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Course Outline

Introduction to Agentic AI and Course Structure

  • Overview of agentic AI concepts and the bootcamp's learning pathway.
  • Review of essential tools, frameworks, and dependencies.
  • Best practices for setting up projects and fostering effective collaboration.

Project 1: Intelligent Assistant with Prompt-Oriented Reasoning

  • Designing a conversational agent focused on specific tasks.
  • Leveraging structured prompts to enhance reasoning and decision-making capabilities.
  • Developing and testing the agent within a Jupyter Notebook environment.

Project 2: Document Analysis and Summarization Agent

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

Project 3: Tool-Using Agent for Workflow Automation

  • Integrating external APIs to automate repetitive operational tasks.
  • Managing complex, multi-step processes through agentic loops.
  • Building a compact automation assistant tailored for real business workflows.

Project 4: Data Analysis and Insight Generation Agent

  • Connecting agents to diverse data sources such as CSV files, SQL databases, or APIs.
  • Conducting exploratory data analysis with the assistance of Python and AI tools.
  • Creating visual insights and performance dashboards for better decision-making.

Project 5: Multi-Agent Collaboration and Orchestration

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

Conclusion and Future Pathways

  • Project presentations and constructive peer feedback.
  • Discussion on optimization and scaling strategies for production environments.
  • Recommended resources for continued learning and further experimentation.

Requirements

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

Target 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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