IERG4330 / ESTR4316 Programming Big Data Systems / Spring 2022

Announcements


Course Description

This course aims to provide students an understanding in the operating principles and hands-on experience with mainstream Big Data Computing systems. Open-source platforms for Big Data processing and analytics would be discussed. Topics to be covered include:

  • Programming models and design patterns for mainstream Big Data computational frameworks ;
  • System Architecture and Resource Management for Data-center-scale Computing ;
  • System Architecture and Programming Interface of Distributed Big Data stores ;
  • High-level Big Data Query languages and their processing systems ;
  • Operational and Programming tools for different stages of the Big Data processing pipeline including data collection/ ingestion, serialization and migration, workflow coordination.

Prerequisite: This course contains substantial hands-on components which require solid background in programming and hands-on operating systems experience. IERG4300 or ESTR4300 or IEMS5709 is an official pre-requisite.

Please check Blackboard for important announcements, assignment submissions, grades, etc.

Course Assessment

The grade of IERG4330 student is based on the following components (tentative):

  • Homework & Programming Assignments (5 sets): 65%
  • Final Exam: 35%

The grade of ESTR4316 student is based on the following components (tentative):

  • Homework & Programming Assignments (5 sets): 60%
  • Project with Presentation: 10%
  • Final Exam: 30%

If face to face exam cannot be held, the course assessment scheme will be revised as follows:

For IERG4330:

  • Homework & Programming Assignments (5 sets): 75%
  • Q&A Assignment: 25%

For ESTR4316:

  • Homework & Programming Assignments (5 sets): 65%
  • Project with Presentation: 10%
  • Q&A Assignment: 25%

Student/Faculty Expectations on Teaching and Learning

http://mobitec.ie.cuhk.edu.hk/StaffStudentExpectations.pdf

Academic Honesty

You are expected to do your own work and acknowledge the use of anyone else’s words or ideas. You MUST put down in your submitted work the names of people with whom you have had discussions.

Refer to http://www.cuhk.edu.hk/policy/academichonesty for details

When scholastic dishonesty is suspected, the matter will be turned over to the University authority for action.

You MUST include the following signed statement in all of your submitted homework, project assignments and examinations. Submission without a signed statement will not be graded.

I declare that the assignment here submitted is original except for source material explicitly acknowledged, and that the same or related material has not been previously submitted for another course. I also acknowledge that I am aware of University policy and regulations on honesty in academic work, and of the disciplinary guidelines and procedures applicable to breaches of such policy and regulations, as contained in the website http://www.cuhk.edu.hk/policy/academichonesty/.

Academic Honesty Slides from Associate Dean of Faculty of Engineering

Previous Offerings


Lecture Time and Venue (IERG4330)

First 4 weeks (01/14, 01/21, 01/28, 02/11):

  • Fri 7:00PM - 10:00PM (Lady Shaw Bldg LT6)

From (02/16) onwards

  • Wed 7:00PM - 9:00PM (Lee Shau Kee Building LT2)
  • Fri 7:00PM - 9:00PM (Science Centre L3)

Lecture Time (ESTR4316)

  • Tue 5:30PM - 6:30PM

Tutorial Time and Venue

  • Mon 6:30PM - 7:15PM (Ho Sin-Hang Engineering Building 833)

Instructor

Email: wclau [at] ie.cuhk.edu.hk

Office hours: Thu 4:30 - 5:30PM (SHB 818)

Teaching Assistants

Da Sun Handason Tam

Email: tds019 [at] ie.cuhk.edu.hk

Office hours: Tue 2:00 - 3:00PM (SHB 803)