Course
Data-Driven Decision Making in SQL
- IntermediateSkill Level
- 4.8+
- 2.7K
Learn how to analyze a SQL table and report insights to management.
Data Literacy
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Course
Introduction to NumPy
- BasicSkill Level
- 4.8+
- 2.7K
Master your skills in NumPy by learning how to create, sort, filter, and update arrays using NYC’s tree census.
Data Manipulation
Course
MLOps Concepts
- IntermediateSkill Level
- 4.8+
- 2.7K
Discover how MLOps can take machine learning models from local notebooks to functioning models in production that generate real business value.
Machine Learning
Course
Introduction to LLMs in Python
- IntermediateSkill Level
- 4.8+
- 2.6K
Learn the nuts and bolts of LLMs and the revolutionary transformer architecture they are based on!
Artificial Intelligence
Course
Intermediate Deep Learning with PyTorch
- IntermediateSkill Level
- 4.8+
- 2.6K
Learn about fundamental deep learning architectures such as CNNs, RNNs, LSTMs, and GRUs for modeling image and sequential data.
Artificial Intelligence
Course
Introduction to SQL Server
- BasicSkill Level
- 4.8+
- 2.5K
Learn to use SQL Server to perform common data manipulation tasks and master common data manipulation tasks using this database system.
Software Development
Course
Large Language Models for Business
- BasicSkill Level
- 4.8+
- 2.5K
Learn about Large Language Models (LLMs) and how they are reshaping the business world.
Artificial Intelligence
Course
Data Governance Concepts
- BasicSkill Level
- 4.8+
- 2.5K
Gain an introduction to data governance, exploring its meaning, purpose, and how to implement a data governance framework.
Data Management
Course
Introduction to Embeddings with the OpenAI API
- IntermediateSkill Level
- 4.8+
- 2.5K
Unlock more advanced AI applications, like semantic search and recommendation engines, using OpenAIs embedding model!
Artificial Intelligence
Course
Software Development with GitHub Copilot
- IntermediateSkill Level
- 4.9+
- 2.3K
Master GitHub Copilot to understand, write, and refine code with context, customization, and smart features.
Artificial Intelligence
Course
Writing Functions in Python
- IntermediateSkill Level
- 4.8+
- 2.2K
Learn to use best practices to write maintainable, reusable, complex functions with good documentation.
Software Development
Course
Introduction to Importing Data in R
- BasicSkill Level
- 4.8+
- 2.2K
In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.
Data Preparation
Course
Hypothesis Testing in Python
- IntermediateSkill Level
- 4.8+
- 2.1K
Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests in Python.
Probability & Statistics
Course
Introduction to Data Security
- BasicSkill Level
- 4.8+
- 2.1K
Discover how to become a data defender and keep data safe and secure with this beginner-friendly interactive course.
Data Management
Course
Financial Modeling in Excel
- IntermediateSkill Level
- 4.9+
- 1.9K
Learn about Excel financial modeling, including cash flow, scenario analysis, time value, and capital budgeting.
Applied Finance
Course
Software Development with Claude Code
- IntermediateSkill Level
- 4.9+
- 1.9K
Claude Code brings AI assistance to your terminal. Learn the workflows that turn it into a reliable tool for real software development.
Artificial Intelligence
Course
Sampling in Python
- IntermediateSkill Level
- 4.8+
- 1.9K
Learn to draw conclusions from limited data using Python and statistics. This course covers everything from random sampling to stratified and cluster sampling.
Probability & Statistics
Course
Data Types in Python
- IntermediateSkill Level
- 4.8+
- 1.9K
Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them to solve Data Science problems.
Software Development
Course
Introduction to Data Quality
- BasicSkill Level
- 4.8+
- 1.8K
Explore the basics of data quality management. Learn the key concepts, dimensions, and techniques for monitoring and improving data quality.
Data Management
Course
Hypothesis Testing in R
- IntermediateSkill Level
- 4.8+
- 1.8K
Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.
Probability & Statistics
Course
Introduction to Kubernetes
- IntermediateSkill Level
- 4.8+
- 1.8K
In this course, you will learn the fundamentals of Kubernetes and deploy and orchestrate containers using Manifests and kubectl instructions.
Software Development
Course
Machine Learning for Business
- BasicSkill Level
- 4.8+
- 1.8K
Understand the fundamentals of Machine Learning and how its applied in the business world.
Machine Learning
Course
Introduction to Model Context Protocol (MCP)
- IntermediateSkill Level
- 4.9+
- 1.8K
Integrate AI/LLM applications with APIs, databases, and filesystems easier than ever before with the Model Context Protocol (MCP).
Artificial Intelligence
Course
Intermediate GitHub Concepts
- IntermediateSkill Level
- 4.8+
- 1.7K
Level up your GitHub skills with our intermediate course on GitHub Projects, Administration, and advanced security features.
Software Development
Course
Exploratory Data Analysis in R
- IntermediateSkill Level
- 4.8+
- 1.7K
Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.
Exploratory Data Analysis
Course
Vector Databases for Embeddings with Pinecone
- IntermediateSkill Level
- 4.8+
- 1.6K
Discover how the Pinecone vector database is revolutionizing AI application development!
Artificial Intelligence
Course
Introduction to Data Ethics
- BasicSkill Level
- 4.8+
- 1.6K
Explore data ethics with this comprehensive introductory course, covering principles, AI ethics, and practical skills to ensure responsible data use.
Data Literacy
Course
Joining Data with dplyr
- BasicSkill Level
- 4.8+
- 1.5K
Learn to combine data across multiple tables to answer more complex questions with dplyr.
Data Manipulation
Course
Multi-Agent Systems with LangGraph
- AdvancedSkill Level
- 4.9+
- 1.5K
Build powerful multi-agent systems by applying emerging agentic design patterns in the LangGraph framework.
Artificial Intelligence
Course
Introduction to Data Engineering
- IntermediateSkill Level
- 4.8+
- 1.4K
Learn about the world of data engineering in this short course, covering tools and topics like ETL and cloud computing.
Data Engineering
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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