Final Exam: AI Architect
Artificial intelligence | Intermediate
- 1 video | 32s
- Includes Assessment
- Earns a Badge
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
Describe anti-patterns commonly found in ai architecturesdescribe ai libraries and their advantages/disadvantagesdescribe how microservices and edmlm patterns workexplain differences between ai architect role and other its rolesdescribe how kappa & lambda architecture patterns workrecognize differences between tactical, strategic, and tactical-strategic planningdescribe differences between tactical, strategic, and tactical-strategic planningdescribe explainable ai and its significancerecognize the relationships between the ai maturity model, ai maturity assessment, tools, metrics % kpis, and analytic dashboardsdescribe how the ai architect interacts with different groups in the enterpriserecognize the importance of complexity vs. business value plots in ai enterprise planningdescribe how ai accelerators reduce the complexity of projects while shortening their timelinesdiscover what is an ai accelerator, and identify some of the main ai acceleratorsidentify three standard ai applications in the pharmaceutical industryidentify and contrast ai architecture and design patternsdescribe three standard ai applications in the pharmaceutical industrydefine ai architect workdescribe the interpretability problem and its importancedescribe how federated learning pattern worksdescribe three standard ai applications in the utility industrywhich patterns are used in each ai development phasedescribe three standard ai applications in the telecommunications industrydescribe three standard ai applications in the cybersecurity industrycompare/contrast ai technologies, frameworks, and platformsdescribe the keras framework and its advantages/disadvantagesdescribe axiomatic attribution at a high leveldescribe intelligible models at a high leveldescribe feature visualization at a high leveldescribe the counterfactual method at a high leveldescribe three standard ai applications in the transportation industry
describe three standard ai applications in salesdescribe three standard ai applications in manufacturingidentify how current projects vs ai accelerators dependency maps are used to create an ai enterprise roadmapdescribe how dblmlm pattern worksdescribe rationalization at a high levelcontrast and compare ai applications in different industriesdescribe monotonicity at a high leveldescribe three standard ai applications in marketingdescribe ai platforms and their advantages/disadvantagesidentify how current projects vs. ai accelerators dependency maps are used to create an ai enterprise roadmapdescribe the mxnet framework and its advantages/disadvantagescontrast ai enterprise planning with it enterprise planning with plain enterprise planningidentify artificial intelligence data set typesidentify ai platforms and their advantages/disadvantagesdescribe three standard ai applications in the financial industrydescribe how data lake pattern worksdescribe what organizations the ai architect participates in as a memberdescribe pre-trained models and their advantages/disadvantagesdescribe the pytorch framework and its advantages/disadvantagesdescribe the cntk framework and its advantages/disadvantagesdescribe what is a discovery map, its sections, and its role in ai enterprise planningdescribe how daisy architecture pattern worksdefine the ai architect roleidentify the relationships between the ai maturity model, ai maturity assessment, tools, metrics % kpis, and analytic dashboardsdescribe how gra pattern worksdescribe how closed-loop intelligence pattern worksdescribe "right to explanation" regulationsdescribe how dase pattern worksdescribe the theano framework and its advantages/disadvantagesrecognize rationalization at a high level
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