Data Mining (Lectures during COVID-19 Quarantine Days)

COMSATS University Islamabad, Vehari Campus

                               

COURSE HANDBOOK

1	Course Title					Data Mining
2	Course Code					CSC-479
3	Credit Hours					3
4	Semester					8th , SP-2020
5	Resource Person					Arslan Ali Raza
6	Supporting Team Members
7	Contact Hours (Theory)					3 hours per week
8	Contact Hours (Lab)
9	Office Hours					arslan@ciitvehari.edu.pk
10	Course Introduction
Data mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. Data Mining aims to build an understanding of the concepts and ideas explicitly involved in the extraction of user generated contents. The course is designed to emphasize the understandings and practical implementation of pattern discovery. In short, the course will provide students with a strong foundation of data mining and knowledge discovery.
11	Learning Objectives
This course is intended to give an overview of the Data Mining, Information Retrieval and Text Summarization where learning objectives are as follow: LO1.    To develop an understanding of Data Mining LO2.    To elaborate the major application areas of Data Mining LO3.    To understand impact of advancements in Data Mining on Market and organizations LO4.     To analyse and compare existing data mining systems and mechanisms  LO5.     To explore novel data mining systems for efficient data retrieval
12	Lecture/Lab Schedule
Weeks	Topic of Lecture						Topic that completed
Week 1	Data Mining History: Past, Present and Future Aspects of Data Mining						Data Mining History: Past, Present and Future Aspects of Data Mining
Week 2	Applications of Data Mining Quiz No 1						Applications of Data Mining Quiz No 1
Week 3	Why Data Mining; Importance and Significance Commercial and Scientific View Point of Data Mining						Why Data Mining; Importance and Significance Commercial and Scientific View Point of Data Mining
Week 4	Major issues in data mining Why is Data Noisy and Unclear?						Major issues in data mining Why is Data Noisy and Unclear?
Week 5-6	Noise Reduction and Data Preparation Quiz No 2						Noise Reduction and Data Preparation Quiz No 2
Week 7	Pre-processing Steps for cleaning desired text Data Mining System Architecture						Pre-processing Steps for cleaning desired text Data Mining System Architecture
Week 8	Data Understanding Data Mining Techniques						Data Understanding Data Mining Techniques
Week 9	Multidimensional measure of data quality Association Rules Mining						Multidimensional measure of data quality Association Rules Mining
Week 10	Supervised Techniques of Data Mining Semi and Unsupervised Techniques of Data Mining						Supervised Techniques of Data Mining Semi and Unsupervised Techniques of Data Mining
Week 11	Data Classification and Associated Aspects Existing Classification Techniques and Research Gaps						Data Classification and Associated Aspects Existing Classification Techniques and Research Gaps
Week 12	Role of Data warehousing in Data Mining  OLAP VS OLTP						Role of Data warehousing in Data Mining  OLAP VS OLTP
Week 13	Frequent Pattern Analysis in Data Mining Opinion Mining and Sentiment Analysis						Frequent Pattern Analysis in Data Mining Opinion Mining and Sentiment Analysis
Week 14	Challenges and Research Gaps of Opinion Mining Turning Data into Business Value						Challenges and Research Gaps of Opinion Mining Turning Data into Business Value
Week 15	Information Privacy and Data Mining Tools and Software used for Data Mining						Information Privacy and Data Mining Tools and Software used for Data Mining
Week 16	Python and Data Mining Toolkit Putting it all together; A review on Data Mining						Python and Data Mining Toolkit Putting it all together; A review on Data Mining
13	Text Book				1.    Data Mining: Concepts and Techniques         Book by Jiawei Han
14	Reference Books				2.    Data Mining: Practical Machine Learning Tools and       Techniques  Book by Eibe Frank and Ian H. Witten 3.    Introduction to Data Mining Book by Michael Steinbach, Pang-Ning Tan
15	Details of Teaching and Assessment
The learning hours for this module are made up of the teaching contact hours as well as the students' private study hours. Further details and timings will be notified later. Grades Letter Grade Credit Points Percentage Marks A ( Excellent) 4.0 90and above A- 3.7 85-89 B+ 3.3 80-84 B (Good) 3.0 75-79 B- 2.7 70-74 C+ 2.3 65-69 C (Average) 2.0 60-64 C- 1.7 55-59 D (Minimum passing) 1.3 50-54 F (Failing) 0.0 Less than 50 Type                                            Details: Teaching Contact Hours              2 Lectures/week (1.5 hours each) Instructors Office Hours              2 hours/week Lab Contact Hours                      1 Lab Session/week (3 hours) Details and timings for the assessment of this module are as follows: 6.1. Theory Part:     Exam (Weightage)                           Duration             Type                                 Sessional-I Exam (10%)                  1 hour                   Subjective + objective                                 Sessional-II Exam (15%)                  1.5 hour               Subjective + objective                                 Final Exam (50%)                             3 hours                Subjective + objective                                Quiz  (15%)                                      20 min each         Subjective +Objective type                                 Assignment (10%)                           Take home            Subjective type 6.2. Practical/Lab Part: Exam (Weightage)                       Duration             Type Sessional-I Exam (10%)               1.5 hour               Hands on + viva Sessional-II Exam (15%)              1.5 hour               Hands on + viva Final Exam (50%)                         3 hours                Hands on + viva Project(OR Lab Evaluation) (25%)                          Individual and group as per difficulty level The minimum pass marks for each course shall be 50%. Students obtaining less than 50% marks in any course shall be deemed to have failed in that course. The correspondence between letter grades, credit points, and percentage marks at CIIT shall be as follows:
			Assignment Format
·         Theory Assignments must be submitted in hard copy on A4 paper or handwritten as per instruction. ·         Lab Assignments will be marked in lab or submitted via canvas.
17		CIIT-LB Procedures for CSC102 module
a) Coursework/Assignment Submissions: Coursework is usually submitted electronically. When the work is required to be submitted in this way, you have until midnight on the advertised submission date to submit the work. Please note, you must submit the work electronically in .doc/.docx format (unless some other file format is specified). When group coursework is to be submitted electronically, a representative of each group (the group leader) should be chosen for submission. If there is any doubt, please contact the Course Organizer BEFORE the submission date. Every piece of written coursework must have a correctly completed front cover sheet which you must sign in order to declare that it is your own work. Paper submissions must be made in person to the specified person during office contact hours. Do not give coursework to any other member of staff as we will not accept responsibility for anything that is not submitted properly. Especially, do not push work under offices doors as it is quite likely to be picked up and disposed of by the cleaning staff. Students, who miss the coursework deadline because of extenuating circumstances, can still submit their work (subject to the approval of course organizer). In this case the submission will be logged as “Late Submission” and will automatically be penalized. b) Examinations: For the explanations, students will be assessed according to clear understanding of concepts and correct usage of technical information in their responses. For essays and assignments, the relevance of information and the coherence of the details would be assessed along with importance and credits for proper examples. For practical assignments, students will be rewarded according to the proper usage of features and tools regarding that assignment, extra credit will be given to students who show more technical learning. c) Penalties for Late Submission of Coursework If you fail to submit coursework on time you will be penalized on the following scale: 10% per day will be lost from your overall mark. (For purposes of calculating penalty – each period of up to 24 hours after the initial submission is counted as 1 day). However, this will be capped at 30% (3 days) maximum penalty. Normally you will not be allowed to submit after the cut-off date. Saturdays and Sundays count as periods late when calculating the penalty. d) Extenuating Circumstances Extenuating circumstances normally mean circumstances beyond your control (e.g. illness, death of a close relative etc). Losing memory sticks, computer problems or theft of laptops will not count since you should always have backup copies elsewhere; printer problems will also not count as you should allow enough time to get the printing done even if there are problems. Any such claim MUST be supported by documentary evidence e.g. an original medical certificate covering the date(s) in question, accompanied by an extenuating circumstances formal statement by the student. Any claim will not be considered, under any circumstances, without supporting documents. Such an authorized absence will allow you to have an experiment rescheduled or coursework submission date shifted by an appropriate amount. However, if the new submission date is likely to exceed the published coursework cut-off date then you may be asked to do a different piece of work to the other students on that course. Also, overall end-of-semester deadlines for marks cannot be exceeded. Each case will be looked at on its individual merits. Please note that it is your own responsibility to submit claims for extenuating circumstances and students with extenuating circumstances cannot be given extra marks. Marks will only be given for the work actually produced, not what might have been done if extenuating circumstances had not arisen.
19				Conduct
CIIT-LB has high expectations of student behaviour. It is expected that students will help to maintain a pleasant atmosphere suitable for serious study throughout their programme of study. Any behaviour that prevents other students from studying will result in disciplinary action by the University. Persistent offenders will be referred to concerned committee for further disciplinary action and possible deregistration. Two issues requiring particular attention are noise disruption and mobile phones. Students should not distract others by talking during taught classes (lectures, labs, tutorials, exercises classes, etc.). Students using the labs should be aware of others around them, and should keep any discussion to a reasonable level. Mobile phones should always be switched off during taught classes, in the Library, and in any tests or examinations. Any student whose mobile phone rings during a taught class or in the Library may be asked to leave. Any student whose mobile phone rings during a test or examination will be referred to concerned committee for disciplinary action. This may lead to a mark of zero being awarded for that particular assessment, and more serious penalties for a subsequent offence.
20	Attendance Policy
Every student must attend 80% of the lectures/seminars delivered in the course and 80% of the practical/laboratory work prescribed. The students falling short of required percentage of attendance of lectures/seminars/practical/laboratory work, etc., shall not be allowed to appear in the terminal examination of this course and shall be treated as having failed this course.
21	Plagiarism and Referencing
Plagiarism is the failure to credit the writings or ideas of another person that you have used in your own work. In such cases you are, deliberately or inadvertently, attempting to pass their work off as your own. Plagiarism is a serious offence, and can carry severe consequences, from failure of the module to deregistration from the course. You may also commit plagiarism by failing to reference your own work that you have already used in a previous essay, or by failing to credit the input of other students on group projects. It is your responsibility to ensure that you understand plagiarism and how to avoid it. The recommendations below can help you in avoiding plagiarism. ·         Be sure to record your sources when taking notes, and to cite these if you use ideas or, especially, quotations from the original source. Be particularly careful if you are cutting and pasting information between two documents, and ensure that references are not lost in the process. ·         Be sensible in referencing ideas – commonly held views that are generally accepted do not always require acknowledgment to particular sources. However, it is best to be safe to avoid plagiarism. ·         Be particularly careful with quotations and paraphrasing. ·         Be aware that technology is now available at CIIT-LB and elsewhere that can automatically detect plagiarism. ·         Ensure that all works used are referenced appropriately in the text of your work and fully credited in your bibliography. ·         If in doubt, ask for further guidance from your Course Organizer. The material that you submit for assessment, whether in an answer script in a written examination or as assessed coursework, must be your own unaided work. Cheating in written examinations and plagiarism in assessed coursework are examination offences. Plagiarism in assessed coursework - this is the use or presentation of the work of another person, including another student, as your own work (or as part of your own work) without acknowledging the source. Plagiarism therefore includes submitting the work of someone else as your own, and extensive copying from someone else's work in your own paper or report. Brief quotations from the published or unpublished work of other persons may be used, but must always be clearly indicated by being placed inside quotation marks, with the source indicated in some way, and the work listed in the bibliography at the end of your own piece of work. It can also be plagiarism to summarize another person's ideas or judgments without reference to the source. Copying material from web pages without acknowledgement is plagiarism. Copying programs (for example from the Internet) without explanation of where they are from or how much you have modified the programs is also plagiarism. Copying from another student (with or without their consent) is plagiarism and both parties will be subject to investigation and possible penalty. Do not copy and do not allow others to copy from you. When you are taking notes for a paper or piece of coursework, it is important to include all the sources you have used, and to indicate any quotations so that you can make the necessary references when you come to write the report/assignment/essay etc. "Unconscious plagiarism", including an un-attributed quotation because you did not identify quotations in your notes, is as much an examination offence as deliberate plagiarism, and will be dealt with in the same way as any other examination offence.

 Lectures Data Mining, CUI Vehari