Agentic AI for Absolute Beginners — A 52 Week Course

Course Overview

Agentic AI for Absolute Beginners — A 52-Week Course is a comprehensive, beginner-friendly program designed to teach the fundamentals of AI agents, including their design, testing, and practical applications. The course covers core concepts such as goals, tasks, actions, decisions, feedback loops, prompt engineering, tool use, memory, workflows, Python programming, APIs, automation, evaluation, safety, and deployment over a structured 52-week journey.

Students will learn to differentiate AI agents from chatbots and traditional workflows, develop reliable AI workflows, use tools and memory effectively, and build practical AI assistants. The course culminates in mini-projects and a portfolio-ready capstone project demonstrating applied knowledge.

Key Takeaways

• Understand what agentic AI is and how it differs from chatbots and fixed workflows.
• Learn core AI agent components: goals, tasks, actions, decisions, observations, and feedback loops.
• Develop skills in prompt engineering for clear instructions, context, constraints, and structured outputs.
• Use AI tools such as web search, calculators, APIs, and external applications safely and effectively.
• Apply concepts of short-term context, long-term memory, and state management in AI agents.
• Design planning, reflection, correction, retry, and error-recovery processes for workflows.
• Implement human-in-the-loop systems with approval, review, escalation, and override controls.
• Gain beginner-level Python programming skills relevant to AI agent development.
• Understand APIs, requests, responses, JSON, model settings, token limits, and cost considerations.
• Build various AI assistants including research, writing, data, support, email, scheduling, meeting, and knowledge assistants.
• Compare agentic systems with deterministic workflows to select appropriate approaches.
• Learn retrieval-augmented generation, document grounding, chunking, citations, and hallucination reduction.
• Evaluate and debug agent outputs using success criteria, test cases, scoring, and regression testing.
• Apply guardrails, privacy controls, restricted actions, safe fallbacks, and responsible AI principles.
• Design multi-agent systems with specialized roles and handoff logic.
• Use logging, tracing, observability, deployment, access control, versioning, and maintenance best practices.
• Build beginner-friendly automations using Python and no-code tools.
• Complete mini-projects and a final capstone with documentation, testing, and demonstration.

Prerequisites

• No prior experience with agentic AI, artificial intelligence, programming, or automation is required.
• Basic computer, file-management, web-browsing, and communication skills are sufficient.
• A computer with reliable internet access is recommended.
• Access to a generative AI assistant is helpful for practical exercises.
• Python is introduced gradually; no previous coding knowledge is necessary.
• A code editor or beginner-friendly notebook environment is useful for Python sections.
• No advanced mathematics, machine learning, or data science knowledge is required.
• Willingness to experiment with prompts, test workflows, review outputs, and troubleshoot is important.
• Consistency and curiosity are valued over technical experience.
• Students should be prepared to complete weekly reviews, mini-projects, and a final capstone.

Target Learners

• Complete beginners seeking a structured introduction to agentic AI.
• Professionals interested in how AI agents can support everyday work.
• Students and recent graduates exploring modern AI and automation careers.
• Career changers exploring roles involving generative AI, intelligent workflows, or AI operations.
• Entrepreneurs and small-business owners looking for practical automation opportunities.
• Business analysts, consultants, and project managers evaluating agentic AI use cases.
• Content creators, educators, and researchers interested in AI-powered assistants.
• Customer support, operations, marketing, sales, and administrative professionals.
• Developers new to AI agents wanting foundational knowledge.
• No-code users progressing from simple automation to adaptive AI workflows.
• Team leaders responsible for reviewing, approving, or governing AI-assisted processes.
• Anyone wanting to build practical AI agents without advanced math or complex software engineering.