Final Exam: AI Apprentice
1 Video | 30m 32s
- Includes Assessment
- Earns a Badge
Final Exam: AI Apprentice will test your knowledge and application of the topics presented throughout the AI Apprentice track of the Skillsoft Aspire AI Apprentice to AI Architect Journey.
WHAT YOU WILL LEARN
classify different types of Convolutional Neural Networks by their structure and purposecompare artificial superintelligence with artificial general intelligence and specify the multiple factors needed to achieve themcompare cognitive modeling and artificial intelligencecompare image processing to Computer Visioncompare image processing to traditional methods of solving image problemscompare multiple approaches to AI development to distinguish key differences between themcompare the major differences between intelligent systems including search algorithms, machine learning systems, probabilistic models, neural networks, and reinforcement learning systemscompare the performance and functionality of Python AI toolbox to R AI toolboxconfigure the Python environment for developing AIdefine general intelligence in terms of AI tools known today and recognize the amount of work needed to achieve any AGIdefine Human-Computer Interaction as a multidisciplinary field essential to computer science and describe its importance for the success of software companiesdefine hybrid learning and describe examples of its usedefine narrow artificial intelligence, describe multiple areas of its use in the modern world, and recognize the latest researchdefine reactive and limited memory systems and describe reactive AI, limited memory AI, and a combination of bothdefine symbolic learning and describe examples of its usedescribe and distinguish between different types of modeling toolsdescribe and distinguish between multiple Python AI librariesdescribe basic concepts in Computer Visiondescribe distinguishing features of adaptive, interactive, iterative, and contextual cognitive modelsdescribe factors that make Python one of the most popular programming languagesdescribe how a CV is used in electronics and why cheap consumer electronics are not possible without CVdescribe how a CV is used in the aerospace industry and list the responsibilities of a CV system on an aircraftdescribe how a CV is used in the automotive industry and its role in the development of self-driving carsdescribe how the success of AI solutions in narrow fields is a combination of adequate task, good data, and appropriate tools and list fields that are most impacted by AIdescribe the principles of prototyping and distinguish between a prototype and a demonstration productdescribe the principles of the anthropomorphic approach to HCIdescribe the Python programming language and recognize its role in AI developmentdescribe the role Computer Vision plays in the industry and associated trendsdescribe the role of a user-oriented approach in the success of AI applicationsdescribe the steps needed to create deep learning models and identify guidelines for using them
describe the steps needed to create machine learning models and identify guidelines for using themdescribe true research on self-aware AI and compare it with common views on the future of AIdescribe why big data improve AI performance and accuracy by specifying how collecting large amounts of data creates opportunities for new AI development and researchdescribe why using artificial intelligence is becoming important today and list multiple factors that make the use of AI in business necessary for competitive advantagedifferentiate between interpreted and compiled programming languagesdistinguish between an intelligent system and pre-programmed logic using several definitions of artificial intelligence and specify the scope of AI applicationsidentify and describe problems that can be solved using Computer Visionidentify different types of cognitive models and name popular cognitive modeling applicationsidentify reasons why the iterative approach has shown to be most practical when designing software applicationsidentify the advantages of using Python when developing AIidentify the main steps in the HCI process and name multiple methodologies usedillustrate how AI can be part of a Computer Vision solutionillustrate how computer science is connected with cognitive modelinglist the components involved in human-computer interaction (HCI) studies and specify their rolelist the steps needed to create an object detection neural network and describe how object detection is performedlist the tools commonly used for HCI studies and specify their purposename and describe basic concepts in and cognition and cognitive modelingname and describe different types of cognitive learningrecognize how CI/CD became essential to any kind of software company and list multiple factors that make CI/CD important for AI companiesrecognize how the performance of Convolutional Neural Network revolutionized CVrecognize major AI tools used in the industryrecognize the most recent research breakthroughs in AI and how they might be used, and list applications of AI that are already on the marketrecognize the multidisciplinary nature of HCI and list the areas most involved in the studiesspecify how AI has affected cognitive modeling and enhanced its powerspecify multiple disciplines involved in cognitive modeling and describe their rolespecify the advantages of Jupyter Notebooks and create Jupyter Notebook files connected to the appropriate kernel environmentspecify the advantages of the Google Collab environment and create files in the environmentspecify the role of Anaconda in keeping clear working environmentsspecify why explainability research in AI is required for developing user-friendly applicationstroubleshoot usability of an AI application prototype
IN THIS COURSE
1.AI Apprentice33sUP NEXT
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