Trending
Beginner
4h
Updated this week
The AI Engineer Interview Crash Course
Build the technical depth and reasoning fluency that AI engineering interviews actually demand: from transformer internals and alignment techniques to production-grade RAG, agents, and safety systems.
If you are short on time and need to prepare efficiently, this crash course is a condensed version of the comprehensive Ace The AI Engineer Interviews course, covering the most critical topics in approximately 15 to 20 hours of focused study.
AI engineering interviews test whether you can reason from first principles, connect concepts across the stack, and explain trade-offs under pressure. This course is built around that reality. It takes you from transformer internals and the alignment pipeline through to production-grade RAG, agentic systems, and safety engineering, covering everything from how attention works to how a deployed LLM system stays reliable at scale.
Every topic was selected using a single filter: Does it appear in real interviews at companies working with large language models? If not, it was excluded.
If you are short on time and need to prepare efficiently, this crash course is a condensed version of the comprehensive Ace The ...Show More
WHAT YOU'LL LEARN
A deep understanding of transformer internals: attention mechanisms, positional encodings, architectural variants like GQA and Flash Attention, and how design choices affect inference cost
Fluency in the full training and alignment pipeline: backpropagation, fine-tuning strategies, RLHF, DPO, and modern techniques like GRPO and Constitutional AI
Practical knowledge of model compression and efficiency: LoRA, QLoRA, quantization, distillation, and understanding when to use each approach
The ability to design and evaluate RAG systems, including retrieval strategies, chunking trade-offs, re-ranking, and common production failure modes
An understanding of agentic architectures: ReAct, tool use, MCP, A2A, and the failure modes that matter when agents operate autonomously
Familiarity with evaluation frameworks, safety risks, and production engineering practices that keep LLM systems reliable at scale
A deep understanding of transformer internals: attention mechanisms, positional encodings, architectural variants like GQA and Flash Attention, and how design choices affect inference cost
Show more
Learning Roadmap
1.
How AI Models Work
How AI Models Work
Master AI and LLM fundamentals for AI engineer interviews, covering ML foundations, tokenization, embeddings, attention, and transformer architectures.
2.
LLM Training, Fine-Tuning, and Optimization
LLM Training, Fine-Tuning, and Optimization
Learn AI model training, fine-tuning, inference, compression, scaling, and evaluation techniques crucial for AI engineer interviews.
3.
AI System Design
AI System Design
5 Lessons
5 Lessons
Explore applied AI system design for interviews, including prompt engineering, RAG systems, agentic AI, and model interpretability
Certificate of Completion
Showcase your accomplishment by sharing your certificate of completion.
Complete more lessons to unlock your certificate
Developed by MAANG Engineers
Trusted by 2.9 million developers working at companies
"These are high-quality courses. Trust me the price is worth it for the content quality. Educative came at the right time in my career. I'm understanding topics better than with any book or online video tutorial I've done. Truly made for developers. Thanks"
Anthony Walker
@_webarchitect_
"Just finished my first full #ML course: Machine learning for Software Engineers from Educative, Inc. ... Highly recommend!"
Evan Dunbar
ML Engineer
"You guys are the gold standard of crash-courses... Narrow enough that it doesn't need years of study or a full blown book to get the gist, but broad enough that an afternoon of Googling doesn't cut it."
Software Developer
Carlos Matias La Borde
"I spend my days and nights on Educative. It is indispensable. It is such a unique and reader-friendly site"
Souvik Kundu
Front-end Developer
"Your courses are simply awesome, the depth they go into and the breadth of coverage is so good that I don't have to refer to 10 different websites looking for interview topics and content."
Vinay Krishnaiah
Software Developer
Hands-on Learning Powered by AI
See how Educative uses AI to make your learning more immersive than ever before.
AI Prompt
Code Feedback
Explain with AI
AI Code Mentor
Free Resources
