Getting Help

  • You are strongly encouraged to post questions about the course material and assignments to the relevant Canvas discussions. This allows other students to help you and allows the entire class to learn from each other. I will try to respond to all unresolved discussion posts within 24 hours. These posts also satisfy the weekly requirement for contributing to a discussion.
  • Questions with personal information (e.g., grades or special circumstances) should be sent via email to me at matthew.d.parno@dartmouth.edu. I will do my best to respond within 24 hours.

Office Hours:

Weekly office hours will be held via Zoom on Tuesday from 8:00-9:00am Eastern and 2:00-3:00pm Eastern. Links to the Zoom meetings will be provided on Canvas.

Lectures and Demonstrations

Each week will have a similar rhythm. Mondays and Wednesdays will be devoted to lectures and Fridays will be devoted to code demonstrations and case studies with real world datasets. All sessions will be recorded so students can watch them at their convenience. Code will be distributed to accompany demonstrations and students are encouraged to “play” with the example code during the Friday lecture.

Lectures will be posted on the Lectures page.

Computing Resources

Using your Dartmouth NetID you will have access to Dartmouth-hosted computing resources at jhub.dartmouth.edu.

  • This site has been set up specifically for this course and will give you access to a Jupyter environment that you will use to complete assignments and run the examples provided in class.
  • We will be using the python programming language inside files called “Jupyter notebooks”. These notebooks allow code to be mixed with formatted text and are commonly used by data science practitioners. The book “Bayesian Methods for Hackers” was actually written using Jupyter notebooks. Demonstrations with Jupyter notebooks will be given in class, but students are encouraged to play around with these resources on their own to become comfortable. A good overview of Jupyter notebooks can be found here.
  • If you are not familiar with Python, git, or the command line. I highly recommend looking at the core lessons created by the software carpentry foundation, especially the “Plotting and Programming in Python” lesson.

Assignments

There are three things students will be responsible for each week:

  1. Complete the weekly problem set
  2. Contribute to a Canvas discussion
  3. Submit feedback.

More details can be found on the Assignments page.

Grading

  • Problem Sets (50%)
  • Stay-at-home midterm (20%)
  • Final project (20%)
  • Participation (10%)
    • Weekly contributions to Canvas discussions and feedback questions will ensure full credit

Textbooks

We will be mixing topics from three different books in this class. All of these books are freely available online or for purchase.

  • Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference by Davidson-Pilon (online version)
  • Introduction to Probability by Grinstead and Snell (online version)
  • Gaussian Processes for Machine Learning by Rasmussen and Williams (online version)

Prerequisites:

Math 22 (Linear Algebra) is required. Math 23 (Differential Equations) is recommended, as is some experience in Python or another programming language. Relevant probability will be covered in class.

Honor Principle

Academic integrity is at the core of our mission as mathematicians and educators, and we take it very seriously. We also believe in working and learning together.

Collaboration on homework is permitted and encouraged, but obviously it is a violation of the honor code for someone to provide the answers for you.

On written homework, you are encouraged to work together, and you may get help from others, but you must write up the answers yourself. If you are part of a group of students that produces an answer to a problem, you cannot then copy that group answer. You must write up the answer individually, in your own words.

You are encouraged to use the communication tools available to you (zoom, google hangouts, slack, etc…) to connect with other students and discuss issues, but are required to complete the work yourself.

On the midterm exam, you may not give or receive help from anyone. The exam is open-book and you are allowed to use your notes, books, and other written resources during the exam. However, you are not allowed to discuss the exam with others.

Special Considerations

Students with disabilities who will be taking this course and may need disability-related accommodations are encouraged to contact their instructor as soon as possible.