Description
AI Engineering Fundamentals is a solid foundation for designing, developing, and deploying modern AI systems, published by Udemy Online Academy. Designed for aspiring engineers, developers, and technology professionals, this course introduces the essential concepts and practical skills needed to build reliable AI-based applications. Students will learn about machine learning workflows, data processing, neural networks, large language models (LLMs), AI application architecture, rapid engineering, model evaluation, and deployment practices. The course focuses on bridging the gap between AI theory and real-world engineering by teaching them how to build scalable, efficient, and production-ready AI solutions.
In this foundational, project-based, focused learning course, you’ll go from “I know Python” to “I can design, build, evaluate, and deploy real LLM applications.” Every concept is taught before you use it. Every lab connects to the bigger picture. Each project ends with something you can put on GitHub, your resume, and your portfolio. This course is recommended for software engineers and developers who want to add production-ready LLM and AI engineering skills to their toolkit, data analysts, scientists, and machine learning professionals who are transitioning from classic machine learning to modern LLMs, transforms, and generative AI, and beginners and career changers looking for a rigorous, scientific introduction to how large language models work under the hood.
What you will learn in AI Engineering Fundamentals:
- Build a small transformer from scratch and understand self-attention, multi-head attention, situational encoding, and GPT-style self-correlated generation.
- Master tokenization (BPE, WordPiece, SentencePiece) and control LLM outputs using temperature, top-k, top-p sampling, streaming, and context windows.
- Apply rapid engineering techniques: zero-shot, few-shot, chain-of-thought, ReAct, prompt chaining, and extract structured output in JSON.
- Protect LLM applications from rapid injection and jailbreak by building a secure chatbot with input validation and defense system notifications.
- Set up a professional AI development environment with API key hygiene, algebraic controls, event logging, and run open source models locally using Ollama.
- And…
Course specifications
Publisher: Udemy
Instructors: TechBricks Lab
Language: English
Level: Introductory to Advanced
Number of Lessons: 222
Duration: 23 hours and 22 minutes
Course topics on 2026/6
AI Engineering Fundamentals Prerequisites
Basic Python knowledge. No prior AI, ML, or deep learning experience is required to get started.
A computer with at least 8 GB of RAM and a stable internet connection.
Curiosity and a willingness to think like a scientist: form hypotheses, run tests, and iterate based on evidence; we’ll teach the rest.
Familiarity with using a terminal or command line is helpful, but every command is walked through step by step.
Pictures
AI Engineering Fundamentals introduction video
Installation guide
After Extract, watch with your favorite Player.
Subtitle: None
Quality: 1080p
Downloadly link
Rapidgator link
File password (s): www.downloadly.ir
Size
12.9 GB
