AI Learning & Development Training
Course Authors
AI Learning & Development Training Hands-on (Online, Onsite, and Classroom Live)
| Commitment | 1 Day, 7-8 hours a day. |
| Language | English |
| User Ratings | Average User Rating 4.8 See what learners said |
| Price | REQUEST |
| Delivery Options | Instructor-Led Onsite, Online, and Classroom Live |
COURSE OVERVIEW
The AI Learning & Development Training Certification comprehensively examines AI’s transformative capabilities within educational settings. Through a series of modules encompassing Machine Learning, Natural Language Processing, Ethical considerations, and Emerging Trends, participants can profoundly comprehend AI fundamentals and their practical implications. Participants will learn to design adaptive learning systems and navigate ethical dilemmas, fostering responsible implementation of AI solutions. The course culminates in a capstone project, enabling learners to tackle real-world educational challenges with their acquired knowledge. The course’s conclusion empowers participants to spearhead innovation and elevate learning outcomes using AI-driven strategies.
WHAT'S INCLUDED?
- 1 day of AI Learning & Development Training with an expert instructor
- AI Learning & Development Training Electronic Course Guide
- Certificate of Completion
- 100% Satisfaction Guarantee
RESOURCES
- AI Learning & Development Training – https://www.wiley.com/
- AI Learning & Development Training – https://www.packtpub.com/
- AI Learning & Development – https://store.logicaloperations.com/
- AI Learning & Development – https://us.artechhouse.com/
- AI Project Manager Training – https://www.amazon.com/
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ADDITIONAL INFORMATION
COURSE OBJECTIVES
Upon completion of this AI Learning & Development Training course, participants can:
- AI Content Development
- Learners will gain the ability to use AI for creating and curating educational content, leveraging AI-driven tools to tailor and optimize learning materials.
- Implementation of Adaptive Learning Systems
- Students will develop skills in designing and implementing adaptive learning systems that use AI to customize the educational experience based on individual learner’s needs and performance.
- Application of NLP in Educational Settings
- Learners who will go through this course will get skills in natural language processing to analyze and understand educational content, enhancing interactions between learners and digital educational platforms.
- Educational Data Mining and Analytics
- Learners will explore techniques in data mining and analytics to understand patterns and trends in student learning behaviors, performance, and engagement. This knowledge enables the development of more effective educational strategies and personalized learning experiences, helping educators and institutions to enhance outcomes and optimize educational processes.
CUSTOMIZE IT
- We can adapt this AI Learning & Development Training course to your group’s background and work requirements at little to no added cost.
- If you are familiar with some aspects of this AI Learning & Development course, we can omit or shorten their discussion.
- We can adjust the emphasis placed on the various topics or build the AI Learning & Development course around the mix of technologies of interest to you (including technologies other than those included in this outline).
- If your background is nontechnical, we can exclude the more technical topics, include the topics that may be of special interest to you (e.g., as a manager or policymaker), and present the AI Learning & Development Training course in a manner understandable to lay audiences.
AUDIENCE/TARGET GROUP
The target audience for this AI Learning & Development Training course:
- All
CLASS PREREQUISITES
The knowledge and skills that a learner must have before attending this AI Learning & Development Training course are:
- A basic understanding of artificial intelligence concepts and terminologies
- Proficiency in using digital tools and platforms for educational purposes
- Familiarity with learning theories and instructional design principles
- Some experience in educational or training roles, such as teaching, content development, or instructional design
- A willingness to engage with technical subjects and apply AI technologies in the context of learning and development
COURSE SYLLABUS
Module 1: Introduction to Artificial Intelligence (AI) in Education
- Overview of Artificial Intelligence
- AI’s Role in Education and Training
- Impact of AI on Educational Content Creation
- AI in Assessment and Feedback
- Ethical Considerations and Challenges
Module 2: Machine Learning Fundamentals
- Introduction to Machine Learning
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Machine Learning in Practice
Module 3: Natural Language Processing (NLP) for Educational Content
- Fundamentals of NLP in Education
- Content Analysis and Enhancement
- Personalized Learning and Adaptive Content
- Assessment and Feedback Automation
Module 4: AI-Driven Content Creation and Curation
- AI in Generating Educational Content
- Adaptive Learning Materials Creation
- Dynamic Assessment Item Generation
- Curating Educational Resources
- Challenges and Ethical Considerations in AI-Driven Content
Module 5: Adaptive Learning Systems
- Foundations of Adaptive Learning
- Designing Adaptive Learning Systems
- Implementation Strategies
- Assessment and Evaluation in Adaptive Systems
- Ethical and Privacy Considerations
Module 6: Ethics and Bias in AI for L&D
- Understanding AI Ethics in L&D
- Privacy Concerns in AI-Driven L&D
- Bias and Fairness in AI Assessments
- Ethical AI Use and Learner Engagement
- Future Challenges and Opportunities
Module 7: Emerging Technologies and Future Trends
- Augmented Reality (AR) in Education
- Virtual Reality (VR) in Learning Environments
- AI-Driven Personalized Learning
- Blockchain in Education
- Emerging AI Technologies in Educational Research and Development
Module 8: Implementation and Best Practices
- Strategic Planning for AI Integration
- Selecting the Right AI Tools
- Implementing AI Solutions
- Monitoring and Evaluating Impact
- Ethical Use and Data Governance
