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AI+ Context Engineering Practitioner (AP-3309)

Reliable AI depends on more than a good prompt. AI+ Context Engineering Practitioner shows you how to manage instructions, memory, tools, and information so AI systems respond more consistently.

You’ll also learn how to build retrieval workflows, control context, connect multiple agents, and prepare systems for business use.

Overview

Overview

Context engineering helps AI systems use the right information at the right time. This course explores how to manage memory, instructions, retrieved information, tools, and system state across AI applications.

You’ll learn how to build context pipelines, connect external information, improve accuracy, and reduce unnecessary processing. The course also covers security, scaling, no-code workflows, industry applications, and systems where several AI agents work together. A capstone project brings these skills together in a working multi-agent solution.

Prerequisites
  • Basic programming knowledge in Python, Java, or a similar language

  • Foundational understanding of AI and machine learning

  • Ability to work with datasets and basic data preparation

  • Familiarity with Internet of Things applications

  • Basic knowledge of cloud-based AI services

  • Strong analytical and problem-solving skills

  • Experience with Git or similar version control tools

Target Audience
  • AI engineers and developers building reliable AI applications

  • Software engineers working with AI-powered systems

  • Data professionals working with retrieval and AI data flows

  • Cloud engineers supporting AI applications and services

  • Solution architects designing AI systems for business use

  • Automation builders using tools such as n8n, Make, or Zapier

  • Technical leaders and consultants planning AI implementations

Exam Blueprint
  • Foundations of Context Engineering – 7%
  • Context Management Patterns & Techniques – 15%
  • The Context Pipeline, RAG, and Grounding Architecture – 15%
  • Optimization, Scaling, and Enterprise Readiness – 15%
  • Context Flow Design for Business Users: Architecting Reliable AI via No-Code Platforms – 12%
  • Real-World Industry Context Applications – 12%
  • Multi-Agent Orchestration & the Future – 12%
  • Capstone Module – 12%
FAQs

1. What is context engineering used for?
Context engineering helps AI systems receive the right instructions, information, memory, and tools for each task. This can improve accuracy and consistency.

2. Can the course be taken online?
Yes, the course is available through live virtual instructor-led training or a self-paced online option.

3. Is in-person training available?
Yes, classroom sessions are available through AI CERTs Authorized Training Partners.

Course Outline

Module 1: Foundations of Context Engineering
  1. Introduction to Context Engineering
  2. Moving from Prompt-Based Systems to Context-Aware Systems
  3. Core Building Blocks of Context Engineering
  4. How LLMs Use Memory and Context
  5. Benefits of Context Engineering
  6. Improving System Performance, Decision-Making, and Scalability
  7. Real-World Context Engineering Applications
  8. Production Environment Case Studies

 

Module 2: Context Management Patterns & Techniques
  1. Context Management Framework
  2. WRITE Context: Defining Identity and State
  3. SELECT Context: Precision Retrieval
  4. COMPRESS Context: Improving Context Efficiency
  5. Isolating Context
  6. Advanced Retrieval and Compression Techniques
  7. Context Management with LlamaIndex and LangChain
  8. Tool Selection for Context Management
  9. Moving from Branching Reasoning to Unified Context Flow
  10. Real-World Case Studies

 

Module 3: The Context Pipeline, RAG, and Grounding Architecture
  1. End-to-End Context Pipelines
  2. Retrieval-Augmented Generation (RAG) Architecture
  3. Practical Applications of Vector Databases
  4. Context Quality Challenges
  5. Grounding Failures
  6. Grounding Failure Mitigation Strategies
  7. Orchestration Frameworks for State and Flow
  8. Case Study: Anthropic’s Multi-Agent Researcher

 

Module 4: Optimization, Scaling, and Enterprise Readiness
  1. Cost Optimization in Context Pipelines
  2. Performance Optimization
  3. Context Scaling
  4. Model Context Protocol (MCP)
  5. Security in Enterprise AI Environments
  6. Compliance Considerations
  7. Context Consistency
  8. Conflict Resolution
  9. Multi-Modal Context
  10. Working with Unstructured Enterprise Data
  11. Real-World Enterprise Case Studies

 

Module 5: Context Flow Design for Business Users: Architecting Reliable AI via No-Code Platforms
  1. Context Flow Architecture for Business Users
  2. Mapping Business Processes to AI-Ready Context Flows
  3. No-Code Tools for Flow Control
  4. Implementing W-S-C-I Visually
  5. Designing Dynamic Customer Onboarding Assistants
  6. Context for Automated Workflows
  7. Building Reliable AI Workflows Without Heavy Coding
  8. Enterprise Context Flow Case Studies

 

Module 6: Real-World Industry Context Applications
  1. Context Engineering in Regulated Industries
  2. Healthcare Applications
  3. Finance Applications
  4. Legal Applications
  5. Education Applications
  6. Context-Driven Clinical Decision-Making
  7. Real-Time Financial Analysis
  8. Personalized Education
  9. Industry-Specific Risk Mitigation
  10. Context Engineering for Advanced AI Agents
  11. Real-World Industry Case Studies

 

Module 7: Multi-Agent Orchestration & the Future
  1. Multi-Agent System Architecture
  2. Context Communication Between Agents
  3. Context Flow Design
  4. Controlling Agent Behaviour Through System Context
  5. Guardrails for Multi-Agent Systems
  6. Scaling Multi-Agent Systems
  7. Automation Across Coordinated Agents
  8. Ethical Implications of Multi-Agent Systems
  9. Enterprise Multi-Agent Deployments
  10. Career Pathways in Context Architecture
  11. Career Pathways in AI Governance

 

Module 8: Capstone Module
  1. Multi-Agent Context-Aware System
  2. Multi-Agent Query Router
  3. Financial Calculations
  4. Policy RAG
  5. Building the Solution Using n8n
  6. Applying Context Flow Design
  7. Applying Multi-Agent Orchestration
  8. Building an Adaptive, Context-Aware AI System
Note : A representative from Datacipher will contact you with further details
Payment Methods

At DataCipher, we offer a variety of payment options for our Fortinet courses. Here are the methods available:

Purchase Order (PO) – If your organization prefers using a purchase order, begin the registration process by clicking the Register button. At the conclusion of the registration form, choose the option “My company will pay for it, please send an invoice with the payment details.” Our training team will then provide an official quote and any necessary additional information that your accounts department might need to issue the PO.

Bank Transfer – DataCipher maintains bank accounts in both the US and Europe, accommodating all standard bank transfer methods such as IBAN/BIC, Swift, ACH, or wire transfer. To make a payment via bank transfer, simply use the Register button to sign up for your selected course.

Credit Card Payments – We accept payments from all major credit cards, including Mastercard, VISA, American Express, Discover & Diners, and Cartes Bancaires. Payments can be made directly through the registration link or by requesting an invoice that includes a web link for online payment. All transactions are secure, and DataCipher does not store any credit card information.

These options are designed to make the registration process as smooth and flexible as possible for all participants.

Status

Guaranteed to Run – DataCipher is committed to running this class unless unforeseen events such as an instructor’s accident or illness occur.

Guaranteed on Next Booking – The course will proceed once an additional student registers.

Scheduled Class – We have scheduled this course and rarely cancel due to low enrollment. We offer a “Cancel No More Than Once” guarantee, ensuring that if a class is canceled due to insufficient enrollment, the next session will run regardless of the number of attendees.

Sold Out – If the class is fully booked, please use our contact form to join the waiting list or to inquire about additional sessions. We’re here to accommodate your training needs and keep you informed of new opportunities.

Half and Full-Day Training

At DataCipher, we offer our training courses in both traditional full-day and convenient half-day formats. Our half-day classes are specifically designed for IT professionals who cannot be away from their workplaces for consecutive full days. This flexible schedule allows participants to dedicate a few hours to learning and then return to their regular work responsibilities.

The curriculum for both the full-day and half-day formats is identical. The primary difference is that the half-day classes spread the coursework over a more extended period, providing a balanced approach to professional education. DataCipher has been successfully running these half-day training sessions for several years, receiving consistently positive feedback from our customers. They appreciate the flexibility and report that the extended timeframe facilitates a deeper understanding of the material, as it gives them more time to absorb and reflect on the information learned.

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