Data Science

Learn Data Science from the best Data Science tutorials, including the most popular Data Science online courses, videos, books, podcasts, and blogs.

Resource type
Cost
Skill level
Certificate

SuperDataScience

By joining our new platform, you will have the fantastic opportunity to learn the essence of both the theory and practice with plenty of hands-on exercises, real-world case studies and on-demand video lessons.

Data Science with R

Data science is becoming more and more valuable to the workplace and to the global economy. Learn how to use the practice of data science and the programming language R to transform your data into actionable insight.

Hands-On Reinforcement Learning with Python

The book starts with an introduction to Reinforcement Learning followed by OpenAI Gym, and TensorFlow. You will then explore various RL algorithms and concepts, such as Markov Decision Process, Monte Carlo methods, and dynamic programming, including value and policy iteration.

Beginning Data Science with Python and Jupyter

Get to grips with the skills you need for entry-level data science in this hands-on Python and Jupyter course. You'll learn about some of the most commonly used libraries that are part of the Anaconda distribution, and then explore machine learning models with real datasets to give you the skills and exposure you need for the real world.

O'Reilly Data Show

The O'Reilly Data Show Podcast explores the opportunities and techniques driving big data, data science, and AI. Subscribe on Apple Podcasts, Stitcher, Google Play, and RSS.

Think Like a Data Scientist

Think Like a Data Scientist teaches you a step-by-step approach to solving real-world data-centric problems. By breaking down carefully crafted examples, you'll learn to combine analytic, programming, and business perspectives into a repeatable process for extracting real knowledge from data

Streaming Data

Streaming Data introduces the concepts and requirements of streaming and real-time data systems. The book is an idea-rich tutorial that teaches you to think about how to efficiently interact with fast-flowing data.

Reactive Data Handling

Reactive Data Handling is a collection of five hand-picked chapters introducing you to building reactive applications capable of handling real-time processing with large data loads. You'll start with the high-level architecture of reactive applications and then look at low-level practical aspects.

Practical Data Science with R, Second Edition

Practical Data Science with R, Second Edition takes a practice-oriented approach to explaining basic principles in the ever expanding field of data science. You'll jump right to real-world use cases as you apply the R programming language and statistical analysis techniques to carefully explained examples based in marketing, business intelligence, and decision support.

Mastering Large Datasets

Modern data science solutions need to be clean, easy to read, and scalable. In Mastering Large Datasets with Python, author J.T. Wolohan teaches you how to take a small project and scale it up using a functionally influenced approach to Python coding. You'll explore methods and built-in Python tools that lend themselves to clarity and scalability, like the high-performing parallelism method, as well as distributed technologies that allow for high data throughput.

Introducing Data Science

Introducing Data Science teaches you how to accomplish the fundamental tasks that occupy data scientists. Using the Python language and common Python libraries, you'll experience firsthand the challenges of dealing with data at scale and gain a solid foundation in data science.

Exploring the Data Jungle

Exploring the Data Jungle: Finding, Preparing, and Using Real-World Data is a collection of three hand-picked chapters introducing you to the often-overlooked art of putting unfamiliar data to good use.

Exploring Data Science

Exploring Data Science is a collection of five hand-picked chapters introducing you to various areas in data science and explaining which methodologies work best for each.