Course
Intermediate Predictive Analytics in Python
- BasicSkill Level
- 4.7+
- 74 reviews
Learn how to prepare and organize your data for predictive analytics.
Machine Learning
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774 Courses
Course
Visualizing Big Data with Trelliscope in R
- BasicSkill Level
- 4.7+
- 44 reviews
Learn how to visualize big data in R using ggplot2 and trelliscopejs.
Data Visualization
Course
Boost Productivity with Gemini in BigQuery
- BasicSkill Level
- 4.9+
- 17 reviews
Use Gemini AI to boost your productivity in BigQuery. Explore data, accelerate code development, and discover visualization workflows.
Cloud
Course
Gemini for Application Developers
- IntermediateSkill Level
- 4.9+
- 14 reviews
You learn how to prompt Gemini to explain code, recommend Google Cloud services, and generate code for your applications.
Cloud
Course
Google Workspace End User: Google Drive
- BasicSkill Level
- 4.8+
- 19 reviews
Learn to upload, organize, share, and manage files and folders in Google Drive from any device.
Cloud
Course
Google Workspace End User: Google Calendar
- BasicSkill Level
- 4.8+
- 19 reviews
Learn to create and manage events, schedule meetings, share calendars, and use tasks and reminders to stay organized.
Cloud
Course
Scalable Data Processing in R
- AdvancedSkill Level
- 4.7+
- 25 reviews
Learn how to write scalable code for working with big data in R using the bigmemory and iotools packages.
Software Development
Course
Google Workspace End User: Google Docs
- BasicSkill Level
- 4.9+
- 20 reviews
Learn to create, format, and collaborate on documents in real time using Google Docs, stored securely in the cloud.
Cloud
Course
Multivariate Probability Distributions in R
- IntermediateSkill Level
- 4.7+
- 46 reviews
Learn to analyze, plot, and model multivariate data.
Probability & Statistics
Cloud
Course
Dimensionality Reduction in R
- BasicSkill Level
- 4.7+
- 97 reviews
Learn dimensionality reduction techniques in R and master feature selection and extraction for your own data and models.
Machine Learning
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
Course
AI Infrastructure: Deployment Types
- IntermediateSkill Level
- 5
- 14 reviews
A guide to deploying, managing, and optimizing AI and high-performance computing (HPC) workloads on Google Cloud.
Cloud
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
Course
Google Workspace End User: Google Meet
- BasicSkill Level
- 4.8+
- 21 reviews
Learn to schedule, host, and manage video meetings in Google Meet, including screen sharing and collaboration tools.
Cloud
Course
Architecting with Google Kubernetes Engine: Production
- IntermediateSkill Level
- 4.8+
- 15 reviews
Secure and monitor GKE production environments. Learn access control, logging, monitoring, CI/CD pipelines, and managed storage integration on Google Cloud.
Cloud
Course
Sentiment Analysis in R
- IntermediateSkill Level
- 4.7+
- 97 reviews
Learn sentiment analysis by identifying positive and negative language, specific emotional intent and making compelling visualizations.
Machine Learning
Course
Lead Qualification and Scoring with Claude Cowork
- IntermediateSkill Level
- 4.7+
- 11 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
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Automating Release Briefs with Claude Cowork
- IntermediateSkill Level
- 4.6+
- 9 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
Course
Strategies for Cloud Security Risk Management
- IntermediateSkill Level
- 5
- 5 reviews
This course is a thrilling mix of expert-led courses and immersive Google Cloud challenges through interactive labs.
Cloud
Course
Model Armor: Securing AI Deployments
- IntermediateSkill Level
- 5
- 11 reviews
This course reviews the essential security features of Model Armor and equips you to work with the service.
Cloud
Course
Build Batch Data Pipelines on Google Cloud
- IntermediateSkill Level
- 4.9+
- 14 reviews
Explore streaming data architectures on Google Cloud with Pub/Sub, Managed Kafka, Dataflow, and BigQuery for real-time data processing.
Cloud
Course
Accelerate App Development with Gemini CLI
- IntermediateSkill Level
- 4.9+
- 10 reviews
Learn about gemini CLI installation and configuration, and introduces use cases and security best practices
Cloud
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
Course
GARCH Models in R
- AdvancedSkill Level
- 4.8+
- 100 reviews
Specify and fit GARCH models to forecast time-varying volatility and value-at-risk.
Applied Finance
Course
Hyperparameter Tuning in R
- AdvancedSkill Level
- 4.8+
- 62 reviews
Learn how to tune your models hyperparameters to get the best predictive results.
Machine Learning
Course
Case Study: Ecommerce Analysis in Tableau
- IntermediateSkill Level
- 4.7+
- 65 reviews
In ecommerce, increasing sales and reducing expenses are top priorities. In this case study, youll investigate data from an online pet supply company.
Data Visualization
Course
Responsible AI for Developers: Privacy & Safety
- IntermediateSkill Level
- 5
- 10 reviews
It explores practical methods and tools to implement AI privacy and safety recommended practices.
Cloud
Course
Defensive R Programming
- IntermediateSkill Level
- 4.8+
- 79 reviews
Learn defensive programming in R to make your code more robust.
Software Development
Course
Practicing Statistics Interview Questions in R
- AdvancedSkill Level
- 4.7+
- 23 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
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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