Data Science Overview is an introductory level course that introduces the entire multi-disciplinary Data Science team to the many evolving and related terms, with focus on Big Data, Data Science, Predictive Analytics, Artificial Intelligence, Data Mining, Data Warehousing. The overview explores the current state of the art and science, the major components of a modern data science infrastructure, team roles and responsibilities, and level-setting realistic possible outcomes for your investment. This goal of this course is to provide students with a baseline understanding of core concepts and technologies to a conversant level.
Learning Objectives
- Foundations: Grids & Virtualization; SOA, ESB / EMB, The Cloud
- The Hadoop Ecosystem: HDFS; Resource Navigators, MapReduce, Spark, Distributions
- Big Data, NOSQL, and ETL
- ETL: Exchange, Transform, Load
- Handling Data & a Survey of Useful tools
- enterprise Integration Patterns and Message Busses
- Developing in Hadoop Ecosystem: R, Python, Java, Scala, Pig, and BPMN
- Artificial Intelligence and Business Systems
- Who’s on the Team? Evolving Roles and Functions in Data Science
- Growing your Infrastructure
Framework Connections
The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):
Competency Areas
Work Roles
Feedback
If you would like to provide feedback on this course, please e-mail the NICCS team at NICCS@mail.cisa.dhs.gov. Please keep in mind that NICCS does not own this course or accept payment for course entry. If you have questions related to the details of this course, such as cost, prerequisites, how to register, etc., please contact the course training provider directly. You can find course training provider contact information by following the link that says “Visit course page for more information...” on this page.