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781 Courses

Course

Machine Learning Operations (MLOps): Getting Started

  • IntermediateSkill Level
  • 4.9+
  • 22 reviews

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

Cloud

4 hours 30 min

Course

Visualizing Time Series Data in R

  • IntermediateSkill Level
  • 4.8+
  • 188 reviews

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

Data Visualization

4 hours

Course

Analyzing Police Activity with pandas

  • IntermediateSkill Level
  • 4.8+
  • 32 reviews

Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.

Data Manipulation

4 hours

Course

Data Visualization in KNIME

  • BasicSkill Level
  • 4.8+
  • 217 reviews

Learn to create compelling data visualizations with KNIME, covering charts, components, and dashboards.

Data Visualization

2 hours

Course

Factor Analysis in R

  • AdvancedSkill Level
  • 4.7+
  • 169 reviews

Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.

Probability & Statistics

4 hours

Course

Developing R Packages

  • IntermediateSkill Level
  • 4.7+
  • 161 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

Using AWS Security for Developers

  • IntermediateSkill Level
  • 4.8+
  • 13 reviews

Secure the AWS workloads you ship: least-privilege IAM, short-lived credentials, API authorization, secrets handling, encryption, and CloudTrail evidence.

Cloud

3 hours

Course

Business Process Analytics in R

  • IntermediateSkill Level
  • 4.8+
  • 50 reviews

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

Reporting

4 hours

Course

Conditional Formatting in Google Sheets

  • BasicSkill Level
  • 4.8+
  • 102 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: Financial Analysis in KNIME

  • IntermediateSkill Level
  • 4.8+
  • 125 reviews

Apply financial analysis in KNIME with real-world data, enhancing data preparation and workflow skills.

Applied Finance

3 hours

Course

Google: Manage Agent Memory and State

  • IntermediateSkill Level
  • 4.7+
  • 46 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

Case Studies in Statistical Thinking

  • IntermediateSkill Level
  • 4.8+
  • 88 reviews

Take vital steps towards mastery as you apply your statistical thinking skills to real-world data sets and extract actionable insights from them.

Probability & Statistics

4 hours

Course

Time Series Analysis in PostgreSQL

  • IntermediateSkill Level
  • 4.8+
  • 103 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

AI Infrastructure: Cloud GPUs

  • IntermediateSkill Level
  • 4.9+
  • 31 reviews

Well explore how CPUs, GPUs, and TPUs make AI tasks super fast, what makes each one unique, and how AI software gets the most out of them.

Cloud

1 hour

Course

HR Analytics: Exploring Employee Data in R

  • IntermediateSkill Level
  • 4.8+
  • 43 reviews

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

Exploratory Data Analysis

5 hours

Course

Analyzing US Census Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 67 reviews

Learn to use the Census API to work with demographic and socioeconomic data.

Exploratory Data Analysis

5 hours

Course

Getting Started with Google Kubernetes Engine

  • IntermediateSkill Level
  • 4.8+
  • 45 reviews

The goal of this course is to introduce the basics of Google Kubernetes Engine, or GKE, and how to get applications containerized and running in Google Cloud.

Cloud

5 hours 15 min

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

Google Workspace End User: Gmail

  • BasicSkill Level
  • 4.8+
  • 41 reviews

Learn to compose, send, and manage email in Gmail, organize messages with labels, and configure settings like filters and signatures.

Cloud

7 hours 15 min

Course

Introduction to Gemini Enterprise

  • BasicSkill Level
  • 4.9+
  • 16 reviews

Gemini Enteprise brings together AI agents, enterprise search, NotebookLM, and intelligent data access to solve organizational challenges.

Cloud

2 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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