Generative AI and Agentic AI Training Course
Generative AI and Agentic AI represent two distinct yet complementary paradigms advancing the landscape of automation and intelligent systems, with the former prioritizing content synthesis and the latter emphasizing goal-oriented, autonomous behavior.
This instructor-led, live training program, available in online or on-site formats, is designed for intermediate-level AI specialists and technical professionals seeking to construct, assess, and integrate generative and agentic AI capabilities into operational applications for government contexts.
Upon completion of this training, participants will be equipped to:
- Comprehend the architectural underpinnings and functional capabilities of generative AI systems.
- Analyze the emergence of autonomous AI agents and their capacity to extend large language model functionality.
- Apply prompt engineering techniques and tool integrations for practical deployment scenarios.
- Evaluate models, tools, and methodologies to ensure responsible and secure implementation.
Instructional Format
- Interactive lectures facilitated by structured discussion.
- Hands-on application of generative and agentic AI tools within simulated real-world environments.
- Guided exercises emphasizing content generation and autonomous workflow management.
Customization Options
- Interested parties may contact the administration to arrange a tailored training curriculum specific to their institutional needs.
Course Outline
Introduction to Generative Artificial Intelligence and Agentic Systems
- Definitions of Generative AI and Agentic AI.
- Distinctions and synergistic capabilities between the two modalities.
- Applications and emerging trends across public and private sectors.
Generative AI Architectural Frameworks and Toolsets
- Transformer-based models, including GPT, LLaMA, and Claude.
- Methodologies: Fine-tuning versus in-context learning.
- Key platforms: ChatGPT, Hugging Face Transformers, and Google AI Studio.
Prompt Engineering for Governance and Structural Control
- Prompting strategies for composition, code generation, and summarization.
- Techniques: Few-shot, zero-shot, and chain-of-thought approaches.
- Leveraging prompt libraries and evaluation testing instruments.
Conceptual Foundations of Agentic AI
- Definition and evolutionary trajectory of agentic systems.
- Core architectures: Planning mechanisms, memory retention, tool utilization, and self-reflective loops.
- Leading frameworks: AutoGPT, BabyAGI, CrewAI, and LangGraph.
Design and Deployment of Autonomous Agents
- Objective formulation and task decomposition strategies.
- Integration of external tools and APIs for search, memory, and code execution.
- Coordination among multiple agents and human-in-the-loop oversight mechanisms.
Operational Use Cases and Implementation Scenarios
- Differentiating content generation from complex task orchestration.
- Applications in enterprise productivity, customer service, and data extraction.
- Ensuring responsible, secure, and compliant implementation for government operations.
Summary and Forward-Looking Recommendations
Requirements
- A foundational understanding of artificial intelligence and machine learning principles.
- Practical experience with API interactions or scripting languages, such as Python.
- Working knowledge of prompt engineering or the utilization of large language models.
Target Audience
- AI developers and systems engineers.
- Innovation and Research and Development (R&D) personnel.
- Technical product managers evaluating agentic AI systems for government applications.
Runs with a minimum of 4 + people. For 1-to-1 or private group training, request a quote.
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Testimonials (1)
the tips and recommended prompts that we can take away from this training
Lee Mei Lin - ST Engineering IHQ Pte Ltd
Course - InVideo AI: Creating Engaging Short-Form Videos
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