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Discipline Module 1 · Introduction to Data Science and Applications

Programming for Data Science

Workload
30h
Professor Profª. Drª. Janniele Soares PhD in Computer Science working in Data Science, optimization, and predictive analytics for complex problem-solving.
Syllabus

Development environments for Data Science. Basic concepts of the Python language: decision structures, loops, functions, file manipulation, and strings. Data structures: lists, dictionaries, tuples, and sets. Lambda functions, iterators, and generators. Introduction to libraries for Data Science: NumPy, SciPy, Pandas, DateTime, Matplotlib, and Seaborn.

Content
  • Development environments for Data Science
  • Basic concepts of the Python language: decision structures, loops, functions, file manipulation, and strings
  • Data structures: lists, dictionaries, tuples, and sets
  • Lambda functions, iterators, and generators
  • Introduction to libraries for Data Science: NumPy, SciPy, Pandas, DateTime, Matplotlib, and Seaborn
Core Bibliography
  • McKinney, Wes. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython. 3. ed. O'Reilly Media, Inc., 2023.
  • Severance, Charles Russell. Python for Everybody: Exploring Data in Python 3. Sue Blumenberg, Elliott Hauser, Aimee Andrion (eds.), 2016
Complementary Bibliography
  • Carvalho, André C. P. L. F. de; Menezes, Angelo G.; Bonidia, Robson P. Ciência de Dados - Fundamentos e Aplicações. ETC, 2024.
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