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Lecturer(s)
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Course content
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Lectures: 1. The basic characteristic of Python language, available implementations, IDEs. 2. Simple data types, basic control sequences. 3. Structured data - lists, tuples, dictionaries. 4. Input and Output, files and file-like objects. 5. Parsing of Markup languages and data exchange file types. 6. Generators. Own data types and special methods part I. 7. Iterators and decorators. Own data types and special methods II 8. Automated software testing, TDD and BDD. 9. Python standard library 10. Web applications in Python - Flask framework 11. Parallel and distributed programming in Python 12. Python for engineering computation - NumPy and SciPy 13. Python for data science - Pandas, SciKit Learn, Seaborn 14. Python for machine learning - TensorFlow, Keras Practice: 1. The first program in Python. Git and Gitlab for the version control and assignment upload. 2. Basic data types - algorithmic solution of given problem. 3. Data structures - simple data transformation task. 4. Working with strings - Caesar cipher 5. String and locales - split Czech text into the words. 6. An algorithmic solution of harder problems. 7. Working with data exchange file formats 8. Own data types and special methods 9. Command line interface 10. HTML parsing 11. Web service with REST API 12. Practical problem solution 13. Example of final test 14. Credit
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Learning activities and teaching methods
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Monological explanation (lecture, presentation,briefing)
- Class attendance
- 56 hours per semester
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Learning outcomes
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The aim of the course is to introduce the students to the Python programming language and its practical applications in engineering, data science, and machine learning.
Students will acquire the basic concepts of interpreted programming language Python. Students get knowledge how to use the Python to solve practical engineering and scientific problems.
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Prerequisites
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Unspecified
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Assessment methods and criteria
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Combined examination
Credit: create solutions for assignments from seminars in acceptable quality Exam: practical coding test + discussion about the solution
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Recommended literature
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David Beazley, Brian K. Jones. Python Cookbook, Third edition. O'Reilly Media; 3 edition (June 1, 2013), 2013. ISBN 978-1449340377.
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Mark Pilgrim. Ponořme se do Pythonu 3. CZ NIC, 2011.
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