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Inference for Categorical Data in R
- AdvancedSkill Level
- 4.4+
- 284
In this course youll learn how to leverage statistical techniques for working with categorical data.
Probability & Statistics
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Gen AI: Beyond the Chatbot
- BasicSkill Level
- 4.7+
- 282
This course aims to move beyond the basic understanding of chatbots to explore the true potential of generative AI for your organization.
Cloud
Course
Case Study: Competitor Sales Analysis in Power BI
- IntermediateSkill Level
- 4.7+
- 276
This Power BI case study follows a real-world business use case where you will apply the concepts of ETL and visualization.
Data Visualization
Course
Marketing Analytics in Tableau
- IntermediateSkill Level
- 4.6+
- 274
Master marketing analytics using Tableau. Analyze performance, benchmark metrics, and optimize strategies across channels.
Data Preparation
Course
Statistical Simulation in Python
- IntermediateSkill Level
- 4.7+
- 272
Learn to solve increasingly complex problems using simulations to generate and analyze data.
Probability & Statistics
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Azure API Management
- IntermediateSkill Level
- 4.5+
- 271
Learn to create, secure, and manage APIs with Azure API Management through hands-on practice.
Cloud
Course
Introduction to DataLab
- BasicSkill Level
- 4.5+
- 269
Learn the fundamentals of using DataLab, an AI-powered data notebook for data analysis and exploration.
Reporting
Course
Introduction to Scala
- IntermediateSkill Level
- 4.7+
- 268
Begin your journey with Scala, a popular language for scalable applications and data engineering infrastructure.
Software Development
Course
Working with the OpenAI Responses API
- IntermediateSkill Level
- 4.6+
- 267
Build smart, interactive, and reliable AI applications easier than ever before with the OpenAI Responses API and GPT-5.
Artificial Intelligence
Course
Recurrent Neural Networks (RNNs) for Language Modeling with Keras
- AdvancedSkill Level
- 4.8+
- 265
Learn how to use RNNs to classify text sentiment, generate sentences, and translate text between languages.
Artificial Intelligence
Course
Gen AI Agents: Transform Your Organization
- BasicSkill Level
- 4.8+
- 264
This course explores how organizations can use custom gen AI agents to help tackle specific business challenges.
Cloud
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Gemini in Google Sheets
- BasicSkill Level
- 4.6+
- 264
Analyze data smarter with Gemini in Google Sheets. Use AI-powered insights, formula suggestions, and automation to simplify spreadsheets and boost productivity.
Artificial Intelligence
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Gemini in Google Docs
- BasicSkill Level
- 4.7+
- 263
Write and edit faster with Gemini in Google Docs. Get AI-powered drafting, rewriting, and content suggestions to create clear, polished documents effortlessly.
Artificial Intelligence
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Analyzing Survey Data in R
- IntermediateSkill Level
- 4.4+
- 261
Learn survey design using common design structures followed by visualizing and analyzing survey results.
Probability & Statistics
Course
Concepts in Computer Science
- BasicSkill Level
- 4.6+
- 260
Learn how computers work, design efficient algorithms, and explore computational theory to solve real-world problems.
Software Development
Course
Statistical Thinking in Python (Part 2)
- IntermediateSkill Level
- 4.6+
- 258
Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.
Probability & Statistics
Course
Develop for Azure Storage
- IntermediateSkill Level
- 4.4+
- 258
Learn how to store, secure, scale, and process data in Azure using Blob Storage, Cosmos DB, queues, and event-driven services.
Cloud
Course
MLOps for Business
- BasicSkill Level
- 4.7+
- 257
Learn about MLOps, including the tools and practices needed for automating and scaling machine learning applications.
Machine Learning
Course
Joining Data with data.table in R
- IntermediateSkill Level
- 4.2+
- 255
This course will show you how to combine and merge datasets with data.table.
Data Manipulation
Course
Survival Analysis in R
- IntermediateSkill Level
- 4.8+
- 252
Learn to work with time-to-event data. The event may be death or finding a job after unemployment. Learn to estimate, visualize, and interpret survival models!
Probability & Statistics
Course
Factor Analysis in R
- AdvancedSkill Level
- 4.7+
- 252
Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.
Probability & Statistics
Course
Create Engaging Video with Google Vids
- BasicSkill Level
- 4.7+
- 250
Create and refine videos faster with Gemini in Google Vids. Use AI-powered storyboarding and content generation to produce polished videos with ease.
Cloud
Course
Data Transformation in KNIME
- BasicSkill Level
- 4.6+
- 250
Enhance your KNIME skills with our course on data transformation, column operations, and workflow optimization.
Data Preparation
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Visualizing Geospatial Data in R
- IntermediateSkill Level
- 4.4+
- 249
Learn to read, explore, and manipulate spatial data then use your skills to create informative maps using R.
Data Visualization
Course
Interactive Data Visualization with plotly in R
- BasicSkill Level
- 4.5+
- 247
Learn how to use plotly in R to create interactive data visualizations to enhance your data storytelling.
Data Visualization
Course
Introduction to Testing in Java
- AdvancedSkill Level
- 4.7+
- 246
Learn how to write effective tests in Java using JUnit and Mockito to build robust, reliable applications with confidence.
Software Development
Course
Advanced Probability: Uncertainty in Data
- AdvancedSkill Level
- 4.6+
- 246
Develop a better intuition for advanced probability, risk assessment, and simulation techniques to make data-driven business decisions with confidence.
Probability & Statistics
Course
Analyzing IoT Data in Python
- IntermediateSkill Level
- 4.7+
- 245
Learn how to import, clean and manipulate IoT data in Python to make it ready for machine learning.
Data Manipulation
Course
Spoken Language Processing in Python
- AdvancedSkill Level
- 4.7+
- 243
Learn how to load, transform, and transcribe speech from raw audio files in Python.
Data Manipulation
Course
Gemini in Google Slides
- BasicSkill Level
- 4.6+
- 243
Create impactful presentations faster with Gemini in Google Slides. Use AI-powered design and suggestions to build professional, engaging slides in minutes.
Artificial Intelligence
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.