Academy of Technical and
Art Applied Studies Belgrade

Data analysis Course code: OI0031 | 6 ECTS credits

Basic information
Level of Studies:
Year of Study: 3
Semester: 6
Requirements:
Goal:
Outcome:
Contents of the course
Theoretical instruction:
Practical instruction (Problem solving sessions/Lab work/Practical training):
Textbooks and References
  1. Sinan Ozdemir,Principles of Data Science, Packt Publishing Ltd, Birminghem, 2016.
  2. Joel Grus, Data Science from Scratch: First Principles with Python, 2nd Edition, O’Relly, 2019.
  3. Wes McKinney, Python for Data Analysis, O'Reilly Media", 2012.
  4. Mladen Varga, Upravljanje podacima, Element, 2012.
  5. Upom Malik , Matt Goldwasser, Benjamin Johnston, SQL za analizu podataka, Kompjuter biblioteka, 2019.
  6. Milan Galagoza, Marketing i menadžment istraživanja, MM Colege, 2005.
  7. Dimić, G., Pecić, Lj., Analiza podataka – priručnik za laboratorijske vežbe.
Number of active classes (weekly)
Lectures: 3
Practical classes: 0
Other types of classes: 2
Grading (maximum number of points: 100)
Pre-exam obligations
Points
activities during lectures
10
activities on practial excersises
10
seminary work
30
colloquium
20
Final exam
Points
Written exam
30
Oral exam
0