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30E03500 - Data Science for Business II, 25.02.2019-11.04.2019

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Syllabus

Week 1 - Predictive Modeling

  • Week 1 - Predictive Modeling

    Week 1 - Predictive Modeling

    • icon for activity Course introduction (2019) File PDF document

      Updated (fixed some errors)

    • icon for activity L1: Time series modelling & predictive analytics File PDF document
    • icon for activity T1: Predicting Brazil inflation rates Folder

      In this first tutorial, you will work with time series data and learn how to perform variable selection for predicting Brazil inflation rates. This folder contains the files for the  .ipynb file, the data and some images. Download from here and run the notebook on your own machine. Alternatively, we have made the files available in JupyterHub. 

    • icon for activity Assignment 1 – Predictive Modeling and a Dash of Time Series

      Deadline: Friday, March 8th, at noon

      The first assignment is meant to be a bridge to the concepts that you have already studied in Data Science for Business I as well as to prepare you for the concepts studied during Week 2.

      The assignment is worth 16 points. Late submissions will suffer a 20% penalty for being up to a day late and a 50% penalty for being more than a day late. Assignments more than 2 days late will not be graded.

      Please submit your solution as a single document. We recommend using a Jupyter notebook file, since it can nicely display the Python code you used along with its output, and exporting it to PDF (or HTML). Name your file studentNum-lastname-firstname-a1.pdf (or .html).


    • icon for activity Week 1 model solution File HTML document

      This is one possible way to solve the first assignment. If you have further questions, please don't hesitate to ask.

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Week 2 - Prescriptive Modeling►
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  • 30E03500 - Data Science for Business II, 25.02.2019-11.04.2019
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  • 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
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  • Schools
    • School of Arts, Design, and Architecture (ARTS)
    • School of Business (BIZ)
    • School of Chemical Engineering (CHEM)
    • –sGuides for students (CHEM)
    • – Instructions for report writing (CHEM)
    • School of Electrical Engineering (ELEC)
    • School of Engineering (ENG)
    • School of Science (SCI)
    • Language Centre
    • Open University
    • Library
    • Aalto university pedagogical training program
    • UNI (exams)
    • Sandbox
  • CORONAVIRUS INFO
    • Koronavirus - tietoa opiskelijalle
    • Coronavirus - information for students
    • Coronavirus - information för studerande
    • Corona help for teachers
  • Service Links
    • MyCourses
    • - Instructions for Teachers
    • - Teacher book your online session with a specialist
    • - Digital tools for teaching
    • - Personal data protection instructions for teachers
    • - Instructions for Students
    • - Workspace for thesis supervision
    • Sisu
    • Into portal for students
    • Courses.aalto.fi
    • Library Services
    • - Resourcesguides
    • - Imagoa / Open science and images
    • IT Services
    • Campus maps
    • - Search spaces and see opening hours
    • Restaurants in Otaniemi
    • ASU Aalto Student Union
    • Aalto Marketplace
  • ALLWELL?
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    • Support for Studying
    • Starting Point of Wellbeing
    • About AllWell? study well-being questionnaire
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