Course Overview

This Data Science course will cover theory, practices, and domain to data relationships as part of process improvement using Java/C programming within a High Performance Computing environment. You'll be able to enhance your abilities as a data scientist by learning how to conduct research and development in an integrated environment. You'll learn how to configure large amounts of data for analysis on Compute Unified Device Architect equipment.

Productivity Objectives

After the completion of the High Performance Computing (HPC) Environment Data Science course, you will have:

1. Gained insight into the 'Roles' played by a Data Scientist.

2. Learned the principles of mapping business domains to solution techniques.

3. Explored parallel processing within Compute Unified Device Architecture (CUDA)

4. Analyzed massive data using Java and C in a CUDA environment.

5. Implemented selected Machine Learning Algorithms in a CUDA environment.

Course Outline

In the High Performance Computing Data Science training course you’ll learn

Role of the Data Scientist

Applied Research




Mapping Business Domains to Solution Techniques

Activity Based Principles

Business Domain to Data Mapping

Business Domain to Algorithm Mapping

Parallel Processing Within the Compute Unified Device Architecture

Basic Architecture

Process Flow

Basic CUDA Program Structure

Massive Data Analysis in a CUDA environment

Communication between Java and CUDA C

Hands-on industrial example of data science theory

Hands-on industrial example of program development

Ready to go to the next level?

Interactive training.