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01-Intro-UNIX/ (0, 2017-11-27)
01-Intro-UNIX/HW01/ (0, 2017-11-27)
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03-NumPy-and-Linear-Algebra/APD-Crime-Data_orig.ipynb (650999, 2017-11-27)
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03-NumPy-and-Linear-Algebra/Introduction_class.ipynb (307014, 2017-11-27)
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# Data Science Programming This material has been developed for the course MSA8010 in the [Master of Science in Analytics](http://robinson.gsu.edu/masters-programs/ms-in-analytics/) at the [J. Mack Robinson College of Business](http://robinson.gsu.edu) at [Georgia State University](http://gsu.edu). ## Topics and Schedule The schedule below applies to all sections for Fall 2017. Please, refer to this page for any changes. | # | Track I | Track II | Topic | Reading | |--|---------|------------|--------|----------| |1 | Mon, August 21 | We, August 23 | UNIX file system, command line tools, Jupyter notebook | [(online)](https://github.com/kingmolnar/DataScienceProgramming/blob/master/01-Intro-UNIX/Introduction_orig.ipynb) | |2 | Mon, August 28 | We, August 30 | Python programming language, Review | [(online)](02-Python/README.md) | |3 | Mon, Sept 11 | We, Sept 6 | Numpy and linear algebra operations | (online) | |4 | Mon, Sept 18 | We, Sept 13 | Pandas data frames, loading data, data-table manipulation | (online) | |5 | Mon, Sept 25 | We, Sept 20 | Operating with multiple tables, joining and reshaping | (online) | |6 | Mon, Oct 2 | We, Sept 27 | Descriptive statistics with Pandas data tables | (online) | |7 | Mon, Oct 9 | We, Oct 4 | Data visualization | (online) | |8 | Mon, Oct 16 | We, Oct 11 | Machine Learning I | ML Chapter 2, 8 | |9 | Mon, Oct 23 | We, Oct 18 | Machine Learning II | ML Chapter 3 | |10 | Mon, Oct 30 | We, Oct 25 | Information Based Learning | ML Chapter 4 | |11 | Mon, Nov 6 | We, Nov 1 | Similarity Based Learning | ML Chapter 5 | |12 | Mon, Nov 13 | We, Nov 8 | Probability Based Learning | ML Chapter 6 | |13 | Mon, Nov 27 | We, Nov 15 | Error Based Learning | ML Chapter 7 | |14 | Mon, Dec 4 | We, Nov 29 | Presentations | | | TBA | TBA | Final Exam | ## Text Book **Fundamentals of Machine Learning for Predictive Data Analytics** by John D. Kelleher, Brian Mac Namee, and Aoife D’Arcy [MIT-Press](https://mitpress.mit.edu/books/fundamentals-machine-learning-predictive-data-analytics) - Hardcover: ISBN 9780262029445, 624 pp., July 2015 - eBook: ISBN 9780262331722, 624 pp., July 2015

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