Data Science

Bridge the gap between developer and data scientist by creating a modern open-source, Python-based toolset that works with Jupyter Notebook, and PixieDust.

Cut through the noise and get real results with a step-by-step approach to data science

Gain useful insights from your data using popular data science tools

Become an efficient data science practitioner by understanding Python's key concepts

Take the strategic and systematic approach to analyze data to solve business problems

Learn the techniques and math you need to start making sense of your data

Master the techniques and sophisticated analytics used to construct Spark-based solutions that scale to deliver production-grade data science products

Understand the concepts and methodologies to manage and deliver top-notch Data Science solutions for your organization.

Data collection, processing, analysis, and more

Examine the techniques and Java tools supporting the growing field of data science

Apply deep learning techniques and neural network methodologies to build, train, and optimize generative network models

Big data processing and analytics at speed and scale using command line tools.

Find, explore, and extract big data to transform into actionable insights

Practical examples for professionals using R in Data science

Develop, deploy, and streamline your data science projects with the most popular end-to-end platform, Anaconda