Course Overview
This comprehensive 10-day course by IRES equips professionals with the skills to leverage Artificial Intelligence (AI) for effective knowledge management. Participants will master tools like Microsoft Azure and Google Cloud AI to enhance knowledge capture, organization, and discovery. Through case studies and practical exercises, you’ll drive innovation and competitiveness in public, private, and nonprofit sectors.
Course Duration
10 Days
Target Audience
- Knowledge and content managers
- IT professionals and data scientists
- Business analysts and digital librarians
- Executives and decision-makers
Organizational Impact
- Enhanced innovation through AI-driven knowledge insights
- Improved decision-making with optimized knowledge access
- Increased efficiency via automated knowledge processes
- Strengthened competitiveness with advanced AI tools
Personal Impact
- Mastery of AI applications in knowledge management
- Enhanced career prospects in AI and knowledge roles
- Increased confidence in deploying AI solutions
- Improved analytical and strategic skills
Course Level:
Course Objectives
- Understand AI’s role in knowledge management
- Apply AI for knowledge capture and generation
- Enhance knowledge retrieval with AI-driven algorithms
- Foster collaboration using AI-powered tools
- Implement ethical AI strategies for knowledge management
Course Outline
Module 1: Introduction to AI and Knowledge Management
- Understanding AI and knowledge management basics
- Exploring AI applications in knowledge management
- Assessing benefits of AI integration
- Using Microsoft OneNote for AI planning
- Case Study: Assess AI needs for knowledge management
Module 2: Knowledge Creation with AI
- Using intelligent agents for knowledge generation
- Applying NLP for content creation
- Automating knowledge capture processes
- Using Google Cloud NLP for content generation
- Case Study: Create AI-generated knowledge content
Module 3: Knowledge Organization and Classification
- Implementing AI-driven information retrieval
- Automating tagging and categorization
- Building semantic analysis and knowledge graphs
- Using Neo4j for knowledge graphs
- Case Study: Develop an AI-based classification system
Module 4: Knowledge Discovery and Recommendation
- Building recommender systems for knowledge
- Applying clustering and topic modeling
- Using text mining for unstructured data
- Using Microsoft Azure for recommendations
- Case Study: Design a recommender system for e-commerce
Module 5: Knowledge Capture and Collaboration
- Deploying chatbots for knowledge capture
- Using AI-powered collaborative platforms
- Applying social network analysis for sharing
- Using Microsoft Teams for collaboration
- Case Study: Implement a chatbot for knowledge capture
Module 6: Knowledge Storage and Retrieval
- Optimizing AI-powered search engines
- Designing knowledge base architectures
- Implementing federated search capabilities
- Using Elasticsearch for retrieval
- Case Study: Build an AI-powered search system
Module 7: AI for Knowledge Maintenance
- Automating content updating and validation
- Evolving knowledge bases with AI
- Using predictive analytics for maintenance
- Using Power BI for analytics
- Case Study: Develop an AI maintenance strategy
Module 8: AI-Driven Decision Support
- Integrating AI into decision support systems
- Enhancing decision-making with AI insights
- Applying AI for risk assessment
- Using Tableau for decision visualization
- Case Study: Create an AI-driven decision support tool
Module 9: Ethical AI in Knowledge Management
- Addressing privacy and bias in AI systems
- Ensuring compliance with data protection laws
- Developing ethical AI policies
- Using compliance tools for monitoring
- Case Study: Design an ethical AI policy
Module 10: AI Implementation Strategies
- Planning AI integration for knowledge management
- Training employees for AI adoption
- Measuring AI impact with KPIs
- Using Microsoft SharePoint for AI deployment
- Case Study: Implement an AI-based KMS
Related Courses
Course Administration Details:
Methodology
These instructor-led training sessions are delivered using a blended learning approach and include presentations, guided practical exercises, web-based tutorials, and group work. Our facilitators are seasoned industry experts with years of experience as professionals and trainers in these fields. All facilitation and course materials are offered in English. Participants should be reasonably proficient in the language.
Accreditation
Upon successful completion of this training, participants will be issued an Indepth Research Institute (IRES) certificate certified by the National Industrial Training Authority (NITA).
Training Venue
The training will be held at IRES Training Centre. The course fee covers the course tuition, training materials, two break refreshments, and lunch. All participants will additionally cater to their travel expenses, visa application, insurance, and other personal expenses.
Accommodation and Airport Transfer
Accommodation and Airport Transfer are arranged upon request. For reservations contact the Training Officer.
- Email: [email protected]
- Phone: +254715 077 817
Tailor-Made
This training can also be customized to suit the needs of your institution upon request. You can have it delivered in our IRES Training Centre or at a convenient location. For further inquiries, please contact us on:
- Email: [email protected]
- Phone: +254715 077 817
Payment
Payment should be transferred to the IRES account through a bank on or before the start of the course. Send proof of payment to [email protected]
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