Course
Scalable AI Models with PyTorch Lightning
- IntermediateSkill Level
- 4.8+
- 179
Streamline your AI projects by building modular models and mastering advanced optimization with PyTorch Lightning!
Artificial Intelligence
Data, AI, and Cloud Courses
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Course
Data Visualization in KNIME
- BasicSkill Level
- 4.8+
- 178
Learn to create compelling data visualizations with KNIME, covering charts, components, and dashboards.
Data Visualization
Course
Develop for Azure Storage
- IntermediateSkill Level
- 4.8+
- 178
Learn how to store, secure, scale, and process data in Azure using Blob Storage, Cosmos DB, queues, and event-driven services.
Cloud
Course
Querying a PostgreSQL Database in Java
- AdvancedSkill Level
- 4.8+
- 176
Connect Java to PostgreSQL with JDBC. Write secure queries, manage transactions, and handle large datasets efficiently.
Software Development
Course
Market Basket Analysis in R
- IntermediateSkill Level
- 4.8+
- 173
Explore association rules in market basket analysis with R by analyzing retail data and creating movie recommendations.
Data Manipulation
Course
Working with the OpenAI Responses API
- IntermediateSkill Level
- 4.8+
- 172
Build smart, interactive, and reliable AI applications easier than ever before with the OpenAI Responses API and GPT-5.
Artificial Intelligence
Course
Python for R Users
- IntermediateSkill Level
- 4.7+
- 172
This course is for R users who want to get up to speed with Python!
Software Development
Course
Analyzing Social Media Data in Python
- IntermediateSkill Level
- 4.9+
- 170
In this course, youll learn how to collect Twitter data and analyze Twitter text, networks, and geographical origin.
Data Manipulation
Course
Nonlinear Modeling with Generalized Additive Models (GAMs) in R
- IntermediateSkill Level
- 4.8+
- 170
GAMs model relationships in data as nonlinear functions that are highly adaptable to different types of data science problems.
Probability & Statistics
Course
Serverless Applications with AWS Lambda
- IntermediateSkill Level
- 4.8+
- 170
Build, deploy, and optimize serverless apps with AWS Lambda. Master event processing, error handling, concurrency, and safe deployments in a live AWS Console.
Cloud
Course
Modernize Infrastructure and Applications with Google Cloud
- BasicSkill Level
- 4.9+
- 168
Modernize Infrastructure and Applications with Google Cloud
Cloud
Course
Building Dashboards with shinydashboard
- BasicSkill Level
- 4.7+
- 168
Learn to create interactive dashboards with R using the powerful shinydashboard package. Create dynamic and engaging visualizations for your audience.
Reporting
Course
Visualizing Geospatial Data in R
- IntermediateSkill Level
- 4.6+
- 167
Learn to read, explore, and manipulate spatial data then use your skills to create informative maps using R.
Data Visualization
Machine Learning
Course
Quantitative Risk Management in R
- BasicSkill Level
- 4.9+
- 164
Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.
Applied Finance
Course
Text Mining with Bag-of-Words in R
- IntermediateSkill Level
- 4.8+
- 163
Learn the bag of words technique for text mining with R.
Machine Learning
Course
Machine Learning for Marketing Analytics in R
- IntermediateSkill Level
- 4.9+
- 161
In this course youll learn how to use data science for several common marketing tasks.
Machine Learning
Course
Case Studies: Building Web Applications with Shiny in R
- IntermediateSkill Level
- 4.9+
- 160
Practice your Shiny skills while building some fun Shiny apps for real-life scenarios!
Reporting
Course
Machine Learning in the Tidyverse
- IntermediateSkill Level
- 4.8+
- 157
Leverage tidyr and purrr packages in the tidyverse to generate, explore, and evaluate machine learning models.
Machine Learning
Course
Credit Risk Modeling in R
- IntermediateSkill Level
- 4.8+
- 156
Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.
Applied Finance
Course
Survival Analysis in Python
- AdvancedSkill Level
- 4.8+
- 155
Use survival analysis to work with time-to-event data and predict survival time.
Probability & Statistics
Course
GARCH Models in R
- AdvancedSkill Level
- 4.8+
- 153
Specify and fit GARCH models to forecast time-varying volatility and value-at-risk.
Applied Finance
Course
Python for Spreadsheet Users
- BasicSkill Level
- 4.9+
- 151
Use your knowledge of common spreadsheet functions and techniques to explore Python!
Software Development
Course
Conditional Formatting in Google Sheets
- BasicSkill Level
- 4.8+
- 151
Learn how to use conditional formatting with your data through built-in options and by creating custom formulas.
Data Manipulation
Course
Structural Equation Modeling with lavaan in R
- AdvancedSkill Level
- 4.8+
- 150
Learn how to create and assess measurement models used to confirm the structure of a scale or questionnaire.
Probability & Statistics
Course
Error and Uncertainty in Google Sheets
- IntermediateSkill Level
- 4.7+
- 149
Learn to distinguish real differences from random noise, and explore psychological crutches we use that interfere with our rational decision making.
Probability & Statistics
Course
Building AI Agents with Haystack
- IntermediateSkill Level
- 4.8+
- 145
Create a healthcare AI agent using Haystack, an open-source framework for orchestrating LLMs and external components.
Artificial Intelligence
Course
Handling Missing Data with Imputations in R
- AdvancedSkill Level
- 4.7+
- 144
Diagnose, visualize and treat missing data with a range of imputation techniques with tips to improve your results.
Data Manipulation
Course
Interactive Data Visualization with plotly in R
- BasicSkill Level
- 4.8+
- 143
Learn how to use plotly in R to create interactive data visualizations to enhance your data storytelling.
Data Visualization
Course
Importing Data in Java
- IntermediateSkill Level
- 4.8+
- 142
Learn to import, manipulate, and transform data in Java using the Tablesaw library. Work with CSV files, tabular structures, and complex JSON formats.
Software Development
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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