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Course Outline

Introduction to Agentic AI and Bootcamp Overview

  • Understanding agentic AI and the bootcamp structure.
  • Review of tools, frameworks, and dependencies.
  • Best practices for project setup and collaboration.

Project 1: Intelligent Assistant with Prompt-Oriented Reasoning

  • Designing a task-based conversational agent.
  • Using structured prompts for reasoning and decision-making.
  • Building and testing in Jupyter Notebook.

Project 2: Document Analysis and Summarization Agent

  • Extracting and summarizing data from PDFs and text files.
  • Using LangChain for document ingestion and retrieval.
  • Generating executive reports from structured and unstructured content.

Project 3: Tool-Using Agent for Workflow Automation

  • Integrating external APIs and automating repetitive tasks.
  • Managing multi-step processes through agentic loops.
  • Building a small automation assistant for real business workflows.

Project 4: Data Analysis and Insight Generation Agent

  • Connecting agents to data sources (CSV, SQL, or API).
  • Performing exploratory data analysis with Python and AI assistance.
  • Creating visual insights and performance dashboards.

Project 5: Multi-Agent Collaboration and Orchestration

  • Coordinating multiple agents for task delegation.
  • Designing a controller–worker architecture.
  • Deploying and testing a prototype multi-agent system.

Wrap-Up and Next Steps

  • Project presentations and peer feedback.
  • Discussion of optimization and scaling strategies.
  • Resources for continued learning and experimentation.

Requirements

  • Intermediate proficiency in Python programming.
  • Basic understanding of AI or machine learning principles.
  • Familiarity with APIs and data processing workflows.

Audience

  • Engineers and developers aiming to build applied AI projects.
  • Technical teams seeking rapid prototyping skills in agentic AI.
  • Practitioners involved in AI integration and pilot program development.
 21 Hours

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