Course
Conditional Formatting in Google Sheets
- BasicSkill Level
- 4.8+
- 182
Learn how to use conditional formatting with your data through built-in options and by creating custom formulas.
Data Manipulation
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Course
Interactive Data Visualization with plotly in R
- BasicSkill Level
- 4.8+
- 182
Learn how to use plotly in R to create interactive data visualizations to enhance your data storytelling.
Data Visualization
Course
Claude Code 101
- BasicSkill Level
- 4.8+
- 177
Learn how to use Claude Code effectively in your daily development workflows.
Artificial Intelligence
Course
Python for Spreadsheet Users
- BasicSkill Level
- 4.9+
- 176
Use your knowledge of common spreadsheet functions and techniques to explore Python!
Software Development
Course
Trust and Security with Google Cloud
- BasicSkill Level
- 4.9+
- 172
Trust and Security with Google Cloud
Cloud
Course
Introduction to Databricks Genie
- BasicSkill Level
- 4.8+
- 171
Ask data questions in plain English with Databricks Genie - build spaces, curate business language, and monitor quality.
Data Engineering
Course
Case Study: Set Up a Book Recommendation App in Azure
- BasicSkill Level
- 4.7+
- 167
Learn to set up a secure, efficient book recommendation app in Azure in this hands-on case study.
Cloud
Course
Modernize Infrastructure and Applications with Google Cloud
- BasicSkill Level
- 4.8+
- 160
Modernize Infrastructure and Applications with Google Cloud
Cloud
Course
Programming Paradigm Concepts
- BasicSkill Level
- 4.8+
- 155
Explore a range of programming paradigms, including imperative and declarative, procedural, functional, and object-oriented programming.
Software Development
Course
Python for MATLAB Users
- BasicSkill Level
- 4.8+
- 137
Transition from MATLAB by learning some fundamental Python concepts, and diving into the NumPy and Matplotlib packages.
Software Development
Course
Dimensionality Reduction in R
- BasicSkill Level
- 4.8+
- 133
Learn dimensionality reduction techniques in R and master feature selection and extraction for your own data and models.
Machine Learning
Course
R For SAS Users
- BasicSkill Level
- 4.8+
- 132
Learn how to translate your SAS knowledge into R and analyze data using this free and powerful software language.
Software Development
Course
DataLab with SQL
- BasicSkill Level
- 4.8+
- 120
Elevate your analysis with this hands-on course using SQL with DataLab workbooks.
Reporting
Course
Working with DeepSeek in Python
- BasicSkill Level
- 4.7+
- 99
Discover what all of the DeepSeek hype was really about! Build applications using DeepSeeks R1 and V3 models.
Artificial Intelligence
Course
Life Insurance Products Valuation in R
- BasicSkill Level
- 4.9+
- 95
Learn the basics of cash flow valuation, work with human mortality data and build life insurance products in R.
Applied Finance
Course
Google: Enterprise Agents and Use Cases
- BasicSkill Level
- 5.0+
- 94
Map agent types to your KPIs and explore use cases that solve problems, learn how Gemini Enterprise empowers you to build and orchestrate the right agents.
Cloud
Course
Scaling with Google Cloud Operations
- BasicSkill Level
- 4.8+
- 90
Scaling with Google Cloud Operations
Cloud
Course
GDPR in Practice: Compliance and Fines
- BasicSkill Level
- 4.9+
- 89
Explore GDPR through real-world cases on data rights, breaches, and compliance challenges.
Data Management
Course
Bond Valuation and Analysis in Python
- BasicSkill Level
- 4.9+
- 81
Learn how bonds work and how to price them and assess some of their risks using the numpy and numpy-financial packages.
Applied Finance
Course
Intermediate Julia
- BasicSkill Level
- 4.7+
- 81
Take your Julia skills to the next level with our intermediate Julia course. Learn about loops, advanced data structures, timing, and more.
Software Development
Course
Intermediate Predictive Analytics in Python
- BasicSkill Level
- 4.8+
- 79
Learn how to prepare and organize your data for predictive analytics.
Machine Learning
Course
Case Studies: Network Analysis in R
- BasicSkill Level
- 4.7+
- 77
Apply fundamental concepts in network analysis to large real-world datasets in 4 different case studies.
Probability & Statistics
Course
Data Manipulation in Julia
- BasicSkill Level
- 4.8+
- 58
Master the essential skills of data manipulation in Julia. Learn how to inspect, transform, group, and visualize DataFrames using real-world datasets.
Data Manipulation
Course
Visualizing Big Data with Trelliscope in R
- BasicSkill Level
- 4.8+
- 52
Learn how to visualize big data in R using ggplot2 and trelliscopejs.
Data Visualization
Course
Probability Puzzles in R
- BasicSkill Level
- 4.8+
- 49
Learn strategies for answering probability questions in R by solving a variety of probability puzzles.
Probability & Statistics
Course
Select a Google Cloud Database for Your Applications
- BasicSkill Level
- 4.9+
- 33
In this course, you learn to analyze and choose the right database for your needs, to effectively develop applications on Google Cloud.
Cloud
Course
Developing Applications with Cloud Run on Google Cloud: Fundamentals
- BasicSkill Level
- 4.9+
- 30
This course introduces the Cloud Run serverless platform for running applications.
Cloud
Course
Observability in Google Cloud
- BasicSkill Level
- 4.9+
- 23
This course is all about application performance management tools, including Error Reporting, Cloud Trace, and Cloud Profiler.
Cloud
Course
Logging and Monitoring in Google Cloud
- BasicSkill Level
- 4.9+
- 21
This course, Logging and Monitoring in Google Cloud, covers the operations-focused components including Logging, Monitoring, and Service Monitoring.
Cloud
Course
Google Workspace End User: Use Functions, Formulas, and Charts in Google Sheets
- BasicSkill Level
- 5.0+
- 7
Analyze data with functions, visualize it with charts, and master search, validation, and formatting in Google Sheets.
Cloud
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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