Foundations of AI & ML for AI Practitioners

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This course is for practitioners who are looking to get an overview of AI, ML, and cognitive technologies. This course will provide you with an introduction to AI and ML concepts, key terms, conceptualizing probabilistic reasoning, core elements of AI stack, a history of AI, previous pitfalls in the advancement of AI, and additional concepts as needed. Ideal roles for this course include data scientists, programmers, Network Analyst, Data Analyst, or anyone in a practitioner or technical role looking for a foundational level AI course.

What Will I Learn?

  • AI Terminology
  • AI, Machine Learning, Deep Learning, and Neural Networks
  • Augmented intelligence
  • Busting AI Myths
  • Why AI Now?
  • The Right (and Wrong) Fit for AI Projects
  • AI Enabled Future
  • The Seven Patterns of AI
  • The Relationship between Data and AI
  • Taking the right perspective on AI

Who is this Training For?

  • Computer Systems Programmer
  • Developer
  • Artificial Intelligence 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
  • Network Infrastructure Engineer
  • Information Technician
  • Data engineer
  • Network operations
  • Information technician

Supported Learning Paths

  • Cognilytica: CPMAI, Procuring AI 
  • DoD JAIC Archetypes / Paths: Create AI, Embed AI
  • Edison DSF: Data Science Professionals (DSP04 -DSP09), Data Engineering & Management Professionals (DSP10-DSP16), Operations & Technical Support (DSP17-DSP19)

Learning Levels

  • DoD JAIC AI : Intermediate (Applied) Level
  • Edison DSF: Level 3-4
  • Category: Foundations of AI & Data Science