HY 514 Περιβάλλοντα Επίλυσης Προβλημάτων για εφαρμογές στην Επιστήμη Δεδομένων (2017)

Problem Solving Environments and Applications in Data Science (Περιβάλλοντα Επίλυσης Προβλημάτων για εφαρμογές στην Επιστήμη Δεδομένων)  (fall)

The course introduces problem solving environments including Python, R, Julia, SaS, JMP, and excel and trains students to use them to apply least squares and regression techniques for big data, to solve nonlinear optimization problems with classical, stochastic, and genetic algorithms using well known libraries like qurobi library and Argonne Optimization Server, and data mining problems.

Το μάθημα εισάγει τα υπολογιστικά περιβάλλοντα Python, R, Julia, SaS, JMP, και Excel και τα εφαρμόζει για την επίλυση  προβλημάτων προσέγγισης δεδομένων, εξόρυξη δεδομένων, και μη- γραμμικών προβλημάτων βελτιστοποίησης. Ιδιαίτερα καλύπτει στοχαστικές μεθόδους για την επίλυση των παραπάνω προβλημάτων και αναγνωρισμένες βιβλιοθήκες και διαδικτυακές υπηρεσίες.

“A PSE is a computer system that provides all the computational facilities necessary to solve a target class of problems”

The course introduces problem solving environments including Python, R, Julia, SaS, JMP, and Excel and trains students to use them to apply least squares and regression techniques for big data, to solve nonlinear optimization problems with classical, stochastic, and genetic algorithms using well known libraries like qurobi library and Argonne Optimization Server, and data mining problems.

ΜΗΧ514 : Why? and What?

"Data Science" has emerged as an important source of insights that can benefit scientific, business, and even personal goals. The enthusiasm around that title may have become overdone -- for example, the Harvard Business Review described Data Scientist as the "sexiest job of the 21st century." According to The New York Times, data science “promises to revolutionize industries from business to government, health care to academia.” Based on the number of job openings, median base salary and career opportunities, Glassdoor has ranked data scientist as the “Best Job in America” for 2016.

Despite that hype, Data Science does represent the intersection of several important fields:
numerical analysis, probability and statistics, machine learning, programming, and computational science infrastructure (algorithms and PSEs).

In ECE514 will develope hands-on skills in several PSEs learning Data Science with case studies and your own datasets.

The background assumed in this course is covered in the ebook by E. Houstis "Εγχειρίδιο Αριθμητικών Μεθόδων για Επιστημονικές Εφαρμογές με την Χρήση MatLab και Python", notes in Data Science with R, and the book
PYTHON - Εισαγωγή στους υπολογιστές