Introduction to Big Data Analytics, Spring 2019

This course offers an introduction to the principles and concepts in big data analytics (BDA), which is gaining more popularity in recent years.
The major topics covered in this course will include: data mining, distributed computing, and parallel programming.
The course is offered at undergraduate level.

Course Information

Instructor: Jenq-Haur Wang
E-mail: mailbox at the domain of csie within our university, and my username is jhwang
Office: R1534, Technology Building (ext. 4238)
Office Hours: Tue. and Fri. 9:10-12:00am
Class Hours: Wed. 9:10-10:00am, Thu. 10:10-12:00am, R1322, Technology Building
TA: Miss Chang (R1424, Technology Building)
E-mail: (TBA)
Prerequisite: data structures (and algorithms), database systems, discrete math (probability), operating systems, and working experience of high-level programming languages
Textbook: (Selected chapters)
- Jiawei Han, Micheline Kamber and Jian Pei, Data Mining: Concepts and Techniques, 3rd ed., Morgan Kaufmann Publishers, July 2011. ([DM3])
References:
- Tom White, Hadoop: The Definitive Guide, 4th ed., O'Reilly Media, 2015.
- Jimmy Lin and Chris Dyer, Data-Intensive Text Processing with MapReduce, Morgan & Claypool Publishers, 2010.
- Jure Leskovec, Anand Rajaraman, Jeffrey David Ullman, Mining of Massive Datasets, 2nd Edition, Cambridge University Press, November 2014.
- Holden Karau, Andy Konwinski, Patrick Wendell, Matei Zaharia, Learning Spark: Lightning-Fast Big Data Analysis, O'Reilly Media, January 2015.
- Others: online documents (Hadoop, Spark), tutorials, and selected academic papers.

Latest News

Sep. 9, 2019: [NOTE] Due to the regulation of Intellectual Property Office, the course materials have been moved to the iSchool platform in NTUT.
Jun. 20, 2019: [NOTE] The scores for all homeworks, exams, and projects have been announced. Please check if there's any questions as soon as possible before Jun. 21, 2019 (Fri.).
May 10, 2019: [NOTE] The current schedule for term project presentation has been announced. Please check if there's any questions.
May 8, 2019: [NOTE] HW#4 has been announced.
May 1, 2019: The current score has been posted. Please check if there's any questions as soon as possible.
Apr. 18, 2019: [NOTE] The midterm exam has been extended to May 2, 2019.
Apr. 16, 2019: [NOTE] The current score and the reference solutions to HW#1 & HW#2 have been posted. Please check if there's any questions or not.
Apr. 11, 2019: [NOTE] HW#3 has been announced.
Mar. 27, 2019: [NOTE] HW#2 has been announced.
Mar. 7, 2019: [NOTE] HW#1 has been announced.
Feb. 19, 2019: The homepage for Introduction to Big Data Analytics (Spring 2019) has been setup.

(Tentative) Schedule

* All slides can be downloaded at the iSchool plaform in NTUT.

Week	Date	Content	Reading	Note
1	Feb. 20 & 21, 2019	Course Overview Introduction to Big Data Analytics	DM3, Ch.1
2	Feb. 27 & 28, 2019	Ch.2, Getting to Know Your Data (2/28: 228 Peace Memorial Day)	DM3, Ch.2
3	Mar. 6 & 7, 2019	Ch.3, Data Preprocessing	DM3, Ch.3 (selected)	3/7: HW#1
4	Mar. 13 & 14, 2019	Ch.6, Frequent Pattern Mining	DM3, Ch.6
5	Mar. 20 & 21, 2019	Ch. 6: Frequent Pattern Mining (3/21: Leave for MOE Project) -- (TA) Term Project Proposal & Team Registration	DM3, Ch.6	Term Project Proposal 3/21 Due: HW#1
6	Mar. 27 & 28, 2019	Ch.8, Classification: Basic Concepts	DM3, Ch.8	HW#2
7	Apr. 3 & 4, 2019	(4/3: Compensation Leave for Sports Day 4/4: Children's Day)
8	Apr. 10 & 11, 2019	Ch.8, Classification: Basic Concepts		HW#3 Due: HW#2
9	Apr. 17 & 18, 2019	Ch.9, Classification: Advanced Methods Ch.10, Cluster Analysis: Basic Concepts and Methods	DM3, Ch.9 (selected sections) DM3, Ch.10
10	Apr. 24 & 25, 2019	Ch.10, Cluster Analysis		Due: HW#3
11	May 1 & 2, 2019	Distribtued Platforms: Hadoop, Spark Ref: Notes on installation, configuration, and management of Hadoop & Spark clusters (5/2:Midterm Exam)		Due: Proposal
12	May 8 & 9, 2019	Parallel Programming Paradigms & Concepts		HW#4: Hadoop & Spark
13	May 15 & 16, 2019	MapReduce Programming
14	May 22 & 23, 2019	Spark Programming Advanced Topics		Due: HW#4
15	May 29 & 30, 2019	Term Project Presentation (Week 1).
16	Jun. 5 & 6, 2019	Term Project Presentation (Week 2).
17	Jun. 12 & 13, 2019	Term Project Presentation (Week 3).
18	Jun. 19 & 20, 2019	(Leave for UC)

Programming Assignments and Projects

Please hand in your assignment before deadline according to the following instructions.

Submission Instructions

NOTE: Programs or projects in electronic files must be submitted directly to the TA online.

If you cannot successfully submit your work, please contact with the TA or the instructor.

Homeworks

There will be several written assignments and programming exercises that target at different data analysis tasks.

HW#1 : Ch.2-3 Data Preprocessing
Due: Mar. 21, 2019
HW#2 : Ch.6 Frequent Pattern Mining
Due: Apr. 10, 2019
HW#3 : Ch.8-9 Classification
Due: Apr. 24, 2019
HW#4 : MepReduce Programming
Due: May 22, 2019

Projects

Term Project: paper presentation or system demonstration

Item	Description	Time
Proposal	You are required to submit a proposal for term project one week after midterm exam.	May 2, 2019 (Thu.)
Topics	For paper presentations, the paper quality will greatly affect your score in term project. Please carefully select good papers to read.
Schedule	Please check the current schedule for term project presentation. (updated: Jun. 4, 2019) Due to our time limits, we have to start the term project presentation as early as May 29, 2019 (Wed.). * [NOTE] All presentations must be finished within the scheduled time slots, which will be the last 3 weeks in this semester. (excluding the last week) No other time slots will be avbailable.	May 29, 30, Jun. 5, 6, 12, 13, 2019
Report	Each team is required to upload the final report after finishing your presentation. The final report should contain at least the following: presentation slides (for all teams), and source code, installation/execution instructions, team members and task responsibility (for system projects)	Jun. 21, 2019 (Fri.)

Exams

Midterm Exam: Apr. 15-19, 2019
- Date: May 2 (Thu.)
- Time: 10:10-12:00am
- Location: R1322, Technology Building
- Range: Ch.1, 2, 3, 6, 8, 9, 10
Final Exam: Jun. 17-21, 2019
- Note: There will be no final exam in this course. Instead, you are required to finish a term project for system development or paper presentation.

Scores

Please check the homework submission site for more details.

Total Score (including all homeworks HW#1-HW#4, Midterm, and Term Project, as of Jun. 23, 2019)

E-mail: jhwang AT csie . ntut . edu . tw
Created: Feb. 19, 2019.
Last Updated: Jun. 23, 2019.