Development of Cross-platform Applications

Major: Computer Science (Design and programming of intelligent systems and devices)
Code of subject: 6.122.12.O.023
Credits: 4.00
Department: Computer-Aided Design
Lecturer: Professor of CAD Department, Sc.Dr., Professor Serhiy Shcherbovskykh
Semester: 4 семестр
Mode of study: денна
Мета вивчення дисципліни: The purpose of studying the discipline is to acquire the basic knowledge, skills and abilities necessary for solving applied problems of Data Science, Web and Software Development, as well as Office using Python.
Завдання: The study of the discipline involves the development of competencies in students: General competences: INT. Ability to solve complex specialized problems and practical problems in the field of computer science or in the learning process, which involves the application of theories and methods of information technology and is characterized by complexity and uncertainty of conditions. ЗК1. Ability to abstract thinking, analysis and synthesis. ЗК2. Ability to apply knowledge in practical situations. ЗК8. Ability to generate new ideas (creativity). ЗК10. Ability to be critical and self-critical. ЗК12. Ability to evaluate and ensure the quality of work performed. ЗК13. Ability to act on the basis of ethical considerations. ЗК14. Ability to exercise their rights and responsibilities as a member of society, to understand the values of civil (free democratic) society and the need for its sustainable development, the rule of law, human and civil rights and freedoms in Ukraine. Professional competences: ФК1. Ability to mathematically formulate and study continuous and discrete mathematical models, justify the choice of methods and approaches for solving theoretical and applied problems in the field of computer science, analysis and interpretation. ФК2. Ability to identify statistical regularities of non-deterministic phenomena, apply methods of computational intelligence, in particular statistical, neural network and fuzzy data processing, machine learning and genetic programming methods, etc.
Learning outcomes: ПР17. Perform parallel and distributed computing, apply numerical methods and algorithms for parallel structures, parallel programming languages in the development and operation of parallel and distributed software.
Required prior and related subjects: Prior academic subjects: 1. Operating systems 2. Web development and design technologies Related and subsequent subjects: 1. Business analysis and development of technological products 2. Design and development of mobile applications 3. Programming of intelligent embedded systems 4. Artificial intelligence systems
Summary of the subject: The course covers the basic issues of the Python language, creating cross-platform applications for solving applied problems in Data Science, Web and Software Development, as well as applications for creating Office documents
Опис: Topic 1: Python programming features General information. Data structures: lists, tuples, dictionaries and sets. Working tools of the language. Modules and data files. Errors and exceptions. Classes. Python templates, recipes and idioms. Topic 2. Data Science applications Scientific computing and data processing with NumPy, SciPy, and Pandas. Building graphs with Matplotlib. Setting up the graphical area, axes, graph lines and labels. Topic 3. Applications for Web and Software Development Performing general system service operations. Performing operations in the network. Parallel programming tools. Tools for developing, debugging and profiling code. Topic 4: Applications for Office Automated generation of documents in docx and xlsx format. Setting the parameters of the text output area. Setting fonts and paragraphs. Add text, tables, and figures.
Assessment methods and criteria: Formative control: laboratory work - written questionnaire; calculation (calculation and graphic) work - analysis for compliance with the task, independent performance. Summative control: testing in the VNS, oral examination.
Критерії оцінювання результатів навчання: Formative control: Laboratory work: 40 Individual work: 5 Summative control: Written component: 50 Oral component: 5 Total: 100
Порядок та критерії виставляння балів та оцінок: 100-88 points - ("excellent") is assigned for a high level of knowledge (some inaccuracies are allowed) of the educational material of the component contained in the main and additional recommended literature sources, the ability to analyse the phenomena studied in their interconnection and development, clearly, concisely, logically, consistently answer the questions posed, the ability to apply theoretical provisions in solving practical problems; 87-71 marks - ("good") is given for a generally correct understanding of the educational material of the component, including calculations, reasoned answers to the questions posed, which, however, contain certain (insignificant) shortcomings, for the ability to apply theoretical provisions in solving practical problems; 70 - 50 points - ("satisfactory") is assigned for poor knowledge of the educational material of the component, inaccurate or poorly reasoned answers, with a violation of the sequence of presentation, for poor application of theoretical provisions in solving practical problems; 49-26 points - ("not certified" with the possibility of retaking the semester control) is assigned for ignorance of a significant part of the educational material of the component, significant errors in answering questions, inability to apply theoretical provisions in solving practical problems; 25-00 points - ("unsatisfactory" with mandatory re-study) is assigned for ignorance of a significant part of the component's educational material, significant errors in answering questions, inability to navigate when solving practical problems, ignorance of the main fundamental provisions.
Recommended books: Al Sweigart. Automate the Boring Stuff with Python, 2nd Edition, 2020. https://automatetheboringstuff.com/
Уніфікований додаток: Lviv Polytechnic National University ensures the realization of the right of persons with disabilities to receive higher education. Inclusive educational services are provided by the Service of Accessibility to Learning Opportunities "Without Limitations", which aims to provide ongoing individual support for the educational process of students with disabilities and chronic diseases. An important tool for implementing the inclusive education policy at the University is the Programme of Professional Development of Academic Staff and Teaching and Support Staff in the Field of Social Inclusion and Inclusive Education. For more information, please contact us at: 2/4 Karpinskoho St., academic building, room. 112 E-mail: nolimits@lpnu.ua Websites: https://lpnu.ua/nolimits https://lpnu.ua/integration
Академічна доброчесність: The policy on academic integrity of the participants of the educational process is formed on the basis of compliance with the principles of academic integrity, taking into account the norms of the "Regulations on Academic Integrity at Lviv Polytechnic National University" (approved by the Academic Council of the University on 20.06.2017, Protocol No. 35).

Development of Cross-platform Applications (курсова робота)

Major: Computer Science (Design and programming of intelligent systems and devices)
Code of subject: 6.122.12.O.026
Credits: 2.00
Department: Computer-Aided Design
Lecturer: Professor of CAD Department, Sc.Dr., Professor Serhiy Shcherbovskykh
Semester: 4 семестр
Mode of study: денна
Мета вивчення дисципліни: The purpose of studying the discipline is to acquire the basic knowledge, skills and abilities necessary for solving applied problems of Data Science, Web and Software Development, as well as Office using Python.
Завдання: The study of the discipline involves the development of competencies in students: General competences: INT. Ability to solve complex specialized problems and practical problems in the field of computer science or in the learning process, which involves the application of theories and methods of information technology and is characterized by complexity and uncertainty of conditions. ЗК1. Ability to abstract thinking, analysis and synthesis. ЗК2. Ability to apply knowledge in practical situations. ЗК8. Ability to generate new ideas (creativity). ЗК10. Ability to be critical and self-critical. ЗК12. Ability to evaluate and ensure the quality of work performed. ЗК13. Ability to act on the basis of ethical considerations. ЗК14. Ability to exercise their rights and responsibilities as a member of society, to understand the values of civil (free democratic) society and the need for its sustainable development, the rule of law, human and civil rights and freedoms in Ukraine. Professional competences: ФК1. Ability to mathematically formulate and study continuous and discrete mathematical models, justify the choice of methods and approaches for solving theoretical and applied problems in the field of computer science, analysis and interpretation. ФК2. Ability to identify statistical regularities of non-deterministic phenomena, apply methods of computational intelligence, in particular statistical, neural network and fuzzy data processing, machine learning and genetic programming methods, etc.
Learning outcomes: ПР17. Perform parallel and distributed computing, apply numerical methods and algorithms for parallel structures, parallel programming languages in the development and operation of parallel and distributed software.
Required prior and related subjects: Prior academic subjects: 1. Operating systems 2. Web development and design technologies Related and subsequent subjects: 1. Business analysis and development of technological products 2. Design and development of mobile applications 3. Programming of intelligent embedded systems 4. Artificial intelligence systems
Summary of the subject: The course covers the basic issues of the Python language, creating cross-platform applications for solving applied problems in Data Science, Web and Software Development, as well as applications for creating Office documents
Опис: Topic 1: Python programming features General information. Data structures: lists, tuples, dictionaries and sets. Working tools of the language. Modules and data files. Errors and exceptions. Classes. Python templates, recipes and idioms. Topic 2. Data Science applications Scientific computing and data processing with NumPy, SciPy, and Pandas. Building graphs with Matplotlib. Setting up the graphical area, axes, graph lines and labels. Topic 3. Applications for Web and Software Development Performing general system service operations. Performing operations in the network. Parallel programming tools. Tools for developing, debugging and profiling code. Topic 4: Applications for Office Automated generation of documents in docx and xlsx format. Setting the parameters of the text output area. Setting fonts and paragraphs. Add text, tables, and figures.
Assessment methods and criteria: Formative control: laboratory work - written questionnaire; calculation (calculation and graphic) work - analysis for compliance with the task, independent performance. Summative control: testing in the VNS, oral examination.
Критерії оцінювання результатів навчання: Formative control: Laboratory work: 40 Individual work: 5 Summative control: Written component: 50 Oral component: 5 Total: 100
Порядок та критерії виставляння балів та оцінок: 100-88 points - ("excellent") is assigned for a high level of knowledge (some inaccuracies are allowed) of the educational material of the component contained in the main and additional recommended literature sources, the ability to analyse the phenomena studied in their interconnection and development, clearly, concisely, logically, consistently answer the questions posed, the ability to apply theoretical provisions in solving practical problems; 87-71 marks - ("good") is given for a generally correct understanding of the educational material of the component, including calculations, reasoned answers to the questions posed, which, however, contain certain (insignificant) shortcomings, for the ability to apply theoretical provisions in solving practical problems; 70 - 50 points - ("satisfactory") is assigned for poor knowledge of the educational material of the component, inaccurate or poorly reasoned answers, with a violation of the sequence of presentation, for poor application of theoretical provisions in solving practical problems; 49-26 points - ("not certified" with the possibility of retaking the semester control) is assigned for ignorance of a significant part of the educational material of the component, significant errors in answering questions, inability to apply theoretical provisions in solving practical problems; 25-00 points - ("unsatisfactory" with mandatory re-study) is assigned for ignorance of a significant part of the component's educational material, significant errors in answering questions, inability to navigate when solving practical problems, ignorance of the main fundamental provisions.
Recommended books: Al Sweigart. Automate the Boring Stuff with Python, 2nd Edition, 2020. https://automatetheboringstuff.com/
Уніфікований додаток: Lviv Polytechnic National University ensures the realization of the right of persons with disabilities to receive higher education. Inclusive educational services are provided by the Service of Accessibility to Learning Opportunities "Without Limitations", which aims to provide ongoing individual support for the educational process of students with disabilities and chronic diseases. An important tool for implementing the inclusive education policy at the University is the Programme of Professional Development of Academic Staff and Teaching and Support Staff in the Field of Social Inclusion and Inclusive Education. For more information, please contact us at: 2/4 Karpinskoho St., academic building, room. 112 E-mail: nolimits@lpnu.ua Websites: https://lpnu.ua/nolimits https://lpnu.ua/integration
Академічна доброчесність: The policy on academic integrity of the participants of the educational process is formed on the basis of compliance with the principles of academic integrity, taking into account the norms of the "Regulations on Academic Integrity at Lviv Polytechnic National University" (approved by the Academic Council of the University on 20.06.2017, Protocol No. 35).