Course Outline
Fundamentals of Agentic AI and Bootcamp Introduction
- Exploring agentic AI concepts and the course structure
- Overview of required tools, frameworks, and dependencies
- Effective strategies for environment setup and collaborative workflows
Assignment 1: Intelligent Assistant with Prompt-Driven Reasoning
- Architecting a task-focused conversational agent
- Leveraging structured prompts to facilitate reasoning and decision processes
- Implementation and verification within a Jupyter Notebook environment
Assignment 2: Document Analysis and Summarization Agent
- Extracting key information and summarizing content from PDFs and text documents
- Utilizing LangChain for document processing and retrieval tasks
- Producing executive summaries from both structured and unstructured data sources
Assignment 3: Tool-Integrated Agent for Process Automation
- Incorporating external APIs to streamline repetitive operational tasks
- Orchestrating multi-step procedures via agentic feedback loops
- Constructing a focused automation assistant for specific business processes
Assignment 4: Data Analysis and Insight Generation Agent
- Linking agents to diverse data sources such as CSV, SQL, or APIs
- Conducting exploratory data analysis using Python with AI support
- Developing visual insights and performance monitoring dashboards
Assignment 5: Multi-Agent Coordination and Orchestration
- Managing multiple agents for distributed task execution
- Structuring a controller–worker model architecture
- Launching and evaluating a prototype multi-agent system
Conclusion and Future Directions
- Sharing project outcomes and receiving peer evaluations
- Exploring strategies for system optimization and scalability
- Accessing resources for ongoing learning and experimentation
Requirements
- Intermediate-level competency in Python programming
- Foundational knowledge of AI or machine learning concepts
- Experience with API interactions and data processing pipelines
Target Audience
- Software engineers and developers aiming to create practical AI solutions
- Technical groups looking to enhance their rapid prototyping capabilities in agentic AI
- Professionals engaged in AI integration and pilot initiative development
Testimonials (1)
First most valuable: Practical data analysis tasks using AI without copy-pasting - but through my own application of what I learned. Second most valuable: definition of terms that everyone uses (skills, agents, MCP, API). Now that I understand them, I feel much more confident in trying AI Third: your input on how AI works, what it can do, what it can't (I will remember your 80/20 rule forever). Fourth: Having everything you taught us in written and accessible form.
