Agentic AI for Absolute Beginners — A 52 Week Course

This course contains the use of artificial intelligence.

Agentic AI for Absolute Beginners — A 52-Week Course is a complete, beginner-friendly learning journey designed to help you understand, design, test, and demonstrate practical AI agents. No previous programming, automation, machine learning, or artificial intelligence experience is required.

You will begin by learning what agentic AI is and how agents differ from chatbots and traditional workflows. You will explore goals, tasks, actions, decisions, observations, feedback loops, planning, iteration, and human oversight. These concepts will help you understand how agents move beyond answering questions and begin completing structured tasks.

The course introduces prompt engineering for AI agents, including clear instructions, context, constraints, examples, output formatting, tables, checklists, and JSON. You will learn how to break complex goals into manageable steps and create reliable workflows that are easier to test and improve.

You will then explore AI tool use, including web search, calculators, APIs, files, and external actions. You will learn how agents gather information, verify sources, call tools, inspect results, and decide what to do next. Memory, context management, planning, reflection, correction, and retry logic are explained using approachable examples.

A gradual introduction to Python for AI agents covers variables, data types, functions, loops, conditionals, lists, dictionaries, scripts, APIs, requests, responses, and model integration. You will use these foundations to understand how simple assistants and agent workflows are created.

Practical modules introduce research helpers, writing assistants, data helpers, support agents, email assistants, scheduling assistants, meeting assistants, and internal knowledge assistants. You will also compare AI agents vs automation workflows so you can select the right design for each problem.

The course covers retrieval-augmented generation, document grounding, chunking, contextual prompts, citations, and hallucination reduction. You will learn how agents can work with files and trusted knowledge rather than relying only on a model’s existing knowledge.

Reliability and safety are central throughout the program. You will study agent evaluation, debugging, guardrails, privacy, restricted actions, human approvals, responsible AI, logging, tracing, observability, cost management, deployment, and maintenance.

You will also explore introductory multi-agent systems, including planner, researcher, writer, reviewer, executor, and coordinator roles. You will learn when specialized agents add value and when a simpler workflow is more reliable.

During the final eight weeks, you will complete mini-projects and build a portfolio-ready capstone. You will define the problem, choose tools, design the workflow, add guardrails, test reliability, improve the user experience, document the system, and present a final demonstration.

By the end of this 52-week agentic AI course, you will have a practical foundation in AI agents, prompting, tools, memory, workflows, Python, APIs, RAG, automation, evaluation, safety, and deployment.