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779 Courses

Course

Machine Learning Operations (MLOps) with Vertex AI: Manage Features

  • IntermediateSkill Level
  • 5
  • 6 reviews

Learn best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud.

Cloud

8 hours

Course

Analyzing US Census Data in R

  • IntermediateSkill Level
  • 4.8+
  • 38 reviews

Learn to rapidly visualize and explore demographic data from the United States Census Bureau using tidyverse tools.

Exploratory Data Analysis

4 hours

Course

Intermediate Regular Expressions in R

  • IntermediateSkill Level
  • 4.8+
  • 34 reviews

Manipulate text data, analyze it and more by mastering regular expressions and string distances in R.

Software Development

4 hours

Course

Manage Scalable Workloads in GKE

  • AdvancedSkill Level
  • 4.7+
  • 9 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

Pandas Joins for Spreadsheet Users

  • IntermediateSkill Level
  • 4.7+
  • 56 reviews

Learn how to effectively and efficiently join datasets in tabular format using the Python Pandas library.

Data Manipulation

4 hours

Course

AI Infrastructure: Deployment Types

  • IntermediateSkill Level
  • 5
  • 13 reviews

A guide to deploying, managing, and optimizing AI and high-performance computing (HPC) workloads on Google Cloud.

Cloud

1 hour 30 min

Course

Deploy and Scale AI Models with Cloud Run

  • IntermediateSkill Level
  • 4.9+
  • 13 reviews

This course is designed for developers, data scientists, and ML engineers interested in quickly deploying AI inference services on Cloud Run.

Cloud

1 hour 15 min

Course

Work with Gemini Models in BigQuery

  • IntermediateSkill Level
  • 4.8+
  • 17 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

Joining Data with data.table in R

  • IntermediateSkill Level
  • 4.8+
  • 73 reviews

This course will show you how to combine and merge datasets with data.table.

Data Manipulation

4 hours

Course

Google Workspace End User: Google Chat

  • BasicSkill Level
  • 4.7+
  • 19 reviews

Learn to message individuals and groups, collaborate in spaces, and integrate Google Chat with other Workspace apps.

Cloud

2 hours 30 min

Course

Model Armor: Securing AI Deployments

  • IntermediateSkill Level
  • 5
  • 9 reviews

This course reviews the essential security features of Model Armor and equips you to work with the service.

Cloud

2 hours 30 min

Course

Bayesian Modeling with RJAGS

  • AdvancedSkill Level
  • 4.8+
  • 52 reviews

In this course, youll learn how to implement more advanced Bayesian models using RJAGS.

Probability & Statistics

4 hours

Course

Architecting with Google Kubernetes Engine: Workloads

  • IntermediateSkill Level
  • 4.8+
  • 15 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

Machine Translation with Keras

  • AdvancedSkill Level
  • 4.8+
  • 48 reviews

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

Artificial Intelligence

4 hours

Course

Automating Release Briefs with Claude Cowork

  • IntermediateSkill Level
  • 4.7+
  • 7 reviews

Want to spend more time coding and less time doing admin? Automate support briefs for the rollout of new features with Claude Cowork.

Artificial Intelligence

15 min

Course

Configure Gemini Code Assist for Organizations

  • IntermediateSkill Level
  • 5
  • 10 reviews

The course introduces the benefits of Gemini Code Assist and compares the features of the different Gemini Code Assist editions.

Cloud

1 hour 30 min

Course

Parallel Programming in R

  • IntermediateSkill Level
  • 4.7+
  • 77 reviews

Unlock the power of parallel computing in R. Enhance your data analysis skills, speed up computations, and process large datasets effortlessly.

Software Development

4 hours

Course

Forecasting Product Demand in R

  • IntermediateSkill Level
  • 4.7+
  • 30 reviews

Learn how to identify important drivers of demand, look at seasonal effects, and predict demand for a hierarchy of products from a real world example.

Probability & Statistics

4 hours

Course

Optimizing R Code with Rcpp

  • IntermediateSkill Level
  • 4.9+
  • 13 reviews

Use C++ to dramatically boost the performance of your R code.

Software Development

4 hours

Course

Business Process Analytics in R

  • IntermediateSkill Level
  • 4.8+
  • 44 reviews

Learn how to analyze business processes in R and extract actionable insights from enormous sets of event data.

Reporting

4 hours

Course

Gemini for end-to-end SDLC

  • IntermediateSkill Level
  • 5
  • 8 reviews

With help from Gemini, you learn how to develop and build a web application, fix errors in the application, develop tests, and query data.

Cloud

1 hour 30 min

Course

Lead Qualification and Scoring with Claude Cowork

  • IntermediateSkill Level
  • 4.7+
  • 9 reviews

Staring at your inbound leads and unsure where to start? Use Claude Cowork to score your leads and build a high-quality, prioritized shortlist.

Artificial Intelligence

15 min

Course

Probability Puzzles in R

  • BasicSkill Level
  • 4.7+
  • 69 reviews

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

Probability & Statistics

4 hours

Course

Data Manipulation in Julia

  • BasicSkill Level
  • 4.7+
  • 44 reviews

Master the essential skills of data manipulation in Julia. Learn how to inspect, transform, group, and visualize DataFrames using real-world datasets.

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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