Course Outline
Overview of Agentic AI and Bootcamp Structure
- Foundational concepts of agentic artificial intelligence and program framework
- Assessment of requisite software tools, development frameworks, and system dependencies
- Established protocols for project initialization and inter-team collaboration
Project 1: Development of an Intelligent Assistant Using Prompt-Based Reasoning
- Architecting a conversational agent designed for specific operational tasks
- Leveraging structured prompts to enhance logical processing and decision-making capabilities
- Implementation and validation within the Jupyter Notebook environment
Project 2: Automated Document Analysis and Summarization Agent
- Extraction and synthesis of critical information from PDF documents and textual sources
- Utilization of LangChain for efficient data ingestion and retrieval mechanisms
- Generation of comprehensive executive summaries derived from structured and unstructured data inputs
Project 3: Workflow Automation via Tool-Integrated Agents
- Integration of external application programming interfaces (APIs) to streamline routine processes
- Execution of complex, multi-stage operations through iterative agent loops
- Development of a prototype automation assistant tailored for specific business workflows
Project 4: Data Analysis and Insight Generation Agent
- Connection to diverse data repositories, including CSV files, SQL databases, and API endpoints
- Execution of exploratory data analysis utilizing Python and artificial intelligence enhancements
- Creation of visual analytics and performance monitoring dashboards for actionable intelligence
Project 5: Multi-Agent Collaboration and Orchestration Framework
- Coordination of distinct agents to facilitate task delegation and resource allocation
- Design implementation of a controller-worker architectural model
- Deployment and rigorous testing of a functional multi-agent system prototype for government operations
Program Conclusion and Future Directions
- Submission of final projects and incorporation of peer evaluation feedback
- Strategic discussion regarding system optimization and scalability methodologies
- Provision of curated resources to support ongoing professional development and technical experimentation
Requirements
- Intermediate competency in Python development
- Foundational knowledge of artificial intelligence and machine learning concepts
- Working familiarity with application programming interfaces (APIs) and data processing procedures
Audience
- Engineers and developers focused on implementing applied AI solutions for government applications
- Technical personnel requiring capabilities in rapid prototyping for agentic AI systems
- Practitioners engaged in the integration of AI technologies and the development of pilot initiatives
Testimonials (3)
The trainer is patient and very helpful. He knows the topic well.
CLIFFORD TABARES - Universal Leaf Philippines, Inc.
Course - Agentic AI for Business Automation: Use Cases & Integration
Good mixvof knowledge and practice
Ion Mironescu - Facultatea S.A.I.A.P.M.
Course - Agentic AI for Enterprise Applications
The mix of theory and practice and of high level and low level perspectives