Coursera Flash Sale
40% Off Coursera Plus for 3 Months!
Grab it
- This module explores fundamental concepts in artificial intelligence (AI) and machine learning.
By the end of this module, you'll be able to:
- Distinguish between supervised, unsupervised, and reinforcement learning, and identify the type of machine learning most suitable for certain scenarios.
- Assess the effectiveness of neural networks in handling unstructured and unlabeled data compared to other machine learning techniques.
- Evaluate statements on the role of continuous refinement in machine learning models.
- This module explores the dynamic integration of artificial intelligence (AI) in education.
By the end of this module, you'll be able to:
- Recognize how AI is being applied in an educational context.
- Compare the use of AI-powered software in enhancing learning engagement and determine its impact on the learning process.
- This module explores various subsets within artificial intelligence (AI) such as natural language processing (NLP), computer vision, and recommendation systems and discuss the integration of AI-powered tools into a learning environment.
By the end of this module, you'll be able to:
- Understand the main advantages of applying AI-powered tools into a learning environment.
- Analyze the differences between different AI subsets and their applications in education.
- This module contains sample activities that demonstrate how to integrate AI-powered tools into your learning environment.
By the end of this module, you'll be able to:
- Evaluate the effectiveness of Microsoft's AI-powered tools in enhancing teaching and learning outcomes.
- Critique the quality of interactive learning materials created using Microsoft PowerPoint Speaker Coach.
- Compare and contrast different AI-powered features in Microsoft 365 products.
