Welcome to your learning hub

Whether you’re brushing up on the basics or diving into something completely new, this is the place to learn, grow, and explore. We’ve gathered a collection of short, easy-to-follow lessons designed to unlock statistical insights to sharpen your planning strategy.

Just pick a topic below. No deadlines, no pressure.

Understanding the power of probabilities in PLANS

Understanding Probabilistic Model Distributions

What’s Likely, What’s Not — and Why It Matters? When you’re working with data, it’s less about exact answers and more about what’s likely to happen. Probabilistic model distributions help you see the full picture, not just a single outcome. They show you where the data tends to

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Monte Carlo Manual Exercise

This Monte Carlo by hand exercise is a simple yet powerful introduction to probabilistic thinking in well planning. By manually simulating drilling durations or costs, you’ll uncover how small variations can impact outcomes—and why embracing uncertainty with tools like PLANS leads to better, more resilient project decisions. It’s a

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Think in probabilities: Advanced PLANS Tactics

Discover how to push the boundaries of traditional forecasting by embracing probabilistic thinking. You’ll learn practical ways to handle complex decisions, explore different possible outcomes, and adjust your plans as things change. It’s all about getting more confident with the unknown and making better choices by thinking in terms of probabilities, not guesses.

Monte Carlo is Key to Crushing Uncertainty

Your browser does not support HLS playback. Monte Carlo models are a powerful way to understand uncertainty in complex systems. Instead of trying to predict a single outcome, these models simulate thousands of possible scenarios, each with random variations in input. The end result is a distribution of results that

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Understanding Probabilistic Model Distributions

What’s Likely, What’s Not — and Why It Matters When you’re working with data, it’s not always about finding exact answers — it’s about understanding likelihoods. Probabilistic model distributions help you see the full picture, not just a single outcome. They show you where the data tends

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The Beauty of Monte Carlo - through casinos, code, coffee and the Cosmos

What’s beautiful about it, you ask? Well, it’s a beautiful part of Monaco, and has a legendary casino 😎 And for a computer scientist, it’s beautiful in a way many other fundamental algorithms are. * Neural networks mimic synapses in our brains in a simple way. You excite the nodes, and out

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Bridging Uncertainty and Automation in PLANS

Behind the Plans

What defines a simulation? In Plans, every simulation is a tree structure like shown below: As indicated in the figure, there are different ways to “walk” a tree. Plans walks the tree in a depth first fashion, which is something we’ll get back to. Each node in the tree (numbered

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Code with Plans

Use rules as functions and plans as calls, and you have a minimal, vectorized functional programming language! Let’s break it down: The name field Ah, the hardest part of coding, naming things! Well, you have to name them something, and this is a good place for it. You know the

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Software Updates

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