Data Engineering for AI

Current Status
Not Enrolled
Coming Soon
Get Started
This course is currently closed

Data engineers are responsible for creating systems and tools that allow companies to aggregate and manipulate data from a variety of sources. This course provides an overview of what data engineers need to be able to identify, extract, and pull together available and pertinent heterogeneous data, including modern data sources such as social media data, open data, governmental data. This advanced level course will provide details for folks who are in a technical role and proficient in AI and big data tools.

What Will I Learn?

  • What is Data Engineering?
  • The role of a Data Engineer
  • Data Scientists vs. Data Engineers
  • How Data Engineering fits into data management
  • Data Engineering in the context of AI Projects
  • Big Data Infrastructure
  • Big Data Methodologies
  • Applying what we learned from Big Data Projects
  • Dealing with small amounts of data for AI
  • Taking a Data-Centric Mentality on AI

Who is this Training For?

  • Computer Systems Programmer
  • Developer
  • AI Research Associate
  • Data Scientist
  • AI / Machine Learning (ML) Engineer
  • AI Assurance Engineer
  • Test & Evaluation Engineer
  • System Engineer
  • Network Analyst
  • Data Analyst
  • Operations Research Analyst
  • Deployment Engineer
  • Knowledge Operations Manager
  • Information Technician
  • Data engineer
  • Network operations
  • Information technician
  • Data technician
  • Network Infrastructure Engineer

Supported Learning Paths

  • DoD JAIC:  Create AI, Embed AI
  • Edison DSF: Data Science Professionals (DSP04 -DSP09), Data Engineering & Management Professionals (DSP10-DSP16), Operations & Technical Support (DSP17-DSP19), Data & User Support (DSP20-DSP22)

Learning Levels

  • DoD JAIC AI: Advanced (Applied) Level
  • Edison DSF: Level 4-5
  • Category: Data Engineering & Management