Jay Pantone

Assistant Professor
Marquette University

jay.pantone@marquette.edu


Math 6000 – Scientific Computing

Spring 2023, Marquette University

Foundational methods and techniques of scientific computing in the mathematical and statistical sciences. This course will cover fundamental computational algorithms aimed toward applications in science and engineering. Students will implement algorithms, and visualize and validate their outcomes. Further, students will be introduced to and implement best programming practices. Prereq: MATH 2450 or equiv. or consent of instructor; MATH 1700 or equiv. introductory statistics course or consent of instructor, and programming competency in a high-level language.

  • Lectures:
    M, W, F 11:00am - 11:50am
    Cudahy Hall 208
  • Office Hours:
    Monday, 1:00pm - 2:00pm
    in person, Cudahy 307
    Wednesday, 2:30pm - 3:30pm
    on Microsoft Teams
    and by appointment (just email me!)

Course Information

The official syllabus is available here.

 
Announcements

Textbook

Important Dates
Tues, Jan 17 Classes begin
Wed, Jan 25 Last day to add/drop classes or request CR/NC option
Mon, Mar 6 — Sat, Mar 11 Midterm exam period
Mon, Mar 13 — Fri, Mar 17 Spring break, no classes
Thurs, Apr 6 — Mon, Apr 10 Easter break, no classes
Fri, Apr 14 Last day to withdraw from classes
Fri, May 5 Last day of classes

Daily Calendar
# Date Topics Announcements / Homework
Week 1
1 Wed, Jan 18 Syllabus
Topic 1 - Installing Python and other tools
Guide to installing and using Python
Before class on Friday:
  • Install Python3.8 or higher, Git for Windows (if applicable), and Sublime Text or some other IDE.
  • Install a package with pip.
  • Update pip.
  • Write and run a very basic python program.
  • Try out interactive mode.
2 Fri, Jan 20 Topic 2 - Quick(ish) Introduction to Python (started) NOTE: You may need to right click the links to notebooks and save them, otherwise they might open in your browser in a messy text format. Windows may add a ".txt" extension automatically when you download the the notebook files. The extension should be .ipynb, not .ipnb.txt. If so, you will need to remove the ".txt" file extension to open it correctly.

Week 2
3 Mon, Jan 23 Topic 2 - Quick(ish) Introduction to Python (continued)
4 Wed, Jan 25 Topic 2 - Quick(ish) Introduction to Python (finished) Topic 3 - Greedy Algorithms (started) Lecture Notes

5 Fri, Jan 27 Homework 1 Assigned — see D2L
Topic 3 - Greedy Algorithms (continued)
Lecture Notes
Week 3
6 Mon, Jan 30 Topic 3 - Greedy Algorithms (continued) Lecture Notes
7 Wed, Feb 1 Topic 3 - Greedy Algorithms (continued) Lecture Notes


8 Fri, Feb 3 Topic 3 - Greedy Algorithms (continued) Lecture Notes

Week 4
9 Mon, Feb 6 Homework 1 Due
10 Wed, Feb 8
11 Fri, Feb 10
Week 5
12 Mon, Feb 13
13 Wed, Feb 15
14 Fri, Feb 17
Week 6
15 Mon, Feb 20
16 Wed, Feb 22
17 Fri, Feb 24
Week 7
18 Mon, Feb 27
19 Wed, Mar 1
20 Fri, Mar 3
Week 8
21 Mon, Mar 6
22 Wed, Mar 8
23 Fri, Mar 10 Midterm Exam, In-Class Part
Take-Home Part Assigned
(tentative)
Spring Break
Mon, Mar 13 Spring Break — no classes
Wed, Mar 15 Spring Break — no classes
Fri, Mar 17 Spring Break — no classes
Week 9
24 Mon, Mar 20
25 Wed, Mar 22
26 Fri, Mar 24 Take-Home Part of Midterm Exam Due (tentative)
Week 10
27 Mon, Mar 27
28 Wed, Mar 29
29 Fri, Mar 31
Week 11
30 Mon, Apr 3
31 Wed, Apr 5
Fri, Apr 7 Easter Break – no classes
Week 12
32 Mon, Apr 10 Home Work Day, no in-person lecture
33 Wed, Apr 12
34 Fri, Apr 14
Week 13
35 Mon, Apr 17
36 Wed, Apr 19
37 Fri, Apr 21
Week 14
38 Mon, Apr 24
39 Wed, Apr 26
40 Fri, Apr 28
Week 15
41 Mon, May 1
42 Wed, May 3
43 Fri, May 5