Candidates for this certification have a foundational knowledge the procedures used to develop an artificial intelligence (AI) solution, as well as an understanding of the issues surrounding the governance, transparency, security, and ethics of AI. Successful candidates will be able to analyze and classify a problem. They should be able to demonstrate knowledge of data collection, data processing, and feature engineering strategies. Candidates should be able to choose an appropriate algorithm for training a model, and understand the metrics used to evaluate model performance. They should understand the AI development lifecycle and how a production pipeline is used to allow for continuous improvement. Candidates at least 150 hours of instruction and/or exploration of artificial intelligence methodology and solutions
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| Expiry period | 6 Months | ||
| Made in | English | ||
| Last updated at | Sat Oct 2025 | ||
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| Total lectures | 30 | ||
| Total quizzes | 0 | ||
| Total duration | Hours | ||
| Total enrolment |
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| Number of reviews | 0 | ||
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| Short description | Candidates for this certification have a foundational knowledge the procedures used to develop an artificial intelligence (AI) solution, as well as an understanding of the issues surrounding the governance, transparency, security, and ethics of AI. Successful candidates will be able to analyze and classify a problem. They should be able to demonstrate knowledge of data collection, data processing, and feature engineering strategies. Candidates should be able to choose an appropriate algorithm for training a model, and understand the metrics used to evaluate model performance. They should understand the AI development lifecycle and how a production pipeline is used to allow for continuous improvement. Candidates at least 150 hours of instruction and/or exploration of artificial intelligence methodology and solutions | ||
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