In this video course quiz, you'll test your understanding of Connecting LLMs to Your Data With Python MCP Servers. By working through this quiz, you'll revisit core MCP concepts like the client-server architecture, tools that LLMs can call, resources that expose static data, and prompts that act as reusable templates.
Handling Schema Issues in Polars - You've got this great data pipeline going until one day it stops working. A schema error caused by a column upstream has stopped you in your tracks. This post talks about the four different causes of schema errors and what to do about them.
You'll also reconnect with the audit points worth applying whenever an AI agent writes Python on your behalf. The quiz contains 10 questions and there is no time limit. You'll get 1 point for each correct answer. At the end of the quiz, you'll receive a total score. The maximum score is 100%. Good luck!
Altair follows a declarative approach where you specify which columns go to which axis, the type of chart or plot, and what should be interactive. Most tools require you to write detailed boilerplate code to set up the axis and figure.
Ray was originally built for reinforcement learning research, then quietly faded as RL hit a wall. Until ChatGPT showed up. Suddenly reinforcement learning was back, as the post-training step that turns a raw language model into something genuinely useful.