Title: Scientific Data Analysis Code: CSCI 2000U
Instructor: Jarek Szlichta, jaroslaw [dot] szlichta [at] uoit [dot] ca
Office hours: Thursdays 4pm-5pm
TAs: Spencer Bryson Lachlan Johnston; spencer.bryson [at] uoit [dot] net, lachlan.johnston [at] uoit [dot] net
TA Office Hours: 11am – 12pm on Tuesday in UA4029 (Spencer), 11am – 12pm on Thursday in UA4029 (Lachlan)
Description and Course Outline: see Blackboard
Marking Scheme: Tutorials and Project 30% (10% + 20%), Midterm : 20%, Final Exam : 40%, Presentation/Participation 10%.
Late project submissions: 50% of the mark (within the first week).
Policies: Refer to following link. Refer to UOIT Faculty of Science academic policies
Data Mining Concepts and Techniques: Jiawei Han and Micheline Kamber
Readings will posted on course website slides
Lecture Notes (always check newest version of the slides):
1. Introduction PDF
2. SQL PDF
3. Data Mining and Learning PDF
4. Apriori and Data Warehouses PDF
5. Python PDF
6. Spreadsheets PDF
7. Data Preprocessing PDF
8. Classification PDF
9. Data Visualization PDF
10. Graph Databases (Guilherme Damasio-IBM Centre for Advanced Studies) PDF
11. R PDF
12. Keyword Search over Big Data (Mehdi Kargar, University of Windsor) PDF
13. Classification and Clustering Analysis PDF
14. Data Cleaning and Query Optimization PDF
Tutorials start in the week of 20th of September.
Tutorial tasks will be posted on Blackboard
Midterm: Fundamentals 17th, Applications (SQL) 19th BRING YOUR LAPTOP TO THE MIDTERM!
Project I report (1-5) is due to 28th of October
Student Presentations: 22nd of November.
Project II report(6-10) is due to 9th of December midnight.
Exam: 16-Dec, 3:30 PM-6.30 PM, UA1350 BRING YOUR LAPTOP TO THE FINAL EXAM
Any student who misses an examination without a valid medical reason and documentation will receive zero for that examination/tutorial. Those with medical documentation will either be given a makeup exam/tutorial or will have the weight of the examination (final exam/midterm) added to the final exam.