Azure AI Fundamentals: Azure Machine Learning Fundamentals
Azure 2024
| Beginner
- 12 videos | 1h 6m 40s
- Includes Assessment
- Earns a Badge
Artificial intelligence (AI) and machine learning (ML) seem to be everywhere we look, and with each passing day, there are new breakthroughs in AI/ML technology. In this course, you will explore key features and uses of AI and ML, computer vision in Azure, and natural language processing (NLP) in Azure. Then you will discover the purpose of knowledge mining in Azure, investigate document intelligence in Azure, and examine generative AI in Azure. Finally, you'll delve into ethical considerations for AI, challenges and risks associated with AI, and critical considerations for the design and implementation of responsible AI. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
WHAT YOU WILL LEARN
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Discover the key concepts covered in this course
Provide an overview of ai features and uses
Describe key ml features and uses
Describe the features and purposes of computer vision with ai
Outline the purpose of and key considerations for nlp in ml
Provide an overview of knowledge mining and its purpose in ml applications -
Outline the role of document intelligence, including how it is leveraged in ml applications
Describe generative ai and its uses
Provide an overview of ethical considerations for ai
Outline challenges and risks commonly associated with ai
Describe key considerations for designing and implementing responsible ai
Summarize the key concepts covered in this course
IN THIS COURSE
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1m 5sIn this video, we will discover the key concepts covered in this course. FREE ACCESS
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6m 59sAfter completing this video, you will be able to provide an overview of AI features and uses. FREE ACCESS
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3. Machine Learning (ML)7m 41sUpon completion of this video, you will be able to describe key ML features and uses. FREE ACCESS
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4. Computer Vision in Azure6m 9sAfter completing this video, you will be able to describe the features and purposes of computer vision with AI. FREE ACCESS
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5. Natural Language Processing (NLP) in Azure7m 20sUpon completion of this video, you will be able to outline the purpose of and key considerations for NLP in ML. FREE ACCESS
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6. Knowledge Mining in Azure5m 19sAfter completing this video, you will be able to provide an overview of knowledge mining and its purpose in ML applications. FREE ACCESS
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7. Document Intelligence in Azure5m 56sUpon completion of this video, you will be able to outline the role of document intelligence, including how it is leveraged in ML applications. FREE ACCESS
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8. Generative AI in Azure7m 7sAfter completing this video, you will be able to describe generative AI and its uses. FREE ACCESS
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9. Ethical Considerations for AI6m 42sUpon completion of this video, you will be able to provide an overview of ethical considerations for AI. FREE ACCESS
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10. Challenges and Risks of AI6m 10sAfter completing this video, you will be able to outline challenges and risks commonly associated with AI. FREE ACCESS
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11. Responsible AI5m 35sUpon completion of this video, you will be able to describe key considerations for designing and implementing responsible AI. FREE ACCESS
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12. Course Summary37sIn this video, we will summarize the key concepts covered in this course. FREE ACCESS
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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