Final Exam: AI Architect

Artificial intelligence    |    Intermediate
  • 1 Video | 30m 32s
  • Includes Assessment
  • Earns a Badge
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Final Exam: AI Architect will test your knowledge and application of the topics presented throughout the AI Architect track of the Skillsoft Aspire AI Apprentice to AI Architect Journey.

WHAT YOU WILL LEARN

  • compare/contrast ai technologies, frameworks, and platforms
    contrast AI Enterprise Planning with IT Enterprise Planning with plain Enterprise Planning
    contrast and compare AI applications in different industries
    define ai architect work
    define the ai architect role
    describe AI libraries and their advantages/disadvantages
    describe AI platforms and their advantages/disadvantages
    describe anti-patterns commonly found in AI architectures
    describe axiomatic attribution at a high level
    describe differences between tactical, strategic, and tactical-strategic planning
    describe explainable ai and its significance
    describe feature visualization at a high level
    describe how AI Accelerators reduce the complexity of projects while shortening their timelines
    describe how Closed-Loop Intelligence pattern works
    describe how Daisy Architecture pattern works
    describe how DASE pattern works
    describe how Data Lake pattern works
    describe how DBLMLM pattern works
    describe how Federated Learning pattern works
    describe how GRA pattern works
    describe how Kappa & Lambda Architecture patterns work
    describe how Microservices and EDMLM patterns work
    describe how the ai architect interacts with different groups in the enterprise
    describe intelligible models at a high level
    describe monotonicity at a high level
    describe pre-trained models and their advantages/disadvantages
    describe rationalization at a high level
    describe "right to explanation" regulations
    describe the cntk framework and its advantages/disadvantages
    describe the counterfactual method at a high level
  • describe the interpretability problem and its importance
    describe the Keras framework and its advantages/disadvantages
    describe the mxnet framework and its advantages/disadvantages
    describe the pytorch framework and its advantages/disadvantages
    describe the theano framework and its advantages/disadvantages
    describe three standard AI applications in manufacturing
    describe three standard AI applications in marketing
    describe three standard AI applications in sales
    describe three standard AI applications in the cybersecurity industry
    describe three standard AI applications in the financial industry
    describe three standard AI applications in the pharmaceutical industry
    describe three standard AI applications in the telecommunications industry
    describe three standard AI applications in the transportation industry
    describe three standard AI applications in the utility industry
    describe what is a Discovery Map, its sections, and its role in AI Enterprise Planning
    describe what organizations the ai architect participates in as a member
    discover what is an AI Accelerator, and identify some of the main AI accelerators
    explain differences between ai architect role and other its roles
    identify AI platforms and their advantages/disadvantages
    identify and contrast AI Architecture and Design Patterns
    identify artificial intelligence data set types
    identify how Current Projects vs AI Accelerators Dependency Maps are used to create an AI Enterprise Roadmap
    identify how Current Projects vs. AI Accelerators Dependency Maps are used to create an AI Enterprise Roadmap
    identify the relationships between the AI Maturity Model, AI Maturity Assessment, tools, metrics % KPIs, and Analytic Dashboards
    identify three standard AI applications in the pharmaceutical industry
    recognize differences between tactical, strategic, and tactical-strategic planning
    recognize rationalization at a high level
    recognize the importance of Complexity vs. Business Value plots in AI Enterprise Planning
    recognize the relationships between the AI Maturity Model, AI Maturity Assessment, tools, metrics % KPIs, and Analytic Dashboards
    which Patterns are used in each AI Development Phase

IN THIS COURSE

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    AI Architect
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