advanced search
Do you have any questions?
+420 731 175 867 (Mo-Fr: 9A.M.-5P.M.)
EN
0 Basket

AI+ Learning & Development Practitioner™

Course code: NPAP420

Formerly known as AI+ Learning & Development™

AI-Enhanced Learning: Where Knowledge Meets Innovation

  • Education Innovation: Empowers educators and trainers to integrate AI effectively into teaching and learning environments
  • Deep Insights: Covers machine learning, NLP, data analytics, and adaptive learning strategies in depth
  • Capstone Delivery: Design and develop AI-powered learning solutions tailored to meet diverse learner needs
  • Ethical Education: Explores ethics, data-driven instruction, and the latest emerging trends in AI-enhanced education
75 EUR

91 EUR including VAT

Selection of dates
onas
Do you have a question?
+420 731 175 867 edu@edutrainings.cz

Professional
and certified lecturers

Internationally
recognized certifications

Wide range of technical
and soft skills courses

View soft skills courses

Great customer
service

Making courses
exactly to measure your needs

Course dates

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 8 hours

Language: en

Price without VAT: 285 EUR

Register

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 8 hours

Language: en

Price without VAT: 75 EUR

Register

Starting
date		 Place
Type Course
duration		 Language Price without VAT
G Upon request Self-paced 8 hours en 285 EUR Register
G Upon request Self-paced 8 hours en 75 EUR Register
G Guaranteed course

Didn't find a suitable date?

Write to us about listing an alternative tailor-made date.

Contact

Course description

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.

Course structure

Course Overview

Module 1: Introduction to Artificial Intelligence (AI) in Education

  • 1.1 Overview of Artificial Intelligence
  • 1.2 AI’s Role in Education and Training
  • 1.3 Impact of AI on Educational Content Creation
  • 1.4 AI in Assessment and Feedback
  • 1.5 Ethical Considerations and Challenges

Module 2: Machine Learning Fundamentals

  • 2.1 Introduction to Machine Learning
  • 2.2 Supervised Learning
  • 2.3 Unsupervised Learning
  • 2.4 Reinforcement Learning
  • 2.5 Machine Learning in Practice

Module 3: Natural Language Processing (NLP) for Educational Content

  • 3.1 Fundamentals of NLP in Education
  • 3.2 Content Analysis and Enhancement
  • 3.3 Personalized Learning and Adaptive Content
  • 3.4 Assessment and Feedback Automation

Module 4: AI-Driven Content Creation and Curation

  • 4.1 AI in Generating Educational Content
  • 4.2 Adaptive Learning Materials Creation
  • 4.3 Dynamic Assessment Item Generation
  • 4.4 Curating Educational Resources
  • 4.5 Challenges and Ethical Considerations in AI-Driven Content

Module 5: Adaptive Learning Systems

  • 5.1 Foundations of Adaptive Learning
  • 5.2 Designing Adaptive Learning Systems
  • 5.3 Implementation Strategies
  • 5.4 Assessment and Evaluation in Adaptive Systems
  • 5.5 Ethical and Privacy Considerations

Module 6: Ethics and Bias in AI for L&D

  • 6.1 Understanding AI Ethics in L&D
  • 6.2 Privacy Concerns in AI-Driven L&D
  • 6.3 Bias and Fairness in AI Assessments
  • 6.4 Ethical AI Use and Learner Engagement
  • 6.5 Future Challenges and Opportunities

Module 7: Emerging Technologies and Future Trends

  • 7.1 Augmented Reality (AR) in Education
  • 7.2 Virtual Reality (VR) in Learning Environments
  • 7.3 AI-Driven Personalized Learning
  • 7.4 Blockchain in Education
  • 7.5 Emerging AI Technologies in Educational Research and Development

Module 8: Implementation and Best Practices

  • 8.1 Strategic Planning for AI Integration
  • 8.2 Selecting the Right AI Tools
  • 8.3 Implementing AI Solutions
  • 8.4 Monitoring and Evaluating Impact
  • 8.5 Ethical Use and Data Governance

Optional Module: AI Agents for Learning & Development

  • 1. Understanding AI Agents
  • 2. Case Studies
  • 3. Hands-On Practice with AI Agents

Prerequisites

  • A foundational understanding of artificial intelligence concepts and related terminology
  • Confidence in using digital tools and platforms within educational or training contexts
  • Familiarity with learning theories and core principles of instructional design
  • Some background in educational or training roles, such as teaching, content creation, or curriculum development
  • A readiness to engage with technical material and apply AI technologies within learning and development settings

Do you need advice or a tailor-made course?

onas

product support

+420 731 175 867

edu@edutrainings.cz

ComGate payment gateway MasterCard Logo Visa logo