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Course Outline
Introduction to Agentic AI and Bootcamp Overview
- Understanding agentic AI and the structure of the bootcamp
- Review of essential tools, frameworks, and dependencies for government use
- Best practices for setting up projects and fostering collaboration in a government environment
Project 1: Intelligent Assistant with Prompt-Oriented Reasoning
- Designing a task-based conversational agent for government applications
- Utilizing structured prompts to enhance reasoning and decision-making capabilities
- Building and testing the agent in Jupyter Notebook for government-specific tasks
Project 2: Document Analysis and Summarization Agent
- Extracting and summarizing data from PDFs and text files for government reports
- Using LangChain to ingest and retrieve information from documents for government use
- Generating executive summaries and reports from structured and unstructured content for government officials
Project 3: Tool-Using Agent for Workflow Automation
- Integrating external APIs to automate repetitive tasks in government workflows
- Managing multi-step processes through agentic loops for improved efficiency in government operations
- Building a small automation assistant to support real-world business processes in the public sector
Project 4: Data Analysis and Insight Generation Agent
- Connecting agents to data sources such as CSV, SQL, or APIs for government datasets
- Performing exploratory data analysis with Python and AI assistance to inform government decision-making
- Creating visual insights and performance dashboards to enhance transparency and accountability in government operations
Project 5: Multi-Agent Collaboration and Orchestration
- Coordinating multiple agents for task delegation in complex government projects
- Designing a controller–worker architecture to optimize resource allocation in government agencies
- Deploying and testing a prototype multi-agent system to support government initiatives
Wrap-Up and Next Steps
- Project presentations and peer feedback sessions for government participants
- Discussion of optimization and scaling strategies for government applications
- Resources for continued learning and experimentation in agentic AI for government use
Requirements
- Intermediate proficiency in Python programming for government applications
- Basic understanding of artificial intelligence or machine learning principles
- Familiarity with application programming interfaces (APIs) and data processing workflows
Audience
- Engineers and developers within government agencies aiming to build applied AI projects
- Technical teams in the public sector seeking rapid prototyping skills in agentic AI
- Practitioners involved in AI integration and pilot program development for government initiatives
21 Hours
Testimonials (3)
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
Ion Mironescu - Facultatea S.A.I.A.P.M.
Course - Autonomous Decision-Making with Agentic AI
practical exercises
