Notice for EIE2108 (+EIE2106) FIMT students



LAST UPDATED TIME: Nov 11, 10:00:00 HKT 2021



What's new:

 

Notes

Textbook & References

Tutorial

Quiz result

Lab material

Useful info

Supplementary materials

Links

Self-learning

Q and A

Please visit this homepage frequently to update your information.

·        Weighting of different components:

o   Exam: 0%

o   Continuous Assessment.: 100%:

§  lab activities: 24%

§  projects: 16%

§  test: 40%

§  quizzes and assignments: 20%


 

·        The solution of the mock test paper is here for your reference.    (2021/11/10)

·        A python code example for computing eigenvalues is here.   (2021/11/10)

·        A mock test paper is here for your reference.    (2021/11/3)

·        Tutorial 4 & 5 question sets and their solution are uploaded.    (2021/11/1)

·        Tutorial 3 question set solution is uploaded.    (2021/10/28)

·        FAQ for lab activities was updated. Extra note for lab activity 2 is added.  (2021/10/23)

·        Links for submitting reports, codes and logbook are now available in Blackboard.  (2021/10/11)

·        A wrong version of image file ‘SImg8x8-bvqc-R.png’ was included in http://www.eie.polyu.edu.hk/~enyhchan/FIMT-yr21-task3-dataset.zip by mistake. The zip file is now updated to include the correct version. You can download it again to get the simulation result of image ‘SImg8x8.png’ as a reference to verify your code for the lab project. You can also download the updated image file directly here.  (2021/10/11)

·        Slides for Matplotlib is updated. You can download the updated version here .  (2021/10/4)

·        An analysis on your quiz 1 is uploaded.  (2021/9/30)

·        Tutorial 2 question set solution is uploaded.    (2021/9/30)

·        Details of the lab activities and the project are available here. A FAQ page is constructed for providing you guidelines, hints, reference, test data etc. You can access it via this link.  (2021/9/25)  FAQ is updated (9/26)

·        Tutorial 2 question set solution for Q1 & Q2 is here.    (2021/9/23)

·        Tutorial 1 question set solution is uploaded.    (2021/9/18)

·        Tutorial 2 question set is uploaded.    (2021/9/15)

·        Tutorial 1 question set is uploaded.    (2021/9/8)


 

Tentative schedule is as follows:

Tentative schedule   



Notes

!! My ppt version is subject to change as I may update it for better presentation.
!! You may download the newest version of handouts here.

  • Matrix theory                                              [1in1 version]

o    A python code example for computing eigenvalues is here.   (2021/11/10)

  • Calculus                                                        [1in1 version]
  • Complex number                                       [1in1 version]

·         Python programming                               [1in1 version]

o     Slides for Matplotlib is updated. You can download it here.   (2021/10/4)

  • Python programming - tasks                   [1in1 version]
  • Artificial intelligence                                 [1in1 version]
  • Digital rights management                      [1in1 version]


Textbook and references:
 

·         Python Tutorial available at  https://www.w3schools.com/python/default.asp

·         S. Nagar, Introduction to Python for Engineers and Scientists, Cambridge University Press 2014.: Open Source Solutions for Numerical Computation, Apress, 2018 (A link  for downloading the e-version is here)

·         F. Faisal, S.J. Russell and P. Norvig, Artificial Intelligence A Modern Approach (4th Edition), Pearson, 2021 (A link  for downloading the e-version is here)



Tutorial arrangement

·        There is no tutorial session in week 1. 

Schedule: 

Week

Venue

Time

2-13

FJ304

Thu, 12:30pm-1:20pm

 



Tutorial problems:

 (Note: Tutorial 1 means it is the 1st tutorial question set in a sequence of question sets. It does not imply that it has to be discussed in tutorial session 1.) 



Revision guidelines:

  • Do revision based on the tutorial question sets, quizzes, exercises and lab tasks.


Quiz and test results:

There will be quizzes or classworks in weeks 3 to 13.

·        The exact time and date of a quiz will be confirmed 1 week in advance.

·        Total ceiling is 20% 

 You can always seek for help from me.

·         Quiz 1 performance :  (2021/9/30)

You can get the feedback from blackboard and use your score to locate your position in the class. Full mark is 10. The mean and the standard deviation are, respectively, 6.93 and 2.08.

·         Quiz 2 performance :  (2021/10/7)

You can get the feedback from blackboard and use your score to locate your position in the class. Full mark is 10. The mean and the standard deviation are, respectively, 8.75 and 1.82.



Laboratory materials:

  • Lab schedule:  (To be confirmed)

Group

Group A

Group B

Date

Tue, weeks 8, (9) 10 & 11

Wed, weeks 8, (9) 10  & 11

Time

8:30 am - 11:20 am

3:30 pm - 6:30 pm

Venue

CF504+CD514 for week 8

CF505+CD514 for week 10,11

CF502/CF503/CF504

We will conduct a lab session in week 9 instead of week 11 if we can find a room for the Tuesday group in week 9. That can leave you more time to handle deadlines of other subjects in the end of the semester.

The complication is due to the fact that the original reserved venue CF105 is now under renovation. It can’t be completed in time due to some unforeseen circumstances, so we have to find alternatives.

  • Lab activities:
    • Details of the ab assignments (including the project)  are available here.  (2021/9/25)
    • 5 datasets for task 2 are here. Use data set No. n in your test, where n = 1 + ((sum of all digits of your student numbers) mod 5). For example, if your student number is 19435207, then use data set 2 (because 1 + ((1+9+4+3+5+2+0+7) mod 5) = 2).
    • A dataset for you to verify your code for realizing task 3 is available here.  (2021/9/26)

·         FAQ for the lab activities/project of 2021 is here.   (2021/9/25)



Some useful information:

 

·        Cheat sheets for python programming are available in https://hakin9.org/wp-content/uploads/2020/02/beginnersPythonCheatSheet.pdf   or  https://www.pythoncheatsheet.org/

·        Cheat sheets for mathematics  are available in  https://doubleroot.in/cheat-sheets/

Before you use them, make sure that you know how to use them. Somebody else's medicine could be poison to you. 



Useful links:

·         A good website for you to learn Python from ground 0:   https://www.w3schools.com/python/

·         A place where you can get an easy-to-start Python distribution:     https://www.anaconda.com/products/individual  (Look for Anaconda Installers)

Its user guide is available in https://docs.anaconda.com/anaconda/user-guide/

·         Door to Matplotlib: https://matplotlib.org/3.2.1/contents.html

·         Door to Numpy: https://numpy.org/

Some clips available in Youtube

·         How to install Anaconda Python, Jupyter Notebook And Spyder on Windows 10  :  https://www.youtube.com/watch?v=5mDYijMfSzs  (It shows you how to download and install Anaconda and provides you some information about Jupitor notebook + Spyder.)

·         Introduction to the Spyder IDE for Python : https://www.youtube.com/watch?v=zYNRqVimU3Q

·         Complete Python NumPy Tutorial (Creating Arrays, Indexing, Math, Statistics, Reshaping) https://www.youtube.com/watch?v=GB9ByFAIAH4

    • @1:35: It explains why processing Numpy array is much faster than processing lists.
    • It’s well organized with a detailed video timeline.

 

Software:

·         Download anaconda from https://www.anaconda.com/products/individual  (Look for Anaconda Installers) and install it in your computer. We will use it to do tutorial and lab activities in class. Get it ready before week 3.

·         Anaconda is bundled with some commonly used packages such as Numpy and MatPlotlib. You don’t need to separately install them. After installing Anaconda, you only need to import them to your program when using them.

·         Anaconda is bundled with some development tools such as Spyder. Spyder is a useful integrated development environment (IDE) for you to develop Python code. We will use it in the class.

·         You need them to do assignments and laboratory activities, so better get familiar with them as soon as possible.