Math 173A Optimization Methods for Data Science I
Fall 2019 Course Syllabus
Course: Math 173A Title Optimization Methods for Data Science I Credit Hours: 4
Textbook: There is no required textbook for the course, and course notes will be posted. However, there may be recommended readings.
Lecture: Attending the lecture is a fundamental part of the course; you are responsible for material presented in the lecture. You should expect questions on the exams that will test your understanding of concepts discussed in the lecture.
Grading: Your cumulative average will be the best of the following two weighted averages:
20% Homework, 20% Midterm Exam I, 20% Midterm Exam II, 40% Final Exam
20% Homework, 20% Best Midterm, 60% Final Exam
You must pass the final examination in order to pass the course. Note: The default policy is that there are no makeup exams. If you miss an exam then your course grade
will be computed with the final exam accounting for 60% of your weighted average.
Homework:
Homework will be assigned on the course
homework page.
Late homework will not be accepted.
The default plan is that all assignments will count towards your final grade.
Gradescope: All standard homework assignments are to be submitted via Gradescope.
Your login is your university email, and your password can be changed (or set) here.
Assignments should be in a single pdf file before being uploaded, or as a picture for each question.
Please make sure your files are legible before submitting. Unreadable solutions will not earn credit.
Most word processors can save files as a pdf.
There are many tools to combine pdfs, such as here, and others for turning jpgs into pdfs, such as here.
Midterm Exams: There will be two in-class (2) midterm exams.
Midterm 1 will be on Tuesday, October 22 -- in class.
Midterm 2 will be on Tuesday, November 19 -- in class.
Final Exam: The final examination will be held at the following date and time.
7 pm - 10 pm, Dec 13
Please note:
It is your responsibility to ensure that you do not have a schedule conflict involving the final examination.
You should not enroll in this class if you cannot sit for the final examination at its scheduled time.
Regrades: If you wish to
have your exam regraded, you must observe the following rules:
If grading is done on paper: Return your exam immediately. Regrade requests will not be considered once the exam leaves the room.
If grading is done via gradescope: Gradescope regrade requests will be only accepted for one week after the exam is graded.
Academic Dishonesty: Academic dishonesty is considered a serious offense at
UCSD. Students caught cheating will face an administrative sanction which may include suspension or
expulsion from the university. Click here for more information.