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30E03500 - Data Science for Business II, 25.02.2019-11.04.2019
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School of Business
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30e03500 - da...
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week 3 - spor...
sports case p...
Syllabus
Sports case project files
betting_data.csv
149 bytes
BettingPortfolio_case.pdf
93KB
schedule-final.csv
16.7KB
schedule.csv
16.8KB
standings-final.csv
1KB
standings.csv
1.1KB
Download folder
◄ Sports analytics & sports case intro - Jirka Poropudas
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Syllabus
Course introduction (2019)
L1: Time series modelling & predictive analytics
T1: Predicting Brazil inflation rates
Assignment 1 – Predictive Modeling and a Dash of Time Series
Week 1 model solution
L2 - Introduction to Prescriptive Modeling
Example 1 Python implementation
Example 2 - Python implementation
Course mid-term feedback
Introduction to Gurobi
Example 3 - Python implementation
Sports analytics & sports case intro - Jirka Poropudas
Take home questionnaire 1
Take-home questionnaire 2
Finance project files
Take home questionnaire for Week 5 (Jyrki Koskinen)
Jyrki Koskinen - From Data to Business Opportunities
Project report template
Project presentation time selection
Finance project presentations
Sports case presentations
Finance case reports
Sports case reports
Assignment 1 Grades
Assignment 2 grades
Assignment 2 general feedback
Course grades
Project grades
Take home questionnaire 1 ►
30E03500 - Data Science for Business II, 25.02.2019-11.04.2019
Sections
General
Materials
JupyterHub
Gurobi
Week 1 - Predictive Modeling
Week 2 - Prescriptive Modeling
Week 3 - Sports Analytics
Week 4 - Prescriptive Analytics in Finance
Week 5 - From Data to Business Opportunities
Course Project
Course Grades
Home
betting_data.csv149 bytes
BettingPortfolio_case.pdf93KB