Introduction to programming in Python
Informacje ogólne
Kod przedmiotu: | 2400-ZEWW871 |
Kod Erasmus / ISCED: | (brak danych) / (brak danych) |
Nazwa przedmiotu: | Introduction to programming in Python |
Jednostka: | Wydział Nauk Ekonomicznych |
Grupy: |
Przedmioty kierunkowe dla Data Science Przedmioty kierunkowe do wyboru - studia II stopnia EM - grupa 1 (3*30h) Przedmioty kierunkowe do wyboru - studia II stopnia IE - grupa 1 (6*30h) Przedmioty wyboru kierunkowego dla studiów licencjackich EM Przedmioty wyboru kierunkowego dla studiów licencjackich IE Przedmioty wyboru kierunkowego dla studiów licencjackich MSEM |
Punkty ECTS i inne: |
(brak)
|
Język prowadzenia: | angielski |
Rodzaj przedmiotu: | nieobowiązkowe |
Skrócony opis: |
This course is dedicated to Python, the programming language most commonly appearing in Google search queries. The course begins from scratch; hence no prior knowledge of programming or computer science is required. At the beginning, the basics of programming and the Python language will be presented, followed by the most useful libraries and solutions for the work of an analyst / economist. The aim of the course is to prepare the participants so that they can continue to expand their knowledge on their own or in more advanced data-science courses. |
Pełny opis: |
• Fundaments of Python, code editors, programming environment, code documentation • Data types, lists, tuples, dictionaries • Code structures (if/else, iterate, comprehensions) • Functions • NumPy: matrices and linear algebra • Data manipulation with Pandas • Data visualization with Matplotlib and Seaborn • Importing data: CSV, Excel, JSON, txt • Web-scraping with requests and Beatifulsoup • Generators, iterators, collections, trees • Objects and classes |
Literatura: |
Bill Lubanovic, B. (2019), Introducing Python, 2nd Edition, O'Reilly VanderPlas, J. (2016), Python Data Science Handbook: Essential Tools for Working with Data, O’Reilly Sweigart, A. (2019), “Automate the Boring Stuff with Python: Practical Programming for Total Beginners”, 2nd Edition, No Starch Press Shaw, Z. (2016), “Learn Python 3 the Hard Way”, Addison-Wesley Professional |
Efekty uczenia się: |
KNOWLEDGE • The student is able to explain the difference between an integrated development environment and a text editor • The student is aware of the existence of various data structures and knows which one is appropriate to solve particular problems • The student is familiar with the notions of functions and classes and knows that they are not limited to a specific language. • The student knows the purpose of basic libraries of the Python language and how to search for libraries needed for specific applications • The student knows how data on the internet is structured, what the Application Programming Interface is and what its uses are • The student identifies common data formats and know which tool to use to load them • The student knows where to look for information concerning programming SKILLS • The student is able to configure a virtual environment and select a tool to write code • The student is able to collect and analyse data from the Internet and use in his/her bachelor's or master's thesis. • The student is able to prepare a simple application using Internet sources • The student is able to write code that solves a problem in an efficient way • The student is able to search for solutions to problems and adapt the solutions found SOCIAL COMPETENCES • The student understands that both own work and constant extension of one's knowledge in communication with others is necessary to achieve success in prgramming • The student realizes that probably the solution to the problem he is facing has already been found and it is necessary to take advantage of others' experience |
Metody i kryteria oceniania: |
The requirements are: 1) solving weekly problem sets that test basic knowledge and skills. 2) preparing the final project. Passing of both parts is required to pass the course. If the course is passed, the final grade depends only on the final project. |
Właścicielem praw autorskich jest Uniwersytet Warszawski, Wydział Nauk Ekonomicznych.