Problem Statement

This set contains seven independent multiple-choice questions from the ML 2.0 section of the assessment. Each question is self-contained: read the stem and pick the single best option. Topics covered: retrieval-augmented generation (RAG) and the session/context model of an MCP server. Question 1. How does poor Information Retrieval affect RAG model performance? It leads to irrelevant or inaccurate answers It decreases model size It increases model training time It doesn't affect the model Question 2. What happens when context is lost in an MCP server session? The session is terminated The user receives a timeout message The session continues without context The user is notified to re-authenticate Question 3. What is a primary challenge when integrating knowledge into RAG models? Ensuring retrieved data is both relevant and accurate Increasing model speed Decreasing the number of data sources Ensuring overfitting does not occur Question 4. What is a critical step when fine-tuning a gene