Overview
The AI+ Context Engineering™ course teaches how to design and manage the context behind AI systems to ensure accurate and reliable results. It covers key concepts like context management, RAG, and workflow automation, helping you build scalable solutions and apply them in various business scenarios.
Strategic AI Insights
Understand AI technologies and their business impact to develop and execute effective AI strategies
Practical Application
Engage in workshops and case studies to gain practical, actionable AI knowledge.
Future-Proof Workforce
Prepare your team with the skills needed to thrive in an AI-driven workplace.
What you’ll learn
By the end of the AI+ Context Engineering course, you will learn how to design and manage context for AI systems, ensuring they produce accurate, relevant, and reliable outputs. You will gain practical skills in working with RAG architectures, managing data and memory, and building context-aware workflows, enabling you to develop scalable AI solutions for real-world applications.
- Foundations of Context Engineering
-What context engineering is and how it differs from prompt engineering.
– Core components: data, memory, tools, and instructions.
– How AI systems use context to improve accuracy and relevance. - Context Management Techniques
– Key strategies: Write, Select, Compress, and Isolate.
– Managing and optimizing context for better performance.
– Techniques for retrieving and structuring relevant data. - Optimization & Scaling
– Improving performance and reducing costs.
– Managing large-scale context and system efficiency.
– Ensuring consistency, accuracy, and reliability in outputs. - Workflow Design & No-Code Tools
– Designing context-aware workflows for business use.
– Using no-code platforms to automate AI processes.
– Structuring context flows for real-world applications. - Industry Applications
– Applying context engineering in healthcare, finance, and other sectors.
– Managing risks, compliance, and data privacy.
– Building reliable AI solutions for high-stakes environments. - Multi-Agent Systems & Future Trends
– Working with multi-agent architectures.
– Managing context across multiple agents.
– Understanding future developments in AI systems.
Instructors
Angel Georgiev
Sales & Training Portfolio Product Manager
Angel Georgiev has over 20 years of experience in designing and delivering enterprise learning solutions in the context of digital transformation. His work focuses on enabling organizations to build capabilities through structured training programs aligned with business and technology needs.
Angel Georgiev
Angel Georgiev is a Sales & Training Portfolio Product Manager in ITCE with over 20 years of experience in designing and delivering enterprise learning solutions in the context of digital transformation. His work focuses on enabling organizations to build capabilities through structured training programs aligned with business and technology needs.
At ITCE, he leads the development and management of a comprehensive training portfolio covering Microsoft, AWS, ServiceNow, and AI certification programs. He works closely with enterprise clients to scope and structure tailored learning solutions, supports presales activities, and ensures alignment between training offerings, market demand, and technology trends.
In parallel, he delivers training and consultancy focused on ITIL, Agile practices, IT Service Management (ITSM), ServiceNow practitioner workshops, and Artificial Intelligence, combining practical implementation experience with structured learning approaches. His work includes designing training content, delivering practical sessions, and supporting organizations in adopting process frameworks and modern technology practices.
Certifications
- AI+ Ethics™
- AI+ Foundation™
- AI+ Certs Certified Trainer
- AI+ Executive™
- AI+ for Everyone™
- AI+ Prompt Engineer™
- ITIL® 4 Foundation
Calendar
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6 – 6 Nov 2026
New -
13 – 13 May 2027
Who should attend?
This course is ideal for AI professionals, developers, and data specialists looking to build more reliable and scalable AI systems, as well as business and technical leaders who want to design context-aware AI solutions for real-world applications. It is also valuable for anyone involved in AI implementation, automation, or digital transformation initiatives.
Prerequisites
- Business Awareness: Basic understanding of how businesses operate.
- Tech Comfort: Openness to learn about AI tools and concepts.
- Decision-Making Insight: Some knowledge of how choices are made in organizations.
- Openness to AI: Curiosity about the potential of artificial intelligence in businesses.
Your Certification Journey Awaits!
Get more information on how you can get certified through online proctored exam vouchers. Boost your career prospects now!
