Introduction to artificial intelligence for trainers

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Module 1: 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.
Module 2: 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.
Module 3: 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.