Admin on The Art of Computing

Course Mechanics -- Important

Enthusiastic Hugo User — Wed, 15 Feb 2017 02:12:01 AEDT

This document summarizes the logistics for participating in Art of Computing and getting credit for it.

All registered student need to read and understand all the content (and information it links to) here. Comments and changes will be incorporated up until the 2nd week of semester.

The goal and position of this course is described here.

Course schedule

The time and location of classes, labs, as well as a weekly breakdown of topics are here.

Course staff and contact

You can find who we are, and how to contact us here.

Assessment scheme and policy

The due dates are specified here, read this for the grading scheme.

Communication and information dissemination

Course communication will be though the following channels.

This website: https://artofcomputing.cecs.anu.edu.au will host basic course information, and important public-facing announcements.
Wattle site for COMP1030
- https://wattlecourses.anu.edu.au/course/view.php?id=19302
- Will be used to host:
  - Course recordings
  - Lab group signup
  - Submit and return assignments
  - Course discussion forum for you to ask and answer questions.

Notes

Students are expected to attend lectures and all tutorials in normal circumstances. The lectures and tutorials/labs are designed as an integral whole and each contain new knowledge and skills that students are expected to master. There are no attendance marks.
We strive to record and archive all lectures using the ANU-wide Echo360 system for students’ benefits. As with many automated systems, recording could go wrong or go missing, we will not try to make up for the missing recordings after the lectures, it is up to you to make up for the material if you’ve missed the lecture (with lecture notes, extra reading, Q&A with lectures/tutors in lab and contact hours, discussing with your peers … ).

Grading Scheme

Enthusiastic Hugo User — Wed, 08 Feb 2017 11:13:58 AEDT

Q: How will I be graded in this class?
A: 50% assignments, best-(N-1)-out-of-N; 5% weekly exercise problems; 45% final exam – required, is a grading hurdle, see below. The rest of this post specifies details.

Grading breakdown

50% assignments, best-(N-1)-out-of-N; 5% weekly exercise problems; 45% final exam.

In order to pass the course, you must have secured ⁵⁰⁄₁₀₀ according to the breakdown above and have attended and scored > 40% for the exam.

Assignments

There will be 8 submitted lab assignments throughout the semester – roughly one assignment per week that consist of a handful of questions. Lab1 and lab2 count as one assignment and are due on Monday of week 3 (see submission). In the rest of this post, N=8.

Your assignment grade is the average from the best N-1 out of these N assignments. In other words, the worst assignment doesn’t count, or you can miss one assignment without penalty.

Weekly exercise problems

We make available a few multiple-choice questions on Wattle with every section of the course. The main purpose is to help you practice computational thinking around each week’s material.

Q: Why 5%? We assign a 5% mark to encourage students to attempt and eventually get all answers right for each problem.

Exam

There will be a final exam held around the end of semester. Its details will be released closer to time. There will be no midterm exam.

Policy

Late assignment submissions: 5% penalty at 24-hour cut-off

Late assignments will not be accepted. However, we understand that sometimes things happen and you may not be able to make it in time despite best efforts.

In case you must be late: There is a hard cut-off of one day (i.e. 24 hours) for each assignment, after which late submission receives no grade. If you submit after the official deadline but before 24 hours have elapsed, your assignment will be graded as-is (say X marks), and you final grade will be 0.95 * X, i.e. part of a day counts as one day.

Your N-1 best assignments are considered graded, and the N-th is considered ungraded. That is to say, you can skip one assignment in the whole semester without penalty.

Collaboration policy

We expect individual assignments. That is, you are expected to write the submitted programs and written assignment independently. The only exception are assignments that explicitly allow pair-programming.

Team work / Pair programming There are a number of assignments where team work (with a team size up to 2) is explicitly permitted. Here is how this works:

You are free to team up with any other student enrolled in this class.
You have to specify in submission comments who you worked with.
The two of you then submit identical files to wattle.
The tutor then grades either copy of the assignment, people in the same team will get the same score.
Both submissions will have to be on-time.

Students are expected to uphold ANU Code of Practice for Student Academic Integrity.

2017 Class Schedule

Enthusiastic Hugo User — Thu, 12 Jan 2017 13:10:06 AEDT

This is an outline of the course schedule and content.

Lectures
- Monday 1200-1300 (PSYC G8)
- Tuesday 1000-1100 (PSYC G8)
- Wednesday 1200-1300 (PSYC G8)
Lab/tutorial slots
- Thu 1400-1600 (CSIT N112)
- Fri 0900-1100 (CSIT N112)
- Fri 1100-1300 (CSIT N112)

Part I – Introduction to Programming

Week 1 (20-24 Feb)

Introductory lecture: What is Art of Computing, what to expect (LX+DP, guest appearance Tony Hosking)

Introduction to programming via Karel the Robot

Procedural abstraction (LX)
Conditionals and loops (LX)
Lab 1: Snap! and Karel the Robot.

Week 2 (27 Feb - 3 Mar)

Programming continued.

Variables (conditionals and loops with variables) (LX)
Procedures with parameters and return values, input and output. (LX)
cultural lecture: different levels of abstractions (DP)
Lab 2: Snap and Karel MK II.

Week 3 (6-10 Mar)

Data structures

Arrays and lists (LX)
Applications to arrays and lists, building blocks for software - recommender system (LX)
(No Wed lecture, music guest lecture 8 May)
Lab 3: Make Snap! Sing and Talk.

Week 4 (14-17 Mar)

(no Monday lecture, Canberra Day 13 Mar)

Recursion

Recursion - guessing a number (LX)
Recursion2 - binary tree, more recursion examples (LX)
Lab 4: Recursion.

Part II – Computational Thinking

Week 5 (20-24 Mar)

Optimization, logistics, and solving sudoku

The 8 Queens problem (LX)
Computational problem-solving and discrete optimisation (LX)
Optimization (Tommaso Urli)
Lab 5: Solving sudoku.

Week 6 (27-31 Mar)

Computational biology and dynamic programming

Dynamic programming - Knapsack problem (DP)
Sequence alignment (DP)
Computational thinking in biology (Gavin Huttley)
Lab 6: Sequence alignment.

Two Week Teaching Break (3 - 17 Apr)

Week 7 (18 - 21 Apr)

(No Monday lecture, Easter Monday 17 April)

Computational social science, sentiment analysis, and hashing

Searching and sorting, notions of algorithm complexity (LX)
Dictionaries and hashtables (LX)
Lab 7: Sentiment analysis.

Week 8 (24-28 Apr)

Computational thinking in the humanities (Terhi Nurmikko-Fuller);
(No Tue lecture, ANZAC day 25 Apr)
Intro to machine learning and data analytics (LX)
Lab 7 take 2: Sentiment analysis.

Week 9 (1 - 5 May)

Data science, predictive analytics, and curing diseases

Trees (LX)
Decision trees (LX)
Digital Music and Live coding (Benjamin Swift)
Lab 8: Diagnosing disease with decision trees.

Part III – Computing in the world

Week 10 (8 - 12 May)

Programming beyond snap! - A look at python
Introduction to the digital computer: Data representation
Continue work on Lab 8

Week 11 (15 - 19 May)

Introduction to the digital computer: Logical functions and circuits
The digital computer, part 1.
The digital computer, part 2.
Lab 9: Simulating combinatorial circuits.

For this lab, we will be using Logisim, a tool that simulates computer hardware.

Week 12 (22 - 26 May)

cultural/guest lecture Computing in the world, “Debate” AI and its impact (TBC)
The limits of computation: The Halting problem and NP-hardness (DP)
Quantum computing (TBC Elanor Huntington)

Contact Information

Enthusiastic Hugo User — Sun, 08 Jan 2017 10:50:40 AEDT

Information about the COMP1030 team and how to reach us is as follows.

Course website (here)

Is used to host lab sheets and course logistic information.

Course Wattle Site and Contact

https://wattlecourses.anu.edu.au/course/view.php?id=19302

This is used to host lecture slides, sample code, used to handle assignment submissions, and is the primary venue of two-way course communication.

We (course staff) will announce schedule changes and release of key material on the wattle news forum.

We encourage all of you to discuss course-related topics, ask and help answer questions among each other on this forum. This forum will be semi-regularly monitored by tutors and lecturers. Course-related questions that are emailed to us will be responded on the forum when appropriate.

Requests that are meant only for lectures/tutors can be emailed to us clearly marked with “COMP1030” in the subject line – requests without this may get filtered into junk piles and not answered.

Lecturers

Lexing Xie Office: Brian Anderson Building B252

Dirk Pattinson Office: Brian Anderson Building B231

Tutors / Teaching Assistants

Rohit Ram

Siqi Wu

Dawei Chen

Student Comments From the 2016 COMP1030 Class

Enthusiastic Hugo User — Thu, 05 Jan 2017 13:10:06 AEDT

The 2016 edition of The Art of Computing has concluded. So what did students say in the Official ANU Student Survey ?

What were the most notable strengths of the course?

All subject matter covered in the course was interesting, and never once boring. Being able to explore the fundamentals of programming was a real joy to learn, and the way in which we learned concepts then applied them to real life situations in our labs was just fantastic. Really enjoyed every second of this course!
Content was interesting and covered relatively well.
It covered a wide variety of topics.
The diversity of the content, and the topics are very interesting - particularly the guest lectures. The lab assignment provided by this course is really interesting, since Professor Xie makes her researches in machine learning, some topics she gives us are from this area, which are really interesting. I cannot imagine that machine learning can be such close to our life, it is fantastic. At the beginning of this course, I couldn’t have understood why this course teach us such a simple programme language, SNAP!, which is not powerful enough like Java, Python, etc. But in the end of this semester, I finally understand. This language is very suitable to us who have never programmed before. And the thinking of programme is conveyed to me in a simple way by using “SNAP!” . In the future programme, I can understand other language very fast since I have got the thinking of programming and computing. It is really a good course.
The tutors were all really helpful and were clear in their explanations when the lecture material wasn’t quite straightforward.
Very interesting assignment

What suggestions for improvement would you like to make?

The learning curve really was steep around the middle of the semester as was explained. I would personally prefer just a gradual climb in difficulty.
Having the entire course be 90% dependent on weekly assignments don’t really give the students a lot of incentive to improve their skills, wherein getting mediocre marks early on due to minor errors can affect motivation and drive once the course material gradually becomes more difficult.
Lecture recording was very poor. If I attended another lecture at the same time, the lecture recording is relatively useless because I can’t see what the lecturer is doing.
I think there is nothing wrong in this course.

Assignment Submission Instructions

Enthusiastic Hugo User — Thu, 05 Jan 2017 11:13:58 AEDT

Q: How and when should I submit the assignments?
A: Online, (almost) every Monday 9am …

Assignment due

9am the Monday after the corresponding lecture / tutorial.

Each assignment consist of a small list of tasks that are structured around the corresponding lectures, and we expect many students to be able to complete the weekly assignment in a few hours.

Note:

Lab 1 and 2 are both due on the Monday of week 3.
See here for Grading Scheme, Late Policy and Collaboration Policy.

Submission procedure

Assignment submission and grade returns are done via the course wattle site https://wattlecourses.anu.edu.au/course/view.php?id=19302

Format and Naming of your submission file

When you are done with the assignment, export your blocks.

From Snap!, use the “export blocks” (or export project … ) menu item as necessary, and then copy-paste the xml code into a plain text editor, save it with a filename in the format of

u1234567_labX_*.xml

Here “u1234567” is your ANU UID, “labX” with X=2, 3, 4, … denotes which assignment it is, and the “*” symbol can be any string that help you distinguish the submission file (e.g. final, submit, version3, … ).

Submission in any other format will not be accepted. If you have questions about how to save the submission file, ask the tutors/lecturers for guidance.

Testing your submission

As always, test your submission file – to make sure everything that should be included is indeed (correctly) included!

To do so:

Start a fresh chrome/chronium session
Load the project for the corresponding lab.
Use the “import … ” function from Snap! to load your submission file containing the blocks.

Now run these blocks – make sure they work as expected.

Student Comments From the 2015 Class

Enthusiastic Hugo User — Wed, 12 Aug 2015 13:10:06 +1100

The 2015 edition of The Art of Computing has concluded. So what did our students say?

From the Official ANU Student Survey

What were the most notable strengths of the course?

Challenging lab assignments which expanded upon the basics taught in the lectures. The labs were also of a good length and assistance was provided throughout. The lectures followed a clearly defined structure, which was helpful for revision.
Engaging, entertaining and knowledgeable lecturer. Snap is a great medium for teaching abstract concepts which might be held back until second or third year due to semantic problems. Interesting practical assignments which can easily be seen to be useful.
This course was incredible.

The foremost strength was the collection of topics covered. I walk away feeling I have been given real, working literacy in an area totally foreign to my normal studies. Additionally, the integration with interdisciplinary application was well done. Pascal is a top-tier lecturer, and brought the course to life.

The assessment schedule encouraged equal dedication to the many different levels of computational problem solving.

I have actively recommended this course to all of my friends. Please keep this course available to students! Especially ones (like myself) outside of the Computer Science degree.
A comprehensive and fun introduction to computing. i’d never done anything with computers before starting and i could mostly keep up with my classmates that had previous experience and were taking other computing classes. the tutors were good at explaining. … very interesting assignments. overall an interesting, fun, challenging (in a good way) course.

We also conducted an unofficial anonymous survey with a few more detailed questions, here is what we heard:

Briefly remind us why you wanted to take Art of Computing

I'd never done any computing before but was interested as I use computers so often and am probably just going to use them more and more throughout my degree and career.

I wanted to obtain some measure of literacy in the field of computing and computational problem solving. As an Arts/Law student very few opportunities are available.

I thought it would be a more relevant course to take, rather than the discovering engineering course, which was my other option.

Did you learn what you expected to learn?

YES! And more. The syllabus was great.

I didn't know what to expect but I learnt a lot. I particularly enjoyed learning about computational thinking and applying that to other disciplines.

I learned more than I expected to learn. This was a really great class.

What advice would you give to a future student of Art of Computing (or yourself 3 months ago)?

Don't underestimate the value of the course, simply because it starts with a visual programming language - you will learn a lot of advanced content.

Keep asking questions until you understand, even if it feels like you're repeating yourself.

Do you think what you learned in Art of Computing will help your in the future (in ANU and beyond), if so, how?

Yes - I think having some experience with such a wide range of algorithms and applications of computer science, and well as knowing more about circuits and binary, will enable me to learn more about these areas at a faster pace than if they were new concepts.

Absolutely. It has given me some measure of functional literacy of computational methods and systems.

I think it's taught me a different way of thinking through problems and given me a deeper appreciation to the complexity of computers and programs I use everyday.

Would you now consider taking another course in computer science? If so, do you know which ones?

I'm planning on doing a degree in computer science, with a focus on artificial intelligence.

Probably not right now but that's more to do with wanting to other things more, I'm not opposed to computing, the craft of computing looks interesting.

This class was incredible - I very much hope it remains available for students outside of the CECS world.

Thank you for running this course, I feel very lucky to have had this opportunity

Admin on The Art of Computing

Course Mechanics -- Important

Course schedule

Course staff and contact

Assessment scheme and policy

Communication and information dissemination

Notes

Grading Scheme

Grading breakdown

Assignments

Weekly exercise problems

Exam

Policy

Late assignment submissions: 5% penalty at 24-hour cut-off

Collaboration policy

2017 Class Schedule

Part I – Introduction to Programming

Week 1 (20-24 Feb)

Week 2 (27 Feb - 3 Mar)

Week 3 (6-10 Mar)

Week 4 (14-17 Mar)

Part II – Computational Thinking

Week 5 (20-24 Mar)

Week 6 (27-31 Mar)

Two Week Teaching Break (3 - 17 Apr)

Week 7 (18 - 21 Apr)

Week 8 (24-28 Apr)

Week 9 (1 - 5 May)

Part III – Computing in the world

Week 10 (8 - 12 May)

Week 11 (15 - 19 May)

Week 12 (22 - 26 May)

Contact Information

Course website (here)

Course Wattle Site and Contact

Lecturers

Tutors / Teaching Assistants

Student Comments From the 2016 COMP1030 Class

What were the most notable strengths of the course?

What suggestions for improvement would you like to make?

Assignment Submission Instructions

Assignment due

Submission procedure

Student Comments From the 2015 Class

What were the most notable strengths of the course?

Briefly remind us why you wanted to take Art of Computing

Did you learn what you expected to learn?

What advice would you give to a future student of Art of Computing (or yourself 3 months ago)?

Do you think what you learned in Art of Computing will help your in the future (in ANU and beyond), if so, how?

Would you now consider taking another course in computer science? If so, do you know which ones?

Any other thoughts you’d like to share about this class?