkill Level
  • 4.8+
  • 95 reviews

Step into the role of CFO and learn how to advise a board of directors on key metrics while building a financial forecast.

Applied Finance

4 hours

Course

Auditing Expenses with Claude Cowork

  • IntermediateSkill Level
  • 4.7+
  • 11 reviews

Bored of pouring over expenses to figure out which ones violate policy? No longer! Use Claude Cowork to produce fast and clear expense violation reports.

Artificial Intelligence

15 min

Course

Introduction to Scala

  • IntermediateSkill Level
  • 4.8+
  • 143 reviews

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

Software Development

3 hours

Course

End-to-End RAG with Weaviate

  • IntermediateSkill Level
  • 4.6+
  • 20 reviews

Master RAG with Weaviate! Embed text and images for retrieval, and experiment with vector, BM25, and hybrid search.

Artificial Intelligence

2 hours

Course

Practicing Statistics Interview Questions in Python

  • AdvancedSkill Level
  • 4.7+
  • 89 reviews

Prepare for your next statistics interview by reviewing concepts like conditional probabilities, A/B testing, the bias-variance tradeoff, and more.

Probability & Statistics

4 hours

Course

Support Vector Machines in R

  • IntermediateSkill Level
  • 4.8+
  • 95 reviews

This course will introduce the support vector machine (SVM) using an intuitive, visual approach.

Machine Learning

4 hours

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

A/B Testing in R

  • IntermediateSkill Level
  • 4.8+
  • 95 reviews

Learn the basics of A/B testing in R, including how to design experiments, analyze data, predict outcomes, and present results through visualizations.

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

Conquering Data Bias

  • BasicSkill Level
  • 4.7+
  • 236 reviews

Unlock your datas potential by learning to detect and mitigate bias for precise analysis and reliable models.

Data Management

2 hours

Course

Google: Manage Agent Memory and State

  • IntermediateSkill Level
  • 4.7+
  • 30 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

Inference for Numerical Data in R

  • AdvancedSkill Level
  • 4.8+
  • 111 reviews

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

Probability & Statistics

4 hours

Course

Network Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 135 reviews

Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.

Probability & Statistics

4 hours

Course

Statistical Simulation in Python

  • IntermediateSkill Level
  • 4.8+
  • 29 reviews

Learn to solve increasingly complex problems using simulations to generate and analyze data.

Probability & Statistics

4 hours

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

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

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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