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Introduction to Scala
- IntermediateSkill Level
- 4.8+
- 236
Begin your journey with Scala, a popular language for scalable applications and data engineering infrastructure.
Software Development
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Course
Data Transformation in KNIME
- BasicSkill Level
- 4.8+
- 236
Enhance your KNIME skills with our course on data transformation, column operations, and workflow optimization.
Data Preparation
Course
Survival Analysis in R
- IntermediateSkill Level
- 4.8+
- 231
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
Introduction to Spark with sparklyr in R
- IntermediateSkill Level
- 4.7+
- 230
Learn how to run big data analysis using Spark and the sparklyr package in R, and explore Spark MLIb in just 4 hours.
Data Engineering
Course
Writing Efficient Code with pandas
- IntermediateSkill Level
- 4.8+
- 222
Learn efficient techniques in pandas to optimize your Python code.
Software Development
Course
Sentiment Analysis in R
- IntermediateSkill Level
- 4.8+
- 208
Learn sentiment analysis by identifying positive and negative language, specific emotional intent and making compelling visualizations.
Machine Learning
Course
Marketing Analytics in Tableau
- IntermediateSkill Level
- 4.8+
- 207
Master marketing analytics using Tableau. Analyze performance, benchmark metrics, and optimize strategies across channels.
Data Preparation
Course
Working with the OpenAI Responses API
- IntermediateSkill Level
- 4.8+
- 201
Build smart, interactive, and reliable AI applications easier than ever before with the OpenAI Responses API and GPT-5.
Artificial Intelligence
Course
Develop for Azure Storage
- IntermediateSkill Level
- 4.8+
- 200
Learn how to store, secure, scale, and process data in Azure using Blob Storage, Cosmos DB, queues, and event-driven services.
Cloud
Course
Data Manipulation in KNIME
- BasicSkill Level
- 4.8+
- 197
Automate data manipulation with KNIME, mastering merging, aggregation, database workflows, and advanced file handling.
Data Manipulation
Course
Analyzing IoT Data in Python
- IntermediateSkill Level
- 4.8+
- 196
Learn how to import, clean and manipulate IoT data in Python to make it ready for machine learning.
Data Manipulation
Course
Trust and Security with Google Cloud
- BasicSkill Level
- 4.9+
- 180
Trust and Security with Google Cloud
Cloud
Course
Market Basket Analysis in R
- IntermediateSkill Level
- 4.8+
- 178
Explore association rules in market basket analysis with R by analyzing retail data and creating movie recommendations.
Data Manipulation
Course
Python for R Users
- IntermediateSkill Level
- 4.7+
- 177
This course is for R users who want to get up to speed with Python!
Software Development
Course
Nonlinear Modeling with Generalized Additive Models (GAMs) in R
- IntermediateSkill Level
- 4.8+
- 174
GAMs model relationships in data as nonlinear functions that are highly adaptable to different types of data science problems.
Probability & Statistics
Course
Visualizing Geospatial Data in R
- IntermediateSkill Level
- 4.6+
- 172
Learn to read, explore, and manipulate spatial data then use your skills to create informative maps using R.
Data Visualization
Course
Machine Learning for Marketing Analytics in R
- IntermediateSkill Level
- 4.9+
- 170
In this course youll learn how to use data science for several common marketing tasks.
Machine Learning
Course
Survival Analysis in Python
- AdvancedSkill Level
- 4.8+
- 170
Use survival analysis to work with time-to-event data and predict survival time.
Probability & Statistics
Machine Learning
Course
Modernize Infrastructure and Applications with Google Cloud
- BasicSkill Level
- 4.9+
- 167
Modernize Infrastructure and Applications with Google Cloud
Cloud
Course
Conditional Formatting in Google Sheets
- BasicSkill Level
- 4.8+
- 163
Learn how to use conditional formatting with your data through built-in options and by creating custom formulas.
Data Manipulation
Course
Foundations of Inference in Python
- AdvancedSkill Level
- 4.9+
- 157
Get hands-on experience making sound conclusions based on data in this four-hour course on statistical inference in Python.
Probability & Statistics
Course
Statistical Simulation in Python
- IntermediateSkill Level
- 4.9+
- 154
Learn to solve increasingly complex problems using simulations to generate and analyze data.
Probability & Statistics
Course
Develop Azure Event-based and Message-based Solutions
- IntermediateSkill Level
- 4.7+
- 154
Learn to design scalable event-driven architectures in Azure using messaging services and real-world integrations.
Cloud
Course
Designing Forecasting Pipelines for Production
- AdvancedSkill Level
- 4.8+
- 153
Learn how to design, automate, and monitor scalable forecasting pipelines in Python.
Machine Learning
Course
End-to-End RAG with Weaviate
- IntermediateSkill Level
- 4.6+
- 151
Master RAG with Weaviate! Embed text and images for retrieval, and experiment with vector, BM25, and hybrid search.
Artificial Intelligence
Course
Handling Missing Data with Imputations in R
- AdvancedSkill Level
- 4.7+
- 149
Diagnose, visualize and treat missing data with a range of imputation techniques with tips to improve your results.
Data Manipulation
Course
Monitor and Troubleshoot Azure Solutions
- IntermediateSkill Level
- 4.7+
- 148
Learn how to monitor, diagnose, and optimize Azure applications using Azure Monitor, Application Insights, and Log Analytics.
Cloud
Course
Importing and Managing Financial Data in R
- IntermediateSkill Level
- 4.7+
- 142
Learn how to access financial data from local files as well as from internet sources.
Applied Finance
Course
Text-to-Query Agents with MongoDB and LangGraph
- IntermediateSkill Level
- 4.8+
- 137
Discover how to talk to your data using text-to-query AI agents with MongoDB and LangGraph.
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.
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