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711 Courses

Course

Google Workspace End User: Google Slides

  • BasicSkill Level
  • 4.8+
  • 9 reviews

With Google Slides, you can create and present professional presentations for sales, projects, training modules, and much more.

Cloud

8 hours 30 min

Course

Google Workspace End User: Google Docs

  • BasicSkill Level
  • 4.8+
  • 10 reviews

Learn to create, format, and collaborate on documents in real time using Google Docs, stored securely in the cloud.

Cloud

4 hours 30 min

Course

Google Workspace End User: Google Sheets

  • BasicSkill Level
  • 4.7+
  • 8 reviews

Learn to create and edit spreadsheets in Google Sheets, work with data, build formulas, and collaborate in real time.

Cloud

6 hours 30 min

Course

Build Batch Data Pipelines on Google Cloud

  • IntermediateSkill Level
  • 4.8+
  • 5 reviews

Explore streaming data architectures on Google Cloud with Pub/Sub, Managed Kafka, Dataflow, and BigQuery for real-time data processing.

Cloud

2 hours 6 min

Course

Architecting with Google Kubernetes Engine: Workloads

  • IntermediateSkill Level
  • 4.8+
  • 5 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

Architecting with Google Kubernetes Engine: Production

  • IntermediateSkill Level
  • 4.7+
  • 4 reviews

Secure and monitor GKE production environments. Learn access control, logging, monitoring, CI/CD pipelines, and managed storage integration on Google Cloud.

Cloud

3 hours 30 min

Course

Manage Scalable Workloads in GKE

  • AdvancedSkill Level
  • 4.3+
  • 3 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

Build Streaming Data Pipelines on Google Cloud

  • IntermediateSkill Level
  • 4.7+
  • 4 reviews

Design and operate batch data pipelines on Google Cloud using Dataflow, Serverless Spark, Cloud Composer, and data validation techniques.

Cloud

3 hours 32 min

Course

Boost Productivity with Gemini in BigQuery

  • BasicSkill Level
  • 4.7+
  • 4 reviews

Use Gemini AI to boost your productivity in BigQuery. Explore data, accelerate code development, and discover visualization workflows.

Cloud

1 hour 23 min

Course

Work with Gemini Models in BigQuery

  • IntermediateSkill Level
  • 4.6+
  • 5 reviews

Work with Gemini AI models in BigQuery for sentiment analysis. Analyze customer reviews using SQL and Python notebooks with Gemini.

Cloud

1 hour

Course

LLM Application Fundamentals with LangChain

  • IntermediateSkill Level
  • 4.7+
  • 98 reviews

Learn to build conversational LLM applications — with reliable structured output, persistent conversation history, and real-time streaming.

Artificial Intelligence

AI Native

3 hours

Course

Retrieval-Augmented Generation with LangChain

  • IntermediateSkill Level
  • 4.7+
  • 35 reviews

Learn to build knowledge-grounded LLM applications that retrieve relevant information from structured and unstructured sources before generating responses.

Artificial Intelligence

AI Native

2 hours

Course

LLM Tool Use with LangChain

  • IntermediateSkill Level
  • 4.6+
  • 21 reviews

Learn to extend your LLM applications with external tools, so your applications can retrieve live data, perform computations, and take real-world actions.

Artificial Intelligence

AI Native

3 hours

Course

Prompt Engineering with LangChain

  • IntermediateSkill Level
  • 4.6+
  • 42 reviews

Learn to write effective prompts and systematically improve them through evaluation rather than intuition.

Artificial Intelligence

AI Native

2 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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