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771 Courses

Course

Case Study: Analyzing Fitness Data in Alteryx

  • IntermediateSkill Level
  • 4.8+
  • 56 reviews

Advance your Alteryx skills with real fitness data to develop targeted marketing strategies and innovative products!

Data Preparation

3 hours

Course

Build Batch Data Pipelines on Google Cloud

  • IntermediateSkill Level
  • 4.8+
  • 9 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

DataLab with SQL

  • BasicSkill Level
  • 4.8+
  • 44 reviews

Elevate your analysis with this hands-on course using SQL with DataLab workbooks.

Reporting

1 hour

Course

Build Streaming Data Pipelines on Google Cloud

  • IntermediateSkill Level
  • 4.8+
  • 11 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

Intermediate Julia

  • BasicSkill Level
  • 4.7+
  • 82 reviews

Take your Julia skills to the next level with our intermediate Julia course. Learn about loops, advanced data structures, timing, and more.

Software Development

4 hours

Course

Google Workspace End User: Google Chat

  • BasicSkill Level
  • 4.7+
  • 16 reviews

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

Cloud

2 hours 30 min

Course

Architecting with Google Kubernetes Engine: Production

  • IntermediateSkill Level
  • 4.8+
  • 10 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

Practicing Statistics Interview Questions in R

  • AdvancedSkill Level
  • 4.7+
  • 22 reviews

In this course, youll prepare for the most frequently covered statistical topics from distributions to hypothesis testing, regression models, and much more.

Probability & Statistics

4 hours

Course

Manage Scalable Workloads in GKE

  • AdvancedSkill Level
  • 4.6+
  • 6 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

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

Analyzing Social Media Data in R

  • IntermediateSkill Level
  • 4.8+
  • 90 reviews

Extract and visualize Twitter data, perform sentiment and network analysis, and map the geolocation of your tweets.

Data Manipulation

4 hours

Course

Building Dashboards with flexdashboard

  • IntermediateSkill Level
  • 4.7+
  • 51 reviews

In this course youll learn how to create static and interactive dashboards using flexdashboard and shiny.

Reporting

4 hours

Course

Optimizing R Code with Rcpp

  • IntermediateSkill Level
  • 4.9+
  • 12 reviews

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

Software Development

4 hours

Course

Boost Productivity with Gemini in BigQuery

  • BasicSkill Level
  • 4.9+
  • 14 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

Equity Valuation in R

  • IntermediateSkill Level
  • 4.8+
  • 65 reviews

Learn the fundamentals of valuing stocks.

Applied Finance

4 hours

Course

Business Process Analytics in R

  • IntermediateSkill Level
  • 4.8+
  • 43 reviews

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

Reporting

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

AI Infrastructure: Networking Techniques

  • IntermediateSkill Level
  • 4.8+
  • 11 reviews

Design and deploy high-performance AI/ML solutions using Google Clouds AI Hypercomputer, GPUs, TPUs, Compute, and Google Kubernetes Engine.

Cloud

1 hour

Course

Architecting with Google Kubernetes Engine: Workloads

  • IntermediateSkill Level
  • 4.8+
  • 11 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+
  • 47 reviews

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

Artificial Intelligence

4 hours

Course

Introduction to Security in the World of AI

  • IntermediateSkill Level
  • 4.7+
  • 15 reviews

This course equips security and data protection leaders with strategies to securely manage AI within their organizations.

Cloud

1 hour

Course

Bayesian Modeling with RJAGS

  • AdvancedSkill Level
  • 4.8+
  • 51 reviews

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

Probability & Statistics

4 hours

Course

Work with Gemini Models in BigQuery

  • IntermediateSkill Level
  • 4.8+
  • 14 reviews

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

Cloud

1 hour

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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