Hi Reader,
This is a "special edition" of Tuesday Tips! π
Instead of the usual format, I'm going to pose a coding question and ask YOU to write the solution!
You can send me your solution, and I'll showcase the best solutions in next week's newsletter! π
There's a classic probability puzzle based on the TV game show "Let's Make a Deal" and named after its host, Monty Hall. Here's the puzzle:
You are a contestant on a game show. In front of you are three closed doors. Behind one of the doors is a car, and behind the other two doors are goats. Your goal is to pick the door with the car.
The host asks you to choose a door. You tell the host your choice. Instead of telling you whether your choice was correct, the host (who knows which door contains the car) opens one of the two doors you didn't choose and reveals a goat.
You now have the opportunity to keep your original choice or switch your choice to the door that is still closed. Which should you choose?
For example, let's pretend that you started by choosing door #1. The host opens door #3 to reveal that it contains a goat. Should you keep your original choice of door #1 or switch your choice to door #2?
One of the "superpowers" of being able to write code is that you can use simulations in order to solve problems like these! In this challenge, I want you to write Python code to simulate this problem.
Specifically, I want you to simulate that you are a contestant on this show 1000 times. Each time, you pick a random door as your first choice, let the host open a door that reveals a goat, and then switch your choice to the door that the host didn't open. With that strategy (known as the "always switch" strategy), how often do you win the car?
Here are a couple of details that I want to be clear about:
If you have questions about any other details, please let me know!
The goal of this challenge is to practice writing Python code to solve a problem. In other words, I don't just want to know the "answer" to this puzzle, rather I want to see the code you wrote to solve the problem!
There are two ways you can submit your code to me:
Please don't copy and paste your code into an email, send me a screenshot of your code, or send me your code as a file attachment. π
In next week's newsletter, I'll showcase the best solutions! I'm looking for code that is concise, easy-to-read, and represents the data in an elegant way.
If you used an AI tool to help you write the code, please let me know. I'm guessing that the most elegant solutions will come from humans, not AI! π€
If you enjoyed this weekβs newsletter, please forward it to a friend!Β Takes only a few seconds, and it really helps me out! π
See you next Tuesday!
- Kevin
P.S. Data structure humorβ
Did someone awesome forward you this email?Β Sign up here to receive data science tips every week!β
Join 25,000+ intelligent readers and receive AI tips every Tuesday!
Hi Reader, This week, I've got a short tip about AI agents, followed by some Data School news... π Tip #56: What are AI agents? Google is calling 2025 "the agentic era," DeepLearning.AI says "the agentic era is upon us," and NVIDIA's founder says "one of the most important things happening in the world of enterprise is agentic AI." Clearly AI agents are a big deal, but what exactly are they? Simply put, an AI agent is an application that uses a Large Language Model (LLM) to control its...
Hi Reader, Last week, I launched a brand new course: Build an AI chatbot with Python. 120+ people enrolled, and a few have already completed the course! π Want to join us for $9? π Tip #55: Should you still learn to code in 2025? Youβve probably heard that Large Language Models (LLMs) are excellent at writing code: They are competitive with the best human coders. They can create a full web application from a single prompt. LLM-powered tools like Cursor and Copilot can autocomplete or even...
Hi Reader, The Python 14-Day Challenge starts tomorrow! Hope to see you there π€ π Tuesday Tip: My top 5 sources for keeping up with AI I'll state the obvious: AI is moving incredibly FAST π¨ Here are the best sources I follow to keep up with the most important developments in Artificial Intelligence: The Neuron (daily newsletter) My top recommendation for a general audience. Itβs fun, informative, and well-written. It includes links to the latest AI news and tools, but the real goldmine is...