How to prepare for the BI Master Program?
You have been accepted for the Business Intelligence (BI) Master Program or you continue your studies. The new term is coming and you want to prepare for it. Great! Below you can find some useful information and links.
First term
In the first term, you will learn how to use different programming environments. In order to prepare for the term, please get familiar with basic structures and comments of Matlab/Octave, Python and R. As a PWr student, you will get a free access to Matlab. Octave, Python and R are open source, so you can download them whenever you need (links below).
You do not need to be good at programming, but you will feel more comfortable knowing the basics. During the term you will have a lot of work, so get prepared in advance. Below you can find links to tutorials.
Downloads & tutorials
Matlab / Octave:
- Matlab Academic Licence (https://di.pwr.edu.pl/oprogramowanie/oprogramowanie-matlab; description in Polish)
- Octave downloads (https://www.gnu.org/software/octave/download) and packages (https://gnu-octave.github.io/packages)
- How to Write a MATLAB Program, a 14 minute video on the basics of Matlab (https://www.mathworks.com/videos/writing-a-matlab-program-69023.html)
- MATLAB Onramp, a 2h introductory tutorial on commonly used features and workflows (https://www.mathworks.com/learn/tutorials/matlab-onramp.html)
- Get Started with MATLAB, a collection of useful tutorials (https://www.mathworks.com/help/matlab/getting-started-with-matlab.html)
- Deep Learning Onramp, a 2h interactive introduction to practical deep learning methods (https://www.mathworks.com/learn/tutorials/deep-learning-onramp.html)
Python:
- Python download (https://www.python.org/downloads)
- 10 Python IDE & code editors (https://www.guru99.com/python-ide-code-editor.html)
- Anaconda (https://www.anaconda.com/products/individual)
- Introductory and Advanced Python Tutorials by learnpython.org (https://learnpython.org)
- Python Tutorial by pythontutorial.net (https://www.pythontutorial.net)
R:
- The Comprehensive R Archive Network downloads (CRAN; https://cloud.r-project.org)
- R studio - IDE for R (https://www.rstudio.com)
- Hands-On Programming with R by Garrett Grolemund (https://rstudio-education.github.io/hopr/index.html)
Bibliography
- Camm, J. D., Cochran, J. J, Fry, M. J., Ohlmann, J. W., Anderson, D. R., Sweeney, D. J., Williams, T. A. (2019) Business Analytics, Cengage
- Eaton, J.W., Bateman, D., Hauberg, S., Wehbring, R. (2021) GNU Octave Manual: Free Your Numbers
[HTML, PDF] - Ferrari, A., Russo, M. (2016) Introducing Microsoft Power BI, Microsoft Press [PDF]
- Gordon, S.I., Guilfoos, B. (2017) Introduction to Modeling and Simulation with MATLAB and Python, CRC Press
- Grolemund, G., Wickham. H. (2017) R for Data Science, O’Reilly [HTML]
- Gundersen, V.B. (2008) Mathesaurus, including the MATLAB/Octave-Python-R cheatsheet [HTML, PDF]
- Hiebeler, D. (2014) MATLAB/R Reference [HTML, PDF]
- Hiebeler, D. (2015) R and MATLAB, Chapman and Hall/CRC
- Sharda, R., Delen, D., Turban, E. (2020) Analytics, Data Science & Artificial Intelligence: Systems for decision support, Pearson
- VanderPlas, J. (2016) Python Data Science Handbook, O'Reilly [HTML]
- Vercellis, C. (2009) Business Intelligence: Data Mining and Optimization for Decision Making, Wiley
Second term
In the second term, you will continue to develop your analytic skills with the programming platforms you already know. However, some new management subjects are introduced. The course Project Management will begin with a repetition of basic notions from project management, after which you will learn about more advanced topics. During the lab classes you will work with Microsoft Project software, which you can download (https://di.pwr.edu.pl/oprogramowanie/oprogramowanie--microsoft) and install on your computers.
When preparing for the Predictive Analytics course have a look at R.J. Hyndman, G. Athanasopoulos (2021) Forecasting: principles and practice (3rd ed.), OTexts. The textbook and the accompanying R codes are (https://otexts.com/fpp3). For Python users the Python Read-Along "Forecasting: Principles and Practice" by Mike Richman will come in handy (https://nbviewer.org/github/zgana/fpp3-python-readalong/blob/master/Contents.ipynb).
During the second term you will choose a topic of your master thesis. If you have time, think about your interests and the area of research that is the most useful for you in the future. You will meet your potential supervisors during the BI Day in November - get prepared to make the decision easier!