AI Engineering for Production Systems Training focuses on the engineering principles and practices required to design, develop, and reliably operate AI-powered applications in production environments.

The course explores modern AI product architectures, the capabilities and limitations of large language models (LLMs), AI application design, context engineering, Retrieval-Augmented Generation (RAG) systems, and AI agent development. Participants gain an understanding of how different AI architectures can be structured for specific use cases and integrated into production systems.

The program also addresses reliable AI application development, evaluation techniques, performance optimization, and enterprise AI engineering practices. By combining fundamental concepts with practical exercises, the training helps participants develop the skills needed to design scalable, maintainable, and production-ready AI solutions for real-world business requirements.

For corporate groups, we can organize this training as an on-site private group.

Prerequisites

Basic knowledge of software development, API usage, and Python programming is recommended. Familiarity with fundamental artificial intelligence concepts and large language models will help participants gain greater value from the training.

Who Should Attend

Software Developers
Data Scientists
AI Researchers
IT Professionals
Professionals Working in Enterprise Digital Transformation Teams

What You Will Learn

By the end of this training, you will be able to:

Apply modern AI architecture and system design principles.
Manage prompt, memory, and retrieval strategies using context engineering techniques.
Build RAG-based AI applications that incorporate external knowledge sources.
Design AI agent systems using workflows and multi-agent architectures.
Implement guardrails, structured outputs, and error recovery mechanisms.
Evaluate AI applications using different testing and assessment methods.
Manage deployment, CI/CD, observability, and scaling processes.
Optimize token consumption, latency, and operational costs.
Address security, privacy, governance, and compliance requirements in enterprise AI solutions.

Training Outline

1. AI Engineering Foundations

Modern AI Product Stack
LLM Capabilities & Limitations
AI System Design Principles
Prompt vs Workflow vs Agent
Introduction to Context Engineering

2. AI Application Architecture

Core architectural concepts and system design approaches for building AI-powered applications.

3. Context Engineering

Managing application context through prompt design, memory management, and retrieval strategies.

4. RAG Systems

Retrieval-Augmented Generation (RAG) architectures and the development of AI applications that incorporate external data sources.

5. Agent Engineering

Developing AI agents and designing workflow-based systems, supervisor patterns, and multi-agent architectures.

6. Reliable AI Systems

Guardrails
Structured Output
Error Recovery Strategies

7. AI Evaluation Methods

Offline Evaluations
Golden Sets
Human Evaluation

8. Production AI Operations

Observability and Monitoring
CI/CD Pipelines
Deployment Strategies
Scaling AI Applications

9. AI Performance and Cost Optimization

Token Usage Optimization
Latency Management
Balancing Cost and Performance in AI Applications

10. Enterprise AI Engineering

Security and Data Privacy
AI Governance
Compliance and Enterprise Requirements

Why Choose Us

Leading UK-based global training provider since 1995.

Experience AI Engineering for Production Systems in United States of America through Bilginç IT Academy's live and interactive virtual classroom environment. Join a Public course as an individual delegate or arrange a dedicated Private / In-house online training program exclusively for your organization.

Delivery Method: Online Instructor-Led
Participation Model: Public / Private (In-house)
Live and Interactive Training: Connect with your instructor in real time and actively participate through discussions, Q&A sessions, practical exercises, and group activities.
Flexible Participation: Join the training from your home, office, or any location with a suitable internet connection.
Expert Trainer Network: Learn from experienced trainers with strong industry backgrounds and practical field expertise.
Over 30 Years of Training Expertise: Benefit from Bilginç IT Academy's professional training experience since 1995.
Worldwide Access: Join our live virtual classrooms from United States of America or anywhere else in the world, or arrange a dedicated online training program for your organization.

Experience AI Engineering for Production Systems through face-to-face Classroom Based training in United States of America. Training can be delivered as a Public course open to individual delegates or as a dedicated Private / In-house class for your organization.

Delivery Method: Classroom Based
Participation Model: Public / Private (In-house)
Face-to-Face Learning: Interact directly with your instructor and fellow delegates in an engaging classroom environment.
Experienced Trainers: Learn from specialists with extensive industry experience and practical real-world knowledge.
Professional Training Environment: Attend training in comfortable, well-equipped classrooms designed to support effective learning.
Practical Learning: Depending on the course, reinforce your knowledge through hands-on exercises, scenarios, case studies, and instructor-led activities.

Arrange AI Engineering for Production Systems in United States of America as a dedicated Onsite training program for your organization. Bilginç IT Academy trainers can deliver the training at your office or another location of your choice, with the program planned around your team's requirements and business objectives.

Delivery Method: Onsite
Participation Model: Private (In-house)
Training at Your Preferred Location: Organize the training at your company's office or another location selected by your organization.
Tailored Course Content: Adapt the training program to your projects, team structure, existing skill levels, and specific business requirements.
Team-Focused Learning: Develop your team around a shared knowledge base while strengthening internal collaboration and knowledge transfer.
Flexible Scheduling: Plan the training dates, location, and program according to your organization's operational requirements.
Worldwide Onsite Delivery: Arrange the training in United States of America or at another preferred location worldwide. Bilginç IT Academy trainers can travel to your selected location to deliver the dedicated training program.

AI Engineering for Production Systems Training in United States of America