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Lecturer(s)
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Course content
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unspecified
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Learning activities and teaching methods
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unspecified
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| learning outcomes |
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| Knowledge |
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| The student can describe the principles of object-oriented programming in Python. |
| The student can describe the principles of object-oriented programming in Python. |
| The student can describe the primary functions of the Numpy, Matplotlib and Pandas libraries. |
| The student can describe the primary functions of the Numpy, Matplotlib and Pandas libraries. |
| The student can explain the term DevOps and its importance in software development. |
| The student can explain the term DevOps and its importance in software development. |
| The student can define and analyze static and dynamic code analysis methods and their importance for quality software development. |
| The student can define and analyze static and dynamic code analysis methods and their importance for quality software development. |
| The student can describe different approaches and techniques for testing software in Python. |
| The student can describe different approaches and techniques for testing software in Python. |
| The student can list methods and tools for generating and managing code documentation in Python. |
| The student can list methods and tools for generating and managing code documentation in Python. |
| The student knows the conventions of writing documentation strings in Python. |
| The student knows the conventions of writing documentation strings in Python. |
| Skills |
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| The student is able to design and implement complex software solutions using advanced features of Python and its libraries such as Numpy, Matplotlib and Pandas. |
| The student is able to design and implement complex software solutions using advanced features of Python and its libraries such as Numpy, Matplotlib and Pandas. |
| The student can create and implement automated processes within the GitLab environment that integrate the phases of software development, application and operation, in accordance with DevOps principles. |
| The student can create and implement automated processes within the GitLab environment that integrate the phases of software development, application and operation, in accordance with DevOps principles. |
| The student can perform static and dynamic code analysis, identify and solve problems, and optimize code to improve its quality and performance. |
| The student can perform static and dynamic code analysis, identify and solve problems, and optimize code to improve its quality and performance. |
| The student is able to create and maintain unittests for basic verification of the functionality and reliability of code written in the Python programming language. |
| The student is able to create and maintain unittests for basic verification of the functionality and reliability of code written in the Python programming language. |
| The student can generate automatic documentation of a software project from documentation strings written in Python. |
| The student can generate automatic documentation of a software project from documentation strings written in Python. |
| assessment methods |
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| Knowledge |
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| Analysis of works made by the student (Technical products) |
| Analysis of works made by the student (Technical products) |
| Written examination |
| Written examination |
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Recommended literature
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CHACON, Scott. Pro Git.. Praha, 2009. ISBN 978-80-904248-1-.
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KANER, Cem, Jack L FALK a Hung Quoc NGUYEN. Testing computer software. 2nd ed.. New York, 1999. ISBN 9780471358466.
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WYSOCKI, Robert K. Effective project management: traditional, agile, extreme.. Indianapolis, 2012. ISBN 9781118016190.
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ZELLE, J. M. Python programming: an introduction to computer science. Third edition.. Portland, Oregon: Franklin, Beedle & Associates,, 2016. ISBN 978-1590282755.
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