Scientific Data Analysis

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

Required readings: 

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. Invited Lecture – Scotiabank (Yousef Akhavan) PDF PDF

5. Python PDF

6. Spreadsheets PDF

7. Data Preprocessing PDF

8. Data Visualization

9. R

10. Classification

11. Classification and Clustering Analysis

12. Unix & Shell


Tutorials:

Tutorials start in the week of 20th of September.

Tutorial tasks will be posted on Blackboard


Announcements:

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: TBD, copy your presentation to USB stick.

Project II report(6-10) is due to TBD midnight.

Exam: TBD 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.