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793 Courses

Course

Manage Scalable Workloads in GKE

  • AdvancedSkill Level
  • 4.8+
  • 14 reviews

Scale and manage multi-cluster GKE environments. Master fleets, Cloud Service Mesh, identity management, CI/CD at scale, and GKE Enterprise capabilities.

Cloud

7 hours 20 min

Course

Building Response Models in R

  • IntermediateSkill Level
  • 4.8+
  • 31 reviews

Learn to build simple models of market response to increase the effectiveness of your marketing plans.

Probability & Statistics

4 hours

Course

Architecting with Google Kubernetes Engine: Workloads

  • IntermediateSkill Level
  • 4.8+
  • 21 reviews

Deploy and manage Kubernetes workloads on GKE. Cover networking, deployments, jobs, persistent storage, and data management in production environments.

Cloud

2 hours 30 min

Course

Predicting CTR with Machine Learning in Python

  • IntermediateSkill Level
  • 4.9+
  • 21 reviews

Learn how to predict click-through rates on ads and implement basic machine learning models in Python so that you can see how to better optimize your ads.

Machine Learning

4 hours

Course

Predictive Analytics using Networked Data in R

  • IntermediateSkill Level
  • 4.8+
  • 36 reviews

Learn to predict labels of nodes in networks using network learning and by extracting descriptive features from the network

Probability & Statistics

4 hours

Course

Machine Translation with Keras

  • AdvancedSkill Level
  • 4.8+
  • 50 reviews

Are you curious about the inner workings of the models that are behind products like Google Translate?

Artificial Intelligence

4 hours

Course

Probability Puzzles in R

  • BasicSkill Level
  • 4.8+
  • 70 reviews

Learn strategies for answering probability questions in R by solving a variety of probability puzzles.

Probability & Statistics

4 hours

Course

Mixture Models in R

  • IntermediateSkill Level
  • 4.7+
  • 29 reviews

Learn mixture models: a convenient and formal statistical framework for probabilistic clustering and classification.

Probability & Statistics

4 hours

Course

Introduction to Snowflake CoCo CLI

  • BasicSkill Level
  • 5
  • 3 reviews

Put Snowflake CoCo to work in your terminal: explore data, run AI functions over text, and build scripts and pipelines while you stay in control.

Artificial Intelligence

2 hours

Course

Gemini for Network Engineers

  • BasicSkill Level

See how Gemini in Google Cloud helps network engineers plan, build, and maintain VPC networks with AI assistance.

Cloud

1 hour

Course

Manage Security in Google Cloud

  • IntermediateSkill Level

Build Google Cloud security foundations with Cloud Identity, IAM, and VPC controls for isolation and logging.

Cloud

8 hours 30 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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