Course: IT Workshop

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Course title IT Workshop
Course code KIV/IWO
Organizational form of instruction Tutorial
Level of course Bachelor
Year of study not specified
Semester Winter and summer
Number of ECTS credits 1
Language of instruction Czech
Status of course Optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Dostal Martin, Ing. Ph.D.
Course content
Students will be able to choose content from the menu with regard to their previous knowledge and current interests. The course will be taught in the form of practical workshops in partner IT companies and the topics will be regularly updated. Workshops on software development, eg: - introduction to the development of mobile devices, - introduction to Python programming, - advanced data analysis - Python / Java - choice of programming language, - advanced software development techniques in Java / Python / .NET ... Testing workshops eg: - web application testing - unit tests, selenium ..., - testing of mobile applications, - software testing - user, automatic, ... Workshops on various technological topics: - git, - docker, - message brokers - eg RabbitMQ, - no-sql database - Mongo, ElasticSearch, Redis, - cloud technologies - Google cloud, AWS, MS Azure

Learning activities and teaching methods
  • Practical training (number of hours) - 20 hours per semester
  • Preparation for laboratory testing; outcome analysis (1-8) - 6 hours per semester
prerequisite
Knowledge
The student has basic knowledge of computer operation.
The student knows the basic formats for storing textual information.
Skills
advanced pc operation
is able to work with MS Excel spreadsheet on advanced level
Competences
N/A
N/A
N/A
learning outcomes
Knowledge
When passing the course a student has: - knowledge of software development - eg control of modern IDE, - knowledge of software testing, - basic knowledge of CI / CD and DevOps, - technological knowledge of his choice - eg git, docker, RabbitMQ, no-sql database
Skills
practical ability to analyze data and draw conclusions
the student is able to preprocess, analyze and visualize text input data
Competences
N/A
N/A
teaching methods
Knowledge
Interactive lecture
Field trip
Practicum
Skills
Lecture
Lecture with visual aids
Practicum
Field trip
Competences
Lecture
Lecture with visual aids
Field trip
assessment methods
Knowledge
Skills demonstration during practicum
Skills
Skills demonstration during practicum
Competences
Skills demonstration during practicum
Recommended literature
  • Clinton Gormley, Zachary Tong. Elasticsearch: The Definitive Guide: A Distributed Real-Time Search and Analytics Engine. 2019. ISBN 1449358543.
  • Shannon Bradshaw , Eoin Brazil , et al. MongoDB: The Definitive Guide: Powerful and Scalable Data Storage. USA, 2019. ISBN 1491954469.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester