Course Schedule - COMP 521: Introduction to Scientific Computing and Data Science

Sixteen weeks: five projects (in rotating pairs), two individual code review presentations, and a four-week solo final project. Project dates are listed below. Class meets Tue/Thu 5:30–6:45 pm in LSN 134.

How to read this page

Deadlines are firm. Topics are not.

Project due dates are fixed — plan around them. Topics and readings are listed by week, not by day, because each session mixes instruction with working time and the balance shifts depending on where we actually are. If we need an extra session on a hard idea, we take it.

Projects are typically assigned Tuesdays and due Wednesdays at 11:59 pm PT. Use the specific dates below for each project.

Come to class prepared to discuss and use the assigned sections. This Week separates preparation, reference, and optional enrichment for the current week and retains links for earlier weeks. Chapter links below also serve as reference routes; a link to a chapter does not mean every deep dive or exercise is assigned. Readings marked (in preparation) are not yet complete lessons; their assigned sections will be identified when ready.

At a glance


First class	Tue Aug 25
Office hours	Thu 4:00–5:00 pm (and by appointment)
Add/drop deadline	Fri Sep 4
Labor Day — campus closed	Mon Sep 7
Project 4	Assigned Wed Oct 14; due Wed Oct 28
Scientific computing code reviews	Thu Oct 22, in class
Project 5	Assigned Thu Oct 29; due Wed Nov 18
DS/ML code reviews	Thu Nov 12, in class
Final-project proposal pitches	Tue Nov 24, in class
No class — Thanksgiving	Thu Nov 26
Final presentations	Thu Dec 10
Last class	Thu Dec 10
Growth Synthesis due	Mon Dec 14 (start of finals week)
Final report due	Thu Dec 17, 11:59 pm PT

Block 1 · Project 1 — Scientific Programming & the Transit Model¶

Assigned Tue Aug 25 · Due Tue Sep 8

Week 1 — Aug 25, 27 · Foundations and setup¶

Readings

Command line intro
Software setup
Git intro
Part I guide, then Chapter 1, Chapter 2, and Chapter 3: environment and clean-kernel execution; arithmetic, variables, numerical comparison; pseudocode, conditionals, and loops

Topics — environment setup, Git/GitHub workflow, Python syntax, floating point, control flow, the five algorithmic patterns

Before class Thu Aug 27 — complete the laptop setup so that you can use Python and Jupyter in class

Due Fri Aug 28, 11:59 pm PT — Project 1 Repository Check in the Project 1 repository you will link through Canvas; use the brief for its setup route

Assigned — Growth Memo 1, Tue Aug 25; due Mon Aug 31, 11:59 pm PT

Week 2 — Sep 1, 3 · Data structures, functions, and arrays¶

Readings

Part I guide, then Chapter 4 and Chapter 5: basic data structures, mutability, and function contracts
NumPy fundamentals
Matplotlib fundamentals

Topics — arrays vs. lists, vectorization, plotting; log and inverted axes; functions in P1 notebooks; modules from Project 2 onward. OOP is reference material for now and returns when a later project needs it.

Due — Project 1 + analysis notebook, Tue Sep 8

Block 2 · Project 2 — Numerical Integration¶

Assigned Tue Sep 8 · Due Wed Sep 23

Week 3 — Sep 8, 10 · Discrete computing and visualization¶

Readings

Topics — discretization, truncation vs. round-off error, Taylor expansion as the source of every method in this course

Week 4 — Sep 15, 17 · Quadrature¶

Readings

Topics — rectangle, trapezoid, Simpson’s rule; adaptive quadrature; error estimation and convergence order; verifying you achieve the expected order

Due — Project 2 (integration library + exoplanet transit model + analysis notebook), Wed Sep 23

Block 3 · Project 3 — Root Finding & Stellar Inference¶

Assigned Tue Sep 22 · Due Wed Oct 7

Week 5 — Sep 22, 24 · Root finding¶

Preparation — use the Week 5 section-level route.

Reference

Topics — bisection, Newton–Raphson, secant; convergence rates; failure modes and bracketing; Wien’s law and habitable-zone calculation

Week 6 — Sep 29, Oct 1 · Kepler orbits and stellar inference¶

Preparation — use the Week 6 science and project route.

Reference

Topics — Kepler’s equation, orbital geometry, root-finding contact points; Star objects and habitable zones for the 15-star P1 sample

Due — Project 3 (root-finding library + stellar-inference notebook), Wed Oct 7

Block 4 · Project 4 — ODE Methods & Exoplanet Interiors¶

Assigned Wed Oct 14 · Due Wed Oct 28

Week 7 — Oct 6, 8 · ODE solvers¶

Use the ODE overview for lecture and reading links. The existing ODE readings remain under revision.

Reference

Topics — Euler, explicit midpoint RK2, RK4; local and global error; order verification

Assigned — Growth Memo 2, Tue Oct 6; due Mon Oct 19, 11:59 pm PT

Week 8 — Oct 13, 15 · ODE validation and planetary interiors¶

Reference

Stability
Module synthesis
Pandas fundamentals (CSV reading and row selection)

Topics — SHO convergence against an exact solution; hydrostatic equilibrium, equations of state, and the constant-density analytic planet check

Thu Oct 15 — Pandas introduction: read a saved NASA exoplanet CSV, select columns and rows with a boolean mask, and plot mass/radius estimates with uncertainties. Broader data analysis follows in Project 5.

Assigned — Project 4, Wed Oct 14; due Wed Oct 28, 11:59 pm PT

Due Mon Oct 19, 11:59 pm PT — Growth Memo 2 (mid-semester).

Week 9 — Oct 20, 22 · Surface finding and mass–radius curves¶

Topics — locating the zero-pressure surface by refining the final RK4 step; planetary profiles; a central-pressure sweep and comparison with the published mass–radius relation. Project 4 is self-contained.

In class — Scientific computing code reviews, Thu Oct 22

Block 5 · Project 5 — Real Data & Model Fitting¶

Assigned Thu Oct 29 · Due Wed Nov 18

Week 10 — Oct 27, 29 · Project 4 completion and real data¶

Preparation and focused reference — use the Week 10 route for selected sections on variance, covariance, dot products, projections, and Pandas table inspection. These are bounded reference sections, not whole-chapter assignments.

Tuesday, October 27 — why scientific Data Science starts with a model of measurements: a primer on probability and linear algebra, connected through a scientific example. Review random variables, distributions, expectations, variance, covariance, vectors, data matrices, dot products, and projections. Include Project 4 questions and completion time.

Thursday, October 29 — begin the methods: inspect data provenance, units, and missing values, then connect a first model fit to residuals and uncertainty weights. Introduce the real Kepler photometry workflow, including Lightkurve, quality flags, and gaps, for Project 5.

Data acquisition, cleaning, and exploratory analysis remains an in-development scope note. The model-fitting reading is also in preparation; completed assigned sections will be identified when ready.

Due Wed Oct 28, 11:59 pm PT — Project 4 (ODE library + exoplanet-interior notebook).

Assigned — Project 5, Thu Oct 29; due Wed Nov 18, 11:59 pm PT

Week 11 — Nov 3, 5 · Data preparation, fitting, and uncertainty¶

Readings

Core linear algebra
Linear algebra for statistics
Probability foundations
Statistical tools
Model fitting and uncertainty (in preparation)

Topics — data preparation, design matrices, normal equations, conditioning, $\chi^2$ , transit-model fitting, and bootstrap uncertainty; final-project pathways and examples

Assigned — Final-Project Proposal Pitch, Tue Nov 3; due Tue Nov 24, in class

Block 6 · Machine Learning & Code Review¶

Week 12 — Nov 10, 12 · Machine-learning introduction and evaluation¶

Reference

Advanced OOP
Supervised learning from scratch (in preparation)
Clustering, PCA, and model evaluation (in preparation)

Topics — a focused introduction to classification and clustering; train/test splits, cross-validation, and evaluation metrics; Project 5 working time. Relevant ML methods can return during final-project check-ins. There is no separate Project 6 assignment.

In class — DS/ML code reviews, Thu Nov 12

Block 7 · Final Project¶

Assigned Tue Nov 17 · Solo · Presentations Thu Dec 10 · Report due Thu Dec 17

Week 13 — Nov 17, 19 · Inference and project scoping¶

Readings

Topics — measurement uncertainty, inference; final-project launch and scoping. The final project launches Tue Nov 17, while Project 5 is being completed.

Due Wed Nov 18, 11:59 pm PT — Project 5 (real Kepler photometry + transit-model fit + analysis notebook).

Assigned — Growth Synthesis, Tue Nov 17; due Mon Dec 14, 11:59 pm PT

Week 14 — Nov 24 · Proposal pitches¶

Due — Final-Project Proposal Pitch (5 minutes + short slide deck), Tue Nov 24, in class

In-class proposal pitches and project check-ins.

Week 15 — Dec 1, 3 · Implementation¶

Working sessions with individual check-ins. Bring results to show, not just code.

Week 16 — Dec 8, 10 · Dress rehearsal and presentations¶

Tue Dec 8 — dress rehearsal. Run your talk past me and your classmates; this is the last chance to catch a figure nobody can read from the back of the room.

Thu Dec 10 — final presentations, 10 minutes each (about 8 to present, 2 for questions). Last class meeting.

Then:

Deliverable	Due
Growth Synthesis	Mon Dec 14, 11:59 pm PT
Final report + repository	Thu Dec 17, 11:59 pm PT