ternikov / hse

description
Course outline and prerequisites

Preface

Information Management course (Fall 2020) for 3rd-year and 4th-year students at HSE

Course format: Blended

Education technologies: Learning-by-doing and Flipped-Classroom

Overview: During this practically oriented data analysis module students will learn how computer programs are used for running predictive models and analytics. The main principal is to explore existing data to build new knowledge, forecast future behavior, anticipate outcomes and trends. Explore theory and practice, and work with tools like Python to solve advanced data science problems in management sphere.

Each Seminar's structure (except Test day):

1. Answering questions about Self-study content
2. Additional (basic and intermediate) hints for Python programming
3. Discussion of an applied tasks (intermediate and advanced) from real sector Data Analytics and interview questions

Online communication: only provided via Slack conference (sign-in with your @edu.hse.ru). Some important info will be duplicated in LMS and send on your group e-mails.

Submission platforms: LMS; Stepik; GitHub Classroom

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Books

1. [PIP] Parker, J.R. (2016). Python: An Introduction to Programming, Mercury Learning & Information (Available from HSE ProQuest Ebook Central).
2. [PDSH] Vanderplas, J.T. (2016). Python data science handbook: Essential tools for working with data. Sebastopol, CA: O’Reilly Media, Inc. (Available from HSE EBSCO Discovery Service).
3. [PPD] Mueller, J.P. (2018). Beginning Programming with Python for Dummies, John Wiley & Sons, Incorporated (Available from HSE ProQuest Ebook Central).
4. [PDA] Cuesta, H. (2016). Practical Data Analysis, Packt Publishing, Limited (Available from HSE ProQuest Ebook Central). {% endhint %}

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Software (Python 3 IDE)

• Recommended:
  • Jupyter Notebook [installed with Anaconda]: for in-class activities
  • Spyder [installed with Anaconda]: for MOOC and assignments
• Optional:
  • Google Colab [online]: sign-in with @gmail.com
  • Repl.it [online]: sign-in with your @edu.hse.ru
  • PyCharm [offline] {% endhint %}

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Recommended Self-study material

• General Questions and Answers about Code
  • **** ****StackOverflow
• Lectures & Exercises
  • MOOC [obligatory]
  • Introduction to Python (JetBrains)
  • Geo-Python (University of Helsinki)
  • Data Science For All (Cornell University and Berkeley University)
  • Automate the Boring Stuff with Python
• Practice
  • CheckIO
  • Adaptive Python
  • A gallery of interesting Jupyter Notebooks
  • Python Exercises
  • Practice Python
• Advanced
  • LeetCode (algorithms)
  • https://mlcourse.ai/ (Machine Learning)
  • Machine Learning and Data Science Applications in Industry {% endhint %}

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