Deadlines. Homework must be submitted by 11:59PM on Thursdays. Please submit the homework (including code) on Gradescope.
Late homework policy. You are granted a total of 4 late days throughout the quarter, with a maximum of 2 late days per individual homework. We understand that personal emergencies occur, and in such cases, extensions may be granted. Please communicate these circumstances as early as possible. Apart from personal emergencies, late homework submissions may not be accepted beyond the allocated late days.
Homework collaboration. You may discuss the homework as a group, but must write your own code and your own solutions individually. If you work with a partner/group, you must declare your partners in writing on your homework.
Generative AI policy. The use of generative AI tools (such as ChatGPT) for homework and exams is regulated under the same policies as collaboration with peers. You may consult generative AI for ideas and explanations, but all submitted work—including code and written answers—must be your original creation. Declare any use of generative AI as you would with any other collaborator.
Programming requirements. The homework will use the Julia language. This is required for this class. Other languages (Python, Matlab, R, Excel, etc) will not be supported or graded. You must turn in your code with your homework.
Past homework questions. Here is a file containing many past homework questions. Note that many of them require Matlab, and use old data files which are not available. However we are posting them here to give you a flavor of the material covered, and the types of homework and exam questions to expect.
Data files. Data files are supplied in JSON format. See below for instructions on how to load these files into Julia.
Homework 1, due Friday 7/5, at 11:59 PM. solutions
Note: Homework assignments are generally due on Thursdays. HW 1 is an exception, as the corresponding Thursday is the 4th of July.
Homework 2, due Thursday 7/11, at 11:59 PM.
Homework 3, due Thursday 7/18, at 11:59 PM.
Load JSON data files in Julia using the method in readclassjson.jl. Download that file and save it somewhere useful, then use readclassjson(filename) to load the data into a dictionary containing all of the variables defined in the file.
For example, if the example_file.json contains a variable called X, you can read it by using
include("readclassjson.jl")
data = readclassjson("example_file.json")
X = data["X"]