AI Agents in Gaming: From NPCs to Strategic AI Training Course
AI agents have transformed the gaming landscape by enabling intelligent and responsive behaviors, ranging from non-playable characters (NPCs) to sophisticated strategic decision-making systems. This course delves into the development of AI agents in gaming, covering essential topics such as decision trees, pathfinding algorithms, and reinforcement learning techniques.
This instructor-led live training (available online or onsite) is designed for intermediate-level game developers and AI enthusiasts aiming to effectively integrate AI agents into gaming applications.
Upon completion of this training, participants will be able to:
- Grasp the role of AI agents in contemporary gaming.
- Build decision-making systems using decision trees and finite state machines.
- Deploy pathfinding algorithms like A* for in-game navigation.
- Utilize reinforcement learning techniques to craft adaptive AI behaviors.
- Optimize AI performance for real-time gaming environments.
Course Format
- Interactive lectures and discussions.
- Ample exercises and practice sessions.
- Hands-on implementation within a live-lab environment.
Course Customization Options
- To request customized training for this course, please contact us to arrange it.
Course Outline
Introduction to AI in Gaming
- Overview of AI applications in games
- Types of AI agents: NPCs, strategic AI, and more
- Key concepts in game AI development
Decision-Making Systems
- Implementing decision trees for simple AI logic
- Finite state machines for complex behaviors
- Behavior trees and modular AI design
Pathfinding and Navigation
- Understanding pathfinding algorithms
- Implementing A* algorithm for in-game navigation
- Optimizing pathfinding for large maps
Reinforcement Learning in Games
- Introduction to reinforcement learning concepts
- Training AI agents using Q-learning and deep Q-networks
- Designing reward structures for adaptive behaviors
Optimizing AI Performance
- Techniques for real-time AI performance optimization
- Managing resources and prioritizing AI tasks
- Debugging and troubleshooting AI systems
Advanced AI Techniques
- Procedural content generation with AI
- Simulating player-like behaviors
- Integrating AI with multiplayer gaming
Future Trends in Game AI
- AI and machine learning in next-generation gaming
- Ethical considerations in game AI
- Exploring AI-driven storytelling and narrative design
Summary and Next Steps
Requirements
- Basic understanding of programming concepts
- Familiarity with game development tools or frameworks
- Basic knowledge of AI principles
Audience
- Game developers
- AI enthusiasts
Open Training Courses require 5+ participants.
AI Agents in Gaming: From NPCs to Strategic AI Training Course - Booking
AI Agents in Gaming: From NPCs to Strategic AI Training Course - Enquiry
AI Agents in Gaming: From NPCs to Strategic AI - Consultancy Enquiry
Testimonials (1)
I like how the course is built to the needs of what we are looking to create for work.
Alexius Burris - Weatherford
Course - From 3ds Max to Unreal: Mastering Real-Time Visualization
Upcoming Courses
Related Courses
From 3ds Max to Unreal: Mastering Real-Time Visualization
21 HoursThis instructor-led, live training in Malaysia (online or onsite) is aimed at intermediate-level to advanced-level 3D artists, game developers, and visualization professionals who wish to leverage their skills in Autodesk 3ds Max and learn how to create immersive real-time experiences in Unreal Engine.
By the end of this training, participants will be able to:
- Understand the key differences between 3ds Max and Unreal Engine workflows.
- Import 3D models, animations, and assets from 3ds Max into Unreal Engine.
- Create and customize materials, textures, and shaders in Unreal Engine.
- Set up dynamic lighting and global illumination for real-time rendering.
- Implement interactivity and gameplay mechanics using Blueprint visual scripting.
- Optimize assets and scenes for real-time performance and efficiency.
Advanced LangGraph: Optimization, Debugging, and Monitoring Complex Graphs
35 HoursLangGraph serves as a framework for developing stateful, multi-agent LLM applications through composable graphs that maintain persistent state and allow precise control over execution flow.
This instructor-led live training, available both online and onsite, is tailored for advanced-level AI platform engineers, AI DevOps specialists, and ML architects aiming to optimize, debug, monitor, and manage production-grade LangGraph systems.
Upon completing this training, participants will be capable of:
- Designing and optimizing complex LangGraph topologies to enhance speed, reduce costs, and improve scalability.
- Building reliability through retries, timeouts, idempotency, and checkpoint-based recovery mechanisms.
- Debugging and tracing graph executions, inspecting states, and systematically reproducing production issues.
- Instrumenting graphs with logs, metrics, and traces; deploying to production; and monitoring SLAs and costs.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practice sessions.
- Hands-on implementation within a live-lab environment.
Customization Options
- To request customized training for this course, please contact us to arrange.
Building Coding Agents with Devstral: From Agent Design to Tooling
14 HoursDevstral is an open-source framework engineered for the creation and execution of coding agents capable of interacting with codebases, developer tools, and APIs to boost engineering productivity.
This instructor-led, live training, available online or onsite, targets intermediate to advanced-level ML engineers, developer-tooling teams, and SREs keen on designing, implementing, and optimizing coding agents using Devstral.
Upon completion of this training, participants will be equipped to:
- Set up and configure Devstral for coding agent development.
- Design agentic workflows for codebase exploration and modification.
- Integrate coding agents with developer tools and APIs.
- Implement best practices for secure and efficient agent deployment.
Course Format
- Interactive lecture and discussion.
- Ample exercises and practice opportunities.
- Hands-on implementation within a live-lab environment.
Customization Options
- To request customized training for this course, please contact us to arrange.
Open-Source Model Ops: Self-Hosting, Fine-Tuning and Governance with Devstral & Mistral Models
14 HoursDevstral and Mistral are open-source AI technologies engineered for flexible deployment, fine-tuning capabilities, and scalable integration.
This instructor-led live training, available both online and onsite, targets intermediate to advanced machine learning engineers, platform teams, and research engineers who aim to self-host, fine-tune, and govern Mistral and Devstral models within production environments.
Upon completing this training, participants will be able to:
- Establish and configure self-hosted environments for Mistral and Devstral models.
- Apply fine-tuning techniques to enhance performance for specific domains.
- Implement versioning, monitoring, and lifecycle governance protocols.
- Ensure security, regulatory compliance, and responsible usage of open-source models.
Course Format
- Interactive lectures and discussions.
- Practical exercises focused on self-hosting and fine-tuning.
- Live laboratory sessions for implementing governance and monitoring pipelines.
Customization Options
- To arrange a customized version of this course, please get in touch with us.
Fiji: Image Processing for Biotechnology and Toxicology
14 HoursThis instructor-led, live training in Malaysia (online or onsite) is aimed at beginner-level to intermediate-level researchers and laboratory professionals who wish to process and analyze images related to histological tissues, blood cells, algae, and other biological samples.
By the end of this training, participants will be able to:
- Navigate the Fiji interface and utilize ImageJ’s core functions.
- Preprocess and enhance scientific images for better analysis.
- Analyze images quantitatively, including cell counting and area measurement.
- Automate repetitive tasks using macros and plugins.
- Customize workflows for specific image analysis needs in biological research.
LangGraph Applications in Finance
35 HoursLangGraph serves as a framework designed for constructing stateful, multi-actor LLM applications through composable graphs that maintain persistent state and offer precise control over execution.
This instructor-led live training, available either online or on-site, targets intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based financial solutions with robust governance, observability, and compliance measures.
Upon completion of this training, participants will be equipped to:
- Design finance-specific LangGraph workflows that align with regulatory and audit requirements.
- Integrate financial data standards and ontologies into graph state and tooling.
- Implement reliability, safety, and human-in-the-loop controls for critical processes.
- Deploy, monitor, and optimize LangGraph systems to meet performance, cost, and SLA objectives.
Format of the Course
- Interactive lecture and discussion.
- Extensive exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
LangGraph Foundations: Graph-Based LLM Prompting and Chaining
14 HoursLangGraph is a framework designed for constructing graph-structured LLM applications that support planning, branching, tool use, memory, and controllable execution.
This instructor-led, live training (available online or onsite) is tailored for beginner-level developers, prompt engineers, and data practitioners who wish to design and build reliable, multi-step LLM workflows using LangGraph.
By the end of this training, participants will be able to:
- Explain core LangGraph concepts (nodes, edges, state) and when to use them.
- Build prompt chains that branch, call tools, and maintain memory.
- Integrate retrieval and external APIs into graph workflows.
- Test, debug, and evaluate LangGraph apps for reliability and safety.
Format of the Course
- Interactive lecture and facilitated discussion.
- Guided labs and code walkthroughs in a sandbox environment.
- Scenario-based exercises on design, testing, and evaluation.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
LangGraph in Healthcare: Workflow Orchestration for Regulated Environments
35 HoursLangGraph empowers stateful, multi-actor workflows driven by Large Language Models (LLMs), offering precise control over execution paths and state persistence. In the healthcare sector, these capabilities are essential for ensuring compliance, interoperability, and the development of decision-support systems that seamlessly align with medical workflows.
This instructor-led live training session is available both online and onsite. It is designed for intermediate to advanced-level professionals aiming to design, implement, and manage LangGraph-based healthcare solutions while effectively addressing regulatory, ethical, and operational challenges.
Upon completion of this training, participants will be able to:
- Design healthcare-specific LangGraph workflows that prioritize compliance and auditability.
- Integrate LangGraph applications with medical ontologies and standards such as FHIR, SNOMED CT, and ICD.
- Apply best practices for reliability, traceability, and explainability in sensitive environments.
- Deploy, monitor, and validate LangGraph applications within healthcare production settings.
Format of the Course
- Interactive lecture and discussion.
- Hands-on exercises with real-world case studies.
- Implementation practice in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
LangGraph for Legal Applications
35 HoursLangGraph serves as a framework designed for constructing stateful, multi-actor LLM applications through composable graphs that maintain persistent state and offer precise execution control.
This instructor-led, live training (available online or onsite) targets intermediate to advanced professionals seeking to design, implement, and operate LangGraph-based legal solutions equipped with necessary compliance, traceability, and governance controls.
Upon completion of this training, participants will be able to:
- Design legal-specific LangGraph workflows that ensure auditability and compliance.
- Integrate legal ontologies and document standards into graph state and processing workflows.
- Implement guardrails, human-in-the-loop approvals, and traceable decision paths.
- Deploy, monitor, and maintain LangGraph services in production environments with robust observability and cost controls.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practice sessions.
- Hands-on implementation in a live laboratory environment.
Customization Options
- To request customized training for this course, please contact us to arrange it.
Building Dynamic Workflows with LangGraph and LLM Agents
14 HoursLangGraph is a framework designed for composing graph-structured LLM workflows that support branching, tool use, memory, and controllable execution.
This instructor-led, live training (available online or onsite) is aimed at intermediate-level engineers and product teams who wish to combine LangGraph’s graph logic with LLM agent loops to build dynamic, context-aware applications such as customer support agents, decision trees, and information retrieval systems.
By the end of this training, participants will be able to:
- Design graph-based workflows that coordinate LLM agents, tools, and memory.
- Implement conditional routing, retries, and fallbacks for robust execution.
- Integrate retrieval, APIs, and structured outputs into agent loops.
- Evaluate, monitor, and harden agent behavior for reliability and safety.
Format of the Course
- Interactive lecture and facilitated discussion.
- Guided labs and code walkthroughs in a sandbox environment.
- Scenario-based design exercises and peer reviews.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
LangGraph for Marketing Automation
14 HoursLangGraph is a graph-based orchestration framework designed to enable conditional, multi-step workflows involving LLMs and tools, making it ideal for automating and personalizing content pipelines.
This instructor-led live training, available online or onsite, targets intermediate-level marketers, content strategists, and automation developers seeking to implement dynamic, branching email campaigns and content generation pipelines using LangGraph.
Upon completion of this training, participants will be able to:
- Design graph-structured content and email workflows incorporating conditional logic.
- Integrate LLMs, APIs, and data sources to facilitate automated personalization.
- Manage state, memory, and context throughout multi-step campaigns.
- Evaluate, monitor, and optimize workflow performance and delivery outcomes.
Course Format
- Interactive lectures and group discussions.
- Hands-on labs focused on implementing email workflows and content pipelines.
- Scenario-based exercises covering personalization, segmentation, and branching logic.
Course Customization Options
- To request customized training for this course, please contact us to arrange a session.
Unreal Editor for Fortnite (UEFN)
7 HoursThis instructor-led live training held in Malaysia (online or on-site) targets beginner to intermediate-level game developers and UGC creators who wish to design, develop, and publish interactive and monetizable experiences for Fortnite players.
By the conclusion of this training, participants will be able to:
- Comprehend the basics of UEFN and its function in generating user-generated content within Fortnite.
- Navigate the UEFN interface, configure projects, and handle assets effectively.
- Develop and launch custom Fortnite experiences using worldbuilding and landscaping tools.
- Apply foundational programming concepts using the Verse scripting language.
- Collaborate on UEFN projects and prepare for monetization opportunities within Fortnite.
Industrial Virtual Environments with Unity, Blender, and Visual Studio
21 HoursUnity, Blender, and Visual Studio collectively offer a robust toolkit for developing and coding industrial virtual environments. Unity facilitates interactive simulation and visualization, Blender provides advanced 3D modelling capabilities, and Visual Studio acts as the programming backbone for integrating control systems and industrial logic.
This instructor-led live training (available online or on-site) is designed for beginner to intermediate-level professionals aiming to design, model, and program industrial environments for simulation, training, and integration purposes.
Upon completion of this training, participants will be able to:
- Design and model industrial equipment and scenarios using Blender.
- Import and optimise 3D models in Unity for visualization purposes.
- Program system logic and integration workflows in Visual Studio.
- Create interactive industrial virtual environments with control system connections.
Course Format
- Interactive lectures and discussions.
- Hands-on 3D modelling and environment development.
- Programming and integration exercises accompanied by live demonstrations.
Course Customization Options
- To request a customized training session for this course, please contact us to make arrangements.
Unreal Engine 4
21 HoursThis instructor-led, live training in Malaysia covers the fundamentals of game development with Unreal Engine 4 while giving participants the chance to create their own sample game.
Unreal Engine 5 Deep Dive
14 HoursThis instructor-led, live training in Malaysia (online or onsite) is aimed at game developers who wish to get a comprehensive understanding of UE5 and how to use it to create stunning real-time content.
By the end of this training, participants will be able to:
- Learn and understand the new features of the UE5 release.
- Utilize the real-time 3D creation tool capability of UE5 to create realistic visuals.
- Explore and build visual worlds and games.
- Learn and master game design principles.
- Create cutscene animations.