Final Exam: AI Architect

WHAT YOU WILL LEARN

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  Describe anti-patterns commonly found in ai architectures
  

  describe ai libraries and their advantages/disadvantages
  

  describe how microservices and edmlm patterns work
  

  explain differences between ai architect role and other its roles
  

  describe how kappa & lambda architecture patterns work
  

  recognize differences between tactical, strategic, and tactical-strategic planning
  

  describe differences between tactical, strategic, and tactical-strategic planning
  

  describe explainable ai and its significance
  

  recognize the relationships between the ai maturity model, ai maturity assessment, tools, metrics % kpis, and analytic dashboards
  

  describe how the ai architect interacts with different groups in the enterprise
  

  recognize the importance of complexity vs. business value plots in ai enterprise planning
  

  describe how ai accelerators reduce the complexity of projects while shortening their timelines
  

  discover what is an ai accelerator, and identify some of the main ai accelerators
  

  identify three standard ai applications in the pharmaceutical industry
  

  identify and contrast ai architecture and design patterns
  

  describe three standard ai applications in the pharmaceutical industry
  

  define ai architect work
  

  describe the interpretability problem and its importance
  

  describe how federated learning pattern works
  

  describe three standard ai applications in the utility industry
  

  which patterns are used in each ai development phase
  

  describe three standard ai applications in the telecommunications industry
  

  describe three standard ai applications in the cybersecurity industry
  

  compare/contrast ai technologies, frameworks, and platforms
  

  describe the keras framework and its advantages/disadvantages
  

  describe axiomatic attribution at a high level
  

  describe intelligible models at a high level
  

  describe feature visualization at a high level
  

  describe the counterfactual method at a high level
  

  describe three standard ai applications in the transportation industry
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  describe three standard ai applications in sales
  

  describe three standard ai applications in manufacturing
  

  identify how current projects vs ai accelerators dependency maps are used to create an ai enterprise roadmap
  

  describe how dblmlm pattern works
  

  describe rationalization at a high level
  

  contrast and compare ai applications in different industries
  

  describe monotonicity at a high level
  

  describe three standard ai applications in marketing
  

  describe ai platforms and their advantages/disadvantages
  

  identify how current projects vs. ai accelerators dependency maps are used to create an ai enterprise roadmap
  

  describe the mxnet framework and its advantages/disadvantages
  

  contrast ai enterprise planning with it enterprise planning with plain enterprise planning
  

  identify artificial intelligence data set types
  

  identify ai platforms and their advantages/disadvantages
  

  describe three standard ai applications in the financial industry
  

  describe how data lake pattern works
  

  describe what organizations the ai architect participates in as a member
  

  describe pre-trained models and their advantages/disadvantages
  

  describe the pytorch framework and its advantages/disadvantages
  

  describe the cntk framework and its advantages/disadvantages
  

  describe what is a discovery map, its sections, and its role in ai enterprise planning
  

  describe how daisy architecture pattern works
  

  define the ai architect role
  

  identify the relationships between the ai maturity model, ai maturity assessment, tools, metrics % kpis, and analytic dashboards
  

  describe how gra pattern works
  

  describe how closed-loop intelligence pattern works
  

  describe "right to explanation" regulations
  

  describe how dase pattern works
  

  describe the theano framework and its advantages/disadvantages
  

  recognize rationalization at a high level