Advanced Agentic AI Engineering Training Course

Advanced Agentic AI Engineering Training Course

Introduction

Advanced Agentic AI Engineering Training Course is designed to equip professionals with advanced skills in building, deploying, and managing autonomous AI agents, multi-agent systems, and intelligent automation platforms. As organizations accelerate digital transformation through Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI orchestration, and autonomous decision-making systems, this course provides deep engineering expertise required to design next-generation AI applications. Participants will explore agentic architectures, AI reasoning frameworks, tool-using agents, workflow automation, AI copilots, memory-enabled agents, and enterprise-grade AI solutions using modern AI engineering practices.

This advanced program focuses on practical implementation of Agentic AI ecosystems that can perceive environments, reason, plan tasks, use external tools, collaborate with other agents, and execute complex workflows with minimal human intervention. Through real-world case studies, hands-on labs, and industry-driven projects, learners will master AI agent development, LLM engineering, prompt optimization, autonomous systems design, AI safety, evaluation frameworks, and scalable deployment strategies to build intelligent solutions for enterprises across industries.

Course Duration

10 Days

Course Objectives

By the end of this course, participants will be able to:

1. Master Advanced Agentic AI Engineering principles and autonomous AI system architectures. 
2. Design and develop LLM-powered intelligent agents for enterprise applications. 
3. Build multi-agent collaboration systems using modern AI frameworks. 
4. Implement AI reasoning, planning, and decision-making capabilities. 
5. Develop advanced Retrieval-Augmented Generation (RAG) agent systems. 
6. Engineer tool-using AI agents capable of interacting with APIs, databases, and applications. 
7. Apply prompt engineering, context engineering, and AI workflow optimization techniques. 
8. Create scalable AI automation pipelines using agent orchestration frameworks. 
9. Implement AI memory systems and long-term knowledge management. 
10. Deploy production-ready enterprise AI agent platforms. 
11. Apply AI governance, security, ethics, and responsible AI practices. 
12. Evaluate and optimize agent performance, reliability, and accuracy. 
13. Develop innovative AI-powered business solutions using autonomous technologies. 

Target Audience

1. AI Engineers and Machine Learning Engineers 
2. Software Developers building AI applications 
3. Data Scientists and Data Analysts 
4. Cloud Engineers and DevOps Professionals 
5. Automation and Digital Transformation Specialists 
6. Enterprise Architects and Technology Leaders 
7. Product Managers developing AI-powered products 
8. Researchers and Innovation Professionals 

Course Modules

Module 1: Foundations of Advanced Agentic AI Engineering

• Evolution from Generative AI to Agentic AI systems 
• Core concepts of autonomous AI agents 
• Agent architectures and intelligent workflows 
• Components of modern AI agent ecosystems 
• Case Study: Enterprise AI assistant transformation using autonomous agents 

Module 2: Large Language Models for Agent Development

• Understanding advanced LLM architectures 
• Model selection and optimization strategies 
• LLM reasoning and context management 
• Fine-tuning and adaptation techniques 
• Case Study: Building an enterprise knowledge agent using LLMs 

Module 3: Agentic AI System Architecture Design

• Designing scalable agent-based architectures 
• Agent perception, reasoning, and execution layers 
• Planning and decision-making frameworks 
• Human-in-the-loop AI systems 
• Case Study: Autonomous customer support agent architecture 

Module 4: AI Agent Frameworks and Development Platforms

• Introduction to modern agent frameworks 
• Agent orchestration patterns 
• Building reusable agent components 
• Managing agent workflows and dependencies 
• Case Study: Multi-functional business automation agent 

Module 5: Multi-Agent Systems Engineering

• Designing collaborative AI agent networks 
• Agent communication protocols 
• Role-based agent architectures 
• Coordination and negotiation strategies 
• Case Study: Multi-agent financial analysis platform 

Module 6: Advanced Prompt and Context Engineering

• Designing intelligent agent prompts 
• Context window optimization 
• Dynamic prompt generation 
• Instruction hierarchy management 
• Case Study: AI research assistant optimization 

Module 7: Retrieval-Augmented Generation (RAG) Agents

• Advanced RAG architectures 
• Vector databases and semantic search 
• Knowledge retrieval optimization 
• Enterprise document intelligence 
• Case Study: Corporate AI knowledge management system 

Module 8: AI Agents with External Tools and APIs

• Building tool-enabled AI agents 
• API integration techniques 
• Database-connected agents 
• Function calling and automation 
• Case Study: AI business operations assistant 

Module 9: AI Memory and Knowledge Management Systems

• Short-term and long-term AI memory 
• Agent learning mechanisms 
• Knowledge storage architectures 
• Personalization techniques 
• Case Study: Personalized AI productivity assistant 

Module 10: Autonomous AI Workflow Automation

• Designing automated business workflows 
• AI-powered process optimization 
• Intelligent task execution systems 
• Workflow monitoring and control 
• Case Study: Automated enterprise workflow platform 

Module 11: Agent Evaluation, Testing, and Optimization

• Measuring AI agent performance 
• Agent reliability testing 
• Benchmarking AI workflows 
• Error detection and improvement 
• Case Study: Improving accuracy of enterprise AI agents 

Module 12: AI Security, Safety, and Governance

• Securing autonomous AI systems 
• Preventing AI misuse and failures 
• Data privacy and compliance 
• Responsible AI engineering principles 
• Case Study: Secure banking AI agent deployment 

Module 13: Cloud Deployment of Agentic AI Systems

• Deploying AI agents on cloud platforms 
• Containerization and scalability 
• Monitoring AI applications 
• Production AI infrastructure 
• Case Study: Cloud-based enterprise AI assistant 

Module 14: Advanced AI Agent Applications

• AI agents in healthcare, finance, and education 
• Industry-specific intelligent automation 
• AI copilots and digital employees 
• Autonomous decision-support systems 
• Case Study: AI-powered enterprise innovation platform 

Module 15: Capstone Project - Building Enterprise Agentic AI Solutions

• Designing complete agent-based applications 
• Integrating LLMs, tools, and knowledge systems 
• Implementing autonomous workflows 
• Deploying production-ready AI solutions 
• Case Study: End-to-end enterprise autonomous AI platform 

Training Methodology

• Interactive lectures and presentations.
• Group discussions and brainstorming sessions.
• Hands-on exercises using real-world datasets.
• Role-playing and scenario-based simulations.
• Analysis of case studies to bridge theory and practice.
• Peer-to-peer learning and networking.
• Expert-led Q&A sessions.
• Continuous feedback and personalized guidance.

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104 

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

 We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.