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Course Outline

Introduction to Agentic AI and Bootcamp Structure

  • Overview of agentic AI and the bootcamp framework
  • Review of essential tools, frameworks, and dependencies
  • Best practices for project setup and team collaboration

Project 1: Intelligent Assistant with Prompt-Oriented Reasoning

  • Designing a task-focused conversational agent
  • Applying structured prompts for reasoning and decision-making
  • Developing and testing in Jupyter Notebook

Project 2: Document Analysis and Summarization Agent

  • Extracting and summarising data from PDFs and text files
  • Utilising LangChain for document ingestion and retrieval
  • Producing 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)
  • Conducting 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

Conclusion and Next Steps

  • Project presentations and peer feedback
  • Discussion on optimisation and scaling strategies
  • Resources for continued learning and experimentation

Requirements

  • Intermediate level of Python programming skill
  • Fundamental knowledge of AI or machine learning concepts
  • Experience with APIs and data processing workflows

Intended Audience

  • Engineers and developers focused on building applied AI projects
  • Technical teams looking to develop rapid prototyping capabilities in agentic AI
  • Professionals involved in AI integration and pilot program development
 21 Hours

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