haiku-cse-waterfront
You can right click on the "Download" button here
http://www.cse.unsw.edu.au/~en1811/20T3/28nZwCUE1g/
Hello
You will be able to download the exam pack from 1:30pm on Monday Dec 7th (today) via the exam webpage:
http://www.cse.unsw.edu.au/~en1811/20T3/28nZwCUE1g/
To unzip the exam pack, you will need a password .
This
password
will be posted at 2pm on the exam webpage.
Hello,
In advance of the exam for ENGG1811. This is the guidance you will see on the first page of the exam.
I'm posting it now so you can read it ahead of time.
I will post another message in the coming days on where to locate the exam, when it will be released and when and where the password to access the exam will be made public!
Professor Aaron Quigley Dec 2, 2020.
The survey will close on Thursday 26 November and we would very much appreciate it if you completed it now. The overall response rate is only 14% right now :(
Thank you,
Aaron
The
ENGG1811 Sample Final Exam (20T3) can be found at this resource
. I will update this notice with
Adam's code examples
for these answer later today under week 10 resources. (this post was updated after it was emailed out)
The Final Exam will be available on the class webpage at 2pm Monday 07 December 2020. Further details of the exam will be discussed at our final lecture on Friday Nov 20th.
Exam details reminder:
Day: Monday December 7th
Start Time: Exam available to download from 2pm
End Time: You must submit your answers by 5pm Monday 07 December 2020 (3 hours after start time).
Referee: In case you have any queries during the exam, please send an email to
en1811.exam@cse.unsw.edu.au
My best with your coursework and exam preparations.
Aaron
With the code examples you will need to add ,allow_pickle=True when loading the datafiles.
See you all tomorrow and Friday.
This week we will be covering some machine learning and I'll show you 3 uses of it from our research.
RadarCat
http://www.youtube.com/embed/B6sn2vRJXJ4
Back of hand http://www.youtube.com/embed/7IJUs3iqags
Itchy nose http://www.youtube.com/embed/PB--yJzoxV8
Next Friday (week 10) we will have some practice exam questions in a live coding session.
Aaron
Webcms3 will be down from 6-9pm today (Wed 21
st
Oct)
The assignment spec can be found here: http://www.cse.unsw.edu.au/~en1811/20T3/assigns/ass1/
Lectures here:
https://www.cse.unsw.edu.au/~en1811/20T3/lec/week01/
http://www.cse.unsw.edu.au/~en1811/20T3/lec/week02/
http://www.cse.unsw.edu.au/~en1811/20T3/lec/week03/
http://www.cse.unsw.edu.au/~en1811/20T3/lec/week04/
http://www.cse.unsw.edu.au/~en1811/20T3/lec/week05/
Example data set for assignment 1:
http://www.cse.unsw.edu.au/~en1811/20T3/lec/week03/code_prelim_3B/voltage_data_complete.txt
Best,
Aaron
Hello
The clarify a few points raised on the Forums I've updated the specification for assignment 1.
ENGG1811: Assignment 1, Peak Detection
Change Log:
1. Your functions max_peak, total_peaks, peak_list_from_file should import peak_list in your code for these three functions [Updated Oct 13th].
2. If there are no peaks in the inputs given max_peak should return the string “No Peaks” [Updated Oct 13th]
3. The text file format is one number per line (as shown in voltage_data_complete.txt in week 3) [Update Oct 13th]
4. For the purposes of this assignment we are only looking to identify peaks above the mean (and we will only test for such conditions) [Oct 13th]
Best
Aaron Quigley
Hi
ENGG1811 Self-Directed Lab 1: Spreadsheets
The Due date is week 8: 5 pm, Tuesday 3rd November 2020.
Select labs in the menu on the left and select week 5.
Best,
Aaron
Just a few tips from some of your questions and the tutors today.
1. Please read the entire practical first and think carefully about the order in which you might implement these functions (I ordered the functions to encourage you to first think, plan, design, outline your ideas and before you code)
2. Where the assignment says a "continuous unbroken series of 1 1 1 values" this means a consecutive series of 1s e.g. 00000111110000 (one peak) or 00000111110000111111110000 (two peaks) or 00011000110000110000110 (four peaks) or or 0001110001100001000010 (four peaks)
3. If you haven't started the assignment I would strongly encourage you to try completing the examples from code_prelim_4A and code_final_4A from today's lecture to practice with lists and analysis.
See you all on Friday.
Best,
Aaron
Hello
Thanks to Rachel and others for pointing out the naming inconsistencies between the .PDF and the .zip code I gave you.
I hope the code and the PDF for assignment one now match (if you spot any issues please do email me).
You need to implement the following four functions, each in a separate file. You need to submit these four files, each containing one function you implement
1. def total_peaks(inputs, smoothing, th, influence) :
2. def max_peak(inputs, smoothing, th, influence) :
3. def peak_list(inputs, smoothing, th, influence) :
4. def peak_list_from_file(smoothing, th, influence, file_name) :
Best,
Professor Aaron Quigley
Hello
Assignment 1 is now online see: Assignment 1 with a focus on "peak detection" in time series data.
Why does this matter? Well, finding peaks in data is a very common problem often with some difficult detection methods. Here we have a reasonably simple approach which could be used with data from a pulse oximeter, for example.
"A pulse oximeter is a small device that clips onto your finger and reads your heart rate and blood oxygen levels. They are now being used to help identify potential COVID-19 Cases, particularly asymptomatic cases. Pulse oximeters are frequently used to provide real time measurements of heart rate and blood oxygen saturation (Sp O 2)."
In this assignment, your goal is to write a python program to determine various characteristics about some time series data you are given. These types of problems are very common in many disciplines, including computer science, engineering, medicine and science. There are many different types of peak detection problems, the setting of this assignment is similar to that used in
pulse oximeter data
. The method described in the assignment is based on a sliding window which allows us to calculate a standard score of the number of standard deviations aways from the mean a value is.
Such peak detection has been used to understand the periodic distributions of nucleotides from the genome of SARS-CoV-2 had been sequenced and structurally annotated or pollution peaks or heart rate detection.
Peak detection is a very common task in the understanding of data.
The provided .zip files has the 4 .py files you should complete along with some testing code you can use.
Hello.
Our Wednesday lecture will start at 9am, Sydney time.
My plan is to get through most of lecture material today so we have time for some live/pair programming with Adam this Friday. As always today will be recorded as I know some of you are in time zones which make attending live difficult.
I also wanted to note that I'll be discussing the assignment this Friday after we have covered for loops, list processing, indexing and slicing in slides 3a and 3b today.
Best,
Aaron
Help sessions are now available with one running today (Tuesday 2-3pm) on Blackboard Collaborate.
See Help Sessions in the left panel on the course webpage.
They will be recorded as I know some of you are in time zones which make attending live difficult.
Aaron
All the materials for Week-01 are now online including
Thanks to everyone who attended the lectures live, your feedback and questions are very helpful. See you next week.
First published in 1869, Nature is the world's leading multidisciplinary science journal. Today Nature published an article on NumPy, which I will be introducing you to in a few weeks in this course.
“NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves and in the first imaging of a black hole”
https://www.nature.com/articles/s41586-020-2649-2
Here we focus on research led teaching so I’ll be incorporating some of this paper into my version of the slides along with my planning for the assignments.
See you all tomorrow for our live coding lecture from 9am!
Professor Aaron Quigley
Please remember the student reps they "represent the CSE students to the relevant staff, anonymising any grievances, questions, or feedback. We also run regular surveys, presented to the Head of School to address any concerns before the end of term."
See: https://www.cse.unsw.edu.au/~stureps/
All labs are Online in Weeks 1 and 2 and they will be conducted in Blackboard Collaborate or Teams. To find this: Go to the
moodle
page for this course, select
Remote Class Rooms
and then your lab time slot. If your lab is in Teams, you will be sent an invite by your tutor. For the rest of the term, labs will be Online unless you have registered for Face-to-Face classes in Weeks 3,5,7,9. A reminder email will be sent to students registered for f2f at the end of Week 2.
Hello
Your Week-01 lecture notes and preliminary code examples are now available on webcms
https://webcms3.cse.unsw.edu.au/ENGG1811/20T3/
I've also posted the draft slides and preliminary code examples for weeks 2 - 5 are also online. I may make some small improvements to the slides before and during lectures, in which case I will post updated slides online.
Professor Aaron Quigley
Hello
We will use Blackboard Collaborate for live lectures, look for the session names " Lecture (Wed 9am - 11am) " or " Lecture (Fri 9am - 11am ) " respectively.
The recordings will be available later.
Best,
Aaron
p.s. I'm planning to record an extra lecture on Wednesday which I will ask you to watch before Friday and then during Friday's lecture we will have a live coding Q&A session so everyone can ask questions and get ready for the weeks ahead.
ENGG1811 is offering mixed face-to-face/online labs. If you are interested, fill in the form .
Note that f2f labs will only run if there is sufficient interest.
Hello
The course outline and advice on safe return to campus and content for week 1 is now online.
Aaron
Welcome to ENGG1811 from Professor Aaron Quigley your lecturer. T3 will begin shortly and details of the course plans are being added here in WebCMS at the moment. While lectures will be online, our plans are to have labs in person and online. In terms of returning to campus you should read this guidance in full prior to returning to campus. You might also wish to refer to the Safe Return to Campus FAQ
Please visit the Course Outline and read my full welcome message which outlines the COVID-19 situation further.