Azure AI Fundamentals: Artificial Intelligence & Machine Learning
Azure
| Beginner
- 18 videos | 1h 43m 31s
- Includes Assessment
- Earns a Badge
Artificial Intelligence and machine learning in particular are solving a significant number of business and social problems and giving computers a new way to handle and process vast amounts of data. In this course, you'll learn about AI and machine learning concepts regarding regression, classification, and clustering algorithms. You'll explore how to manage datasets and work with labeled versus unlabeled data. You'll learn how supervised and unsupervised machine learning can be used, as well as how to build and use AIs safely, transparently, and fairly. 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
Describe artificial intelligence and how it can be used to solve business problems
Describe machine learning and how it can be used for anomaly detection, computer vision, and natural language processing
Describe datasets and how to manipulate data for those datasets
Differentiate between labeled and unlabeled data and describe why some ai models require labeled data
Describe how features are selected and used from datasets in ai algorithms
Describe regression algorithms and how they are used to make predictions
Describe classification algorithms and how they are used to classify objects or relations
Describe clustering algorithms and how they can be used to determine groupings in data -
Describe how supervised machine learning models use labeled data, are simpler to build, and have more accurate results
Describe how unsupervised machine learning models use unlabeled data, which makes them more complex but more flexible than supervised machine learning
Describe how to responsibly use ai by making sure it is reliable and safe
Describe how transparency should be used with ai algorithms in a responsible way
Describe how privacy and security must be factored into responsibly creating and using ai solutions
Describe how the use of inclusiveness in ai algorithms can benefit everyone
Describe how fairness in ai algorithms results in responsible ai
Describe how governance and organizational policies provide accountability for ai responsibility
Summarize the key concepts covered in this course
IN THIS COURSE
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1m 21s
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5m 42sIn this video, you will learn how to describe Artificial Intelligence and how it can be used to solve business problems. FREE ACCESS
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3. Machine Learning6m 57sDuring this video, you will learn how to describe machine learning and how it can be used for anomaly detection, computer vision, and natural language processing. FREE ACCESS
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4. Datasets and Data Manipulation4m 59sIn this video, you will learn how to describe datasets and how to manipulate data for those datasets. FREE ACCESS
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5. Labeled vs. Unlabeled Data6m 42sDiscover how to differentiate between labeled and unlabeled data and describe why some AI models require labeled data. FREE ACCESS
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6. Features in Data5m 37sIn this video, you will discover how features are selected and used from datasets in AI algorithms. FREE ACCESS
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7. Machine Learning Using Regression6m 9sAfter completing this video, you will be able to describe regression algorithms and how to use them to make predictions. FREE ACCESS
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8. Machine Learning Using Classification7m 28sIn this video, you will learn how to describe classification algorithms and how they are used to classify objects or relations. FREE ACCESS
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9. Machine Learning Using Clustering6m 52sUpon completion of this video, you will be able to describe clustering algorithms and how they can be used to determine groupings in data. FREE ACCESS
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10. Supervised Machine Learning6m 32sDuring this video, you will learn how to describe how supervised machine learning models use labeled data, are simpler to build, and have more accurate results. FREE ACCESS
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11. Unsupervised Machine Learning5m 44sHow do unsupervised machine learning models use unlabeled data? FREE ACCESS
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12. Reliability and Safety in AI Algorithms and Use5m 45sLearn how to describe how to use AI responsibly by making sure it is reliable and safe. FREE ACCESS
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13. Transparency in AI Algorithms and Use6m 16sIn this video, you will learn how to describe how transparency should be used with AI algorithms in a responsible way. FREE ACCESS
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14. Privacy and Security in Responsible AI6m 14sDuring this video, you will learn how to describe how privacy and security must be factored into responsibly creating and using AI solutions. FREE ACCESS
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15. Inclusiveness in AI Algorithms and Use6mIn this video, discover how the use of inclusiveness in AI algorithms can benefit everyone. FREE ACCESS
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16. Fairness in AI Algorithms and Use7m 28sDiscover how to describe how fairness in AI algorithms results in responsible AI. FREE ACCESS
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17. Accountability in AI Algorithms and Use6m 44sIn this video, you will discover how governance and organizational policies provide accountability for AI responsibility. FREE ACCESS
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18. Course Summary1mIn 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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