Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
or
Course
Learn to use AI as a senior engineering partner for code analysis, performance optimization, security, and software architecture decisions.
Artificial Intelligence
Course
Gain an overview of AI Agents. Discover how AI Agents use autonomous action and reasoning to solve complex problems.
Cloud
Course
Learn how to create pivot tables and quickly organize thousands of data points with just a few clicks.
Data Manipulation
Course
Analyze data smarter with Gemini in Google Sheets. Use AI-powered insights, formula suggestions, and automation to simplify spreadsheets and boost productivity.
Artificial Intelligence
Course
Use a chatbot to create a study guide tailored to your goals and schedule. Build skills with simple, effective prompts.
Artificial Intelligence
Course
Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.
Software Development
Course
Learn how to create a PostgreSQL database and explore the structure, data types, and how to normalize databases.
Data Preparation
Course
Learn how to clean data with Apache Spark in Python.
Data Preparation
Course
Ask data questions in plain English with Databricks Genie - build spaces, curate business language, and monitor quality.
Data Engineering
Course
Learn fundamental natural language processing techniques using Python and how to apply them to extract insights from real-world text data.
Machine Learning
Course
Data visualization is one of the most desired skills for data analysts. This course allows you to present your findings better using Tableau.
Data Visualization
Course
Build smart, interactive, and reliable AI applications easier than ever before with the OpenAI Responses API and GPT-5.
Artificial Intelligence
Course
Master AI for marketing to plan smarter campaigns, create quality content, and build custom AI agents.
Artificial Intelligence
Course
Unlock Alteryx for data transformation, mastering Crosstab, Transpose, and workflow optimization in this interactive course.
Data Manipulation
Course
Learn techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.
Machine Learning
Course
This course provides an overview of the opportunities and challenges companies encounter in their digital transformation journey.
Cloud
Course
Learn to use the KNIME Analytics Platform for data access, cleaning, and analysis with a no-code/low-code approach.
Data Preparation
Course
Sharpen your skills in Oracle SQL including SQL basics, aggregating, combining, and customizing data.
Data Manipulation
Course
Learn the practical uses of A/B testing in Python to run and analyze experiments. Master p-values, sanity checks, and analysis to guide business decisions.
Probability & Statistics
Course
Organize and manage files with Gemini in Google Drive. Use AI-powered search to quickly find information, streamline collaboration, and boost productivity.
Artificial Intelligence
Course
Learn how to transform raw data into clean, reliable models with dbt through hands-on, real-world exercises.
Data Engineering
Course
Master the core operations of spaCy and train models for natural language processing. Extract information from unstructured data and match patterns.
Machine Learning
Course
This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.
Probability & Statistics
Course
Learn how to leverage statistical techniques using spreadsheets to more effectively work with and extract insights from your data.
Probability & Statistics
Course
Build SQL skills by writing AI prompts that generate queries for sorting, grouping, filtering, and categorizing data.
Data Manipulation
Course
Explore Azure services like Compute, Storage, and Automation, with hands-on experience.
Cloud
Course
Discover how Marketing Analysts use data to understand customers and drive business growth.
Leadership
Course
Are customers thrilled with your products or is your service lacking? Learn how to perform an end-to-end sentiment analysis task.
Machine Learning
Course
Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.
Machine Learning
Course
In this course, youll learn the basics of relational databases and how to interact with them.
Data Manipulation
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.
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.
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.
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.
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.
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.
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.
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.
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.
Make progress on the go with our mobile courses and daily 5-minute coding challenges.