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The Complete AI Engineer Bootcamp 2026
New
301 students
The Complete AI Engineer Bootcamp 2026
Learn Python, model APIs, prompting, RAG, and tool calling by building and testing your first AI assistant.
Created byArjun Vaid, School of AI, MEET SHAH
Last updated 10/2026
English
English [Auto],
What you'll learn
- Build Python AI applications that call model APIs, manage conversation history, and handle common errors.
- Write clear prompts and validate structured AI outputs for reliable information extraction.
- Build a document-based AI assistant using retrieval, embeddings, and inspectable source references.
- Add a validated calculator tool, evaluate answer quality, and create a local web interface for your AI assistant.
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Course content
9 sections • 40 lectures • 3h 20m total length
Requirements
- No prior AI or Python experience required. We cover the fundamentals step by step. Basic computer skills, including downloading files and installing software. A computer running Windows, macOS, or Linux, with permission to install Python and a code editor. Internet access to download tools and use optional live AI features. Optional: An API account and key for live model exercises. API usage may incur separate charges; free offline demonstrations are included.
Description
This course contains the use of artificial intelligence.
The Complete AI Engineer Bootcamp 2026 helps you take your first steps into AI engineering through clear explanations, practical examples, and guided projects. No previous AI or Python experience is required.
You’ll begin with the Python essentials needed to build AI applications, including variables, functions, file handling, and JSON. Then you’ll explore how large language models generate responses, what tokens and context windows mean, and why fluent answers still need verification.
As you progress, you’ll learn to write effective prompts, extract information into structured formats, and connect Python applications to model APIs. You’ll also practice managing conversation history and handling common errors.
The course introduces retrieval-augmented generation, or RAG, through a document-based assistant. You’ll learn how to split documents into chunks, retrieve relevant passages, understand embeddings, and display source references that users can inspect.
Next, you’ll add a calculator tool with input validation and controlled execution. You’ll test your assistant using supported questions, missing-information cases, and invalid inputs before connecting it to a simple local web interface.
Your final project brings these skills together in a study assistant that answers questions from supplied notes, shows supporting passages, and performs explicit calculations.
The course includes seven guided labs, downloadable Python projects, practice starters, completed reference code, quizzes, prompt templates, and a final-project checklist. Free offline demonstrations let you practice without an API key. Optional live API exercises require your own account and key, and usage may incur separate charges.
With approximately 4 hours and 40 minutes of planned lessons and guided demonstrations, this bootcamp gives beginners a focused introduction to building and evaluating AI applications. Independent practice and quizzes take additional time.
Who this course is for:
- Complete beginners who want to understand AI engineering and build their first AI application. Students and career changers seeking a practical introduction to Python, model APIs, and document-based AI assistants. Developers new to AI who want hands-on experience with prompts, retrieval, tool calling, and evaluation. Professionals and hobbyists who learn by building and want to create a simple AI assistant with a local web interface.