Assess your practical AI engineering skills at the Middle level. This test covers LLM integration, prompt and context engineering, structured
outputs, embeddings, vector search, RAG, AI agents, evaluation, observability, safety, and production reliability. It is designed for
developers who build and maintain real-world AI-powered applications
Skills
AI Application Architecture
Training vs Inference
Probabilistic Model Behavior
Model Selection and Trade-offs
Tokens and Tokenization
Context Windows
Transformers and Attention
Next-Token Prediction
Pretrained and Fine-Tuned Models
Sampling and Decoding Parameters
