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ITEC3040: Introduction to Data Analytics Winter 2026/2027 (4pages)

exam bundles Aug 25, 2025
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Course Instructor: • Xiaofeng Zhou • Email: [email protected] ∗ It is preferable that you use your York University email account, and include ‘ITEC3040 M’ on the subject line to minimize the risk that your email ends up in SPAM folder. Please identify yourself with you full name and student ID at end of the email. ∗ Responses to student emails will be provided within 24-48 hours from Monday to Friday. Please wait 48 hours before sending an identical email to the course director. Normally, there will be no email response on the weekends and holidays. If you are experiencing an emergency, please include ’URGENT’ in the subject line of your email. Course Description: This course offers an introduction to the field of data analytics with an emphasis on techniques relevant to managing modern organizations. Topics on descriptive, predictive and prescriptive analytics are discussed. Topics to be covered include statistical methods, data mining techniques, forecasting, risk analysis, linear and integer optimization, as well as text and web mining, decision analysis techniques and big data considerations. Course Webpage: eClass Student need Passport York to login. Course syllabus, announcement and important notice will be posted there. Please check the eClass regularly throughout the term to make sure that you are up to date on due dates and other important information. Times and Locations: Please note that this is an in-person course. • Lecture time: Monday 7:00pm – 10:00pm • Location: DB 0006 Textbook & Reference: • Textbook: Data Mining - Concepts and Techniques Author: Jiawei Han, Micheline Kamber and Jian Pei Publisher: Morgan Kaufmann 1 This study source was downloaded by 100000861878070 from CourseHero.com on 03-12-2026 12:07:46 GMT -05:00 https://www.coursehero.com/file/170465637/ITEC3040-2026-Winter-Syllabuspdf/ • Reference: Data Mining, The Textbook Author: Charu C. Aggarwal Publisher: Springer • Reference: Data Mining – Practical Machine Learning Tools and Techniques Author: Ian H. Witten, Eibe Frank and Mark A. Hall Publisher: Morgan Kaufmann Course Evaluation: • Two individual assignments: 20% • Group Project: 20% Due date: Apr.11, 2026, Please note this is the last date to submit the term work. • Midterm exam: 20?te: Feb.28, 2026 • Final exam: 40?te: TBA Assignment/Project/Exam Policy: • No late assignment or project report will be accepted. If you miss assignment, or project for medical reason, you must inform me within one week from the due date, then the weight will be added to the weight of the final exam. • Midterm No make-up exam will be provided. If you miss the exam for medical reason, you must inform me within one week from the quiz/exam date, then the weight will be added to the weight of the final exam. • Final Exam: No make-up exam will be provided. The final exam is held during the University examination period. The date of the final exam is not known until the official University examination schedule is published. It is your responsibility to be present at the exam. If you cannot take the final exam, you must notify me in advance and you have to apply for deferred final examination within ONE week from the scheduled exam date. The deferred standing application must be submmitted to ITEC at [email protected]. • Deferred Standing (Final Exams and Project): How to apply?


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ITEC3040: Introduction to Data Analytics Winter 2026/2027 (4pages)

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