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Introduction

Welcome to the MLDS lab! If you're a new student here, we're happy have you join the team. This quick-start guide is intended to be a rapid orientation, exposing you to the most important subjects and keywords you'll be using during your time in our group.

By the end, you should have a more specialized vocabulary in astrodynamics, machine learning, and software engineering which you can use to ask more precise questions to fill in any knowledge gaps.

What is the structure of this handbook?

This book is divided into four parts:

  1. Quick-Start (this) --- introduction to key topics used in the group.
  2. On-Boarding --- exercises that cover fundamentals in astrodynamics, machine learning, and software engineering.
  3. Documentation --- lab policies on paper writing, presentations, etc. and additional in depth resources on the PhD program and logistics.
  4. Resources --- a list of carefully procured external resources.

Tips before getting started

Links to specific videos and lecture series are provided throughout. I recommend watching these; however, considering doing so on 3x or 4x speed when possible. Our goal is to introduce you to key topics, focusing on building familiarity rather than mastery. After each lecture, write down a short summary from memory to capture what you've learned.

Overriding Video Playback Rate to >2x

You can force videos to play even faster than the 2x limit imposed on youtube by inserting document.querySelector('video').playbackRate = 2.75 in your web-browser's console. You can reach this console in most browsers using the F12 key.

In my experience, for lecture series that include people writing notes or whiteboarding, you can go as fast as x3.5 and still follow along successfully.

How long will it take to learn everything?

Transitioning into a new graduate program can be overwhelming, especially when you're aspiring to be proficient in both astrodynamics and machine learning. Unlike programs where you might specialize in one area, here you'll need to master both fields. This means covering a significant amount of material in a relatively short period. However, don't be discouraged; the process might be more manageable than you expect.

To put things into perspective, consider the structure of a typical graduate degree program. Generally, you would complete around 30 credits, or 10 courses. Assuming these are typical Tuesday/Thursday classes with 28 lectures each, we can calculate the time commitment:

Time per course: \(28 \text{ lectures} \times 1.25 \text{ hours} \div 3.5 \text{ playback rate} = 10 \text{ hours}\)

Total time for all courses: \(10 \text{ hours/class} \times 10 \text{ classes} \div 8 \text{ hours per workday} = 12.5 \text{ workdays}\)

This means that by watching your lectures at 3.5x speed, you could cover the equivalent of an entire graduate curriculum in just 2.5 work weeks.

To be clear, I'm not asking you to do this. All this is to say, when / if you see a class playlist on Youtube, considering committing an hour or two a day to watching + actively engaged with that material. You'll be amazed what you can accomplish in just one month's time.