Social Media and Text Analytics 2401-CS-MF-SMaTA-s2

(in Polish) Total student workload Contact hours with teacher: - participation in laboratory - 30 hrs Self-study hours: - preparation for lectures - 10 hrs - preparation for test/ examination- 30 hrs Altogether: 70 hrs

(in Polish) W1: The student knows the basic methods used in NPL W2: The student knows the areas of application of text processing algorithms W3: The student knows the criteria for selecting text analysis methods W4: The student knows the text analysis algorithms (text categorization, clustering, topic modeling) W5: The student identifies social media as source of text data

(in Polish) U1: The student is able to use basic text processing tools U2: The student is able to write a simple program using NLP algorithms U3: The student is able to choose the appropriate algorithm to solve a given problem

(in Polish) K1: The student is able to communicate the effects of text processing algorithms K2: The student is able to argue and interpret the results of the text processing algorithm.

(in Polish) 1. Observation teaching methods: - display 2. Expository teaching methods - participatory lecture - problem-based lecture 3. Exploratory teaching methods - practical - brainstorming - laboratory - project work - presentation of a paper

(in Polish) 1. Python – basic (including basic libraries and packages: numpy, pandas, matplotlib, scikit-learn) 2. basic knowledge of machine learning 3. basic mathematic knowledge

Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system:

• Description of 2401-CS-MF-SMaTA-s2 in USOSweb