| Teaching Fellow |
Name: Adrian Calderon
Office: MCS 251
Office hours: Wed./Fri. 12:30-2 in MCS 251
E-mail: acaldero (at) bu.edu
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| Course info |
Lecture (MA 242 C1) :
Tuesday and Thursday, 5-6:15 pm, CAS 224
Discussion sections:
- MA 242 C2 - Mon 8-8:50 PSY B43
- MA 242 C3 - Mon 9:05-9:55 PSY B43
- MA 242 C4 - Mon 10:10-11 PSY B53
- MA 242 C5 - Mon 11:15-12:05 PSY B53
- MA 242 C6 - Mon 12:20-1:10 COM 213
IMPORTANT: You must be registered for both the MA 242 C1 lecture
section as well as for one of the discussion sections (MA 242
C2-C6). You may only attend the discussion section you are registered
for.
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| Text |
"Linear Algebra and Its Applications" 6th ed. with MyMathLab access, by
David Lay, Judi McDonald, and Steven Lay.
Please wait to purchase the text until you receive an email
with instructions ,
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| Exams |
First exam: Oct. 13
Second exam: Nov. 15
Final exam: TBA
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Logistical notes of interest:
- There will be two in-class midterms and a final exam.
- Homework questions will be assigned using Pearson's MyMathLab
platform and submmitted electronically. Late homeworks are not
accepted.
- There will be a written quiz on the homework in each discussion section. There will be no make-up quizzes, and the quiz must be taken in the discussion section that you are registered for.
- Your lowest two quiz and homework grades will be dropped.
- Incompletes are rarely given and only in serious situations, typically involving health problems which prevent a student from being able to complete their course work.
Make-up exams are only given in the case of serious illness (and
require a note from a doctor).
- All course information, including supplementary materials, will
be posted to the class Blackboard site.
- A class forum will be maintained on Campuswire, and will be used
to post announcements and ask/answer questions
about homework and other matters. Students are
encouraged to participate and help their class-mates.
Course grading:
- Homework 20%
- Quizzes: 15%
- First hourly exam: 20%
- Second hourly exam: 20%
- Final exam: 25%
What this course is about:
Linear algebra is concerned with the algebraic and geometric properties of systems of linear equations, and the dictionary between these. It is a fundamental tool in all areas of science, and in particular in data science, machine learning, optimization, finance etc. The following resources may help you get a better sense of the subject is about, and more can be found in the resource section of the Blackboard site.
What we will cover:
We will cover most of Chapters 1-6 of Lay's text, as well as some additional applications such as the PageRank algorithm originally used by Google. In particular, we will learn about:
- Systems of linear equations, how these can be described using matrices, and how they can be solved using Gaussian elimination
- Matrix algebra, and what various operation on matrices correspond to geometrically
- Determinants, their properties, and what geometric quantities they compute
- Vector spaces - the abstract perspective on linear algebra
- Eigenvalues, eigenvectors, and diagonalization
- Orthogonality - the generalization of things being "perpendicular", and how this can be applied in a variety of situations, including least-squares fits etc.