Implementing AI: AI and ML Frameworks & Platforms

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Understanding how to implement AI is just crucial to your project’s success. This course will explore the common frameworks to implement AI models, as well as focus on operating in different environments such as the Cloud. It will also go over what is cloud-native Machine Learning and various AI tools available. This intermediate level course is best for those implementing AI such as project managers or those in a technical role.

What Will I Learn?

  • Common frameworks to implement AI models
  • Different environments for operationalizing AI models
  • Cloud Environment
  • On premise Environment
  • Edge Environment
  • Hybrid Environment
  • Cloud-native Machine Learning
  • Advantages/disadvantages to cloud-native ML

Who is this Training For?

  • Project Manager
  • Product Manager
  • Capability Manager
  • Technical Manager
  • Acquisitions Manager
  • Procurement & Contracting Officers
  • Computer Systems Programmer
  • Developer
  • AI Research Associate
  • Data Scientist
  • AI / Machine Learning (ML) EngineerAI 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
  • Data technician
  • Program manager
  • Project manager
  • Supply program manager
  • Designers

Supported Learning Paths

  • Cognilytica: CPMAI Certification
  • DoD JAIC: Drive AI, Create AI, Embed AI, Facilitate AI
  • Edison DSF: Data Science Professionals (DSP04 -DSP09), Data Engineering & Management Professionals (DSP10-DSP16)

Learning Levels

  • DoD JAIC AI: Intermediate (Applied) Level
  • Edison DSF: Level 4-5
  • Category: Implementing AI