Search Engine Optimization
Course: «Applied Linguistics (Translation Editing and Expert Linguistic Analysis)»
Structural unit: Educational and Scientific Institute of Philology
Title
Search Engine Optimization
Code
ННД.12
Module type
Обов’язкова дисципліна для ОП
Educational cycle
Second
Year of study when the component is delivered
2023/2024
Semester/trimester when the component is delivered
2 Semester
Number of ECTS credits allocated
3
Learning outcomes
PLO 2. To demonstrate an adequate level of national and foreign languages ( English) mastery to perform written and spoken communication, namely in situations of professional and scientific communication; to present the results of their studies in the national and foreign languages (English).
PLO 3. To implement modern methods and techniques, namely informational, in order to perform a successful and effective professional activity and guarantee the quality of research in an applied linguistics field.
PLO 16. To use specialized conceptual knowledge in applied linguistics to solve complex tasks and issues, which requires updates and integration of knowledge, often under conditions of incomplete/lacking information and contradictory requirements.
PLO 19. To apply professional techniques and technologies of web page creation and web design, search engine optimization, copywriting, rewriting, and text compression.
Form of study
Full-time form
Prerequisites and co-requisites
To have the skills of programming in any programming tool environment (Python), to develop programs in high-level languages to implement the task.
Course content
The subject of the discipline is issues related to the methodology of using tools and methods of rational organization of a website. The knowledge and skills acquired in the course of the discipline, in particular those regarding the peculiarities of applying website optimization methods in the process of web design, support for making decisions on web design, organization of the analytical process, use of Python, HTML for website design, will be useful in the process of completing a master's thesis and in further professional activities.
Recommended or required reading and other learning resources/tools
1. Alberto Artasanchez. Prateek Joshi. Artificial Intelligence with Python: Your complete guide to building intelligent apps using Python 3.x. Packt Publishing; 2020. 620 p.
2. Hadelin de Ponteves. AI Crash Course: A fun and hands-on introduction to machine learning, reinforcement learning, deep learning, and artificial intelligence with Python. Packt Publishing; 2019. 534 p.
3. Introduction to Search Engine Optimization Getting Started With SEO to Achieve Business Goals. HubSpot; 2019. 40 p.
4. Eric Enge. The Art of SEO. – Cambridge O’Reilly "KM Академія", 2014, 688 p.
5. Artificial Intelligence and Data Mining Approaches in Security Frameworks. Edited by
Neeraj Bhargava. John Wiley & Sons, Inc.,. 2021. 320 p.
6. Artificial Intelligence and Intellectual Property. Edited by Jyh-An Lee, Oxford University Press. 2021. 441 p.
Planned learning activities and teaching methods
Forms of instruction: lectures, seminars, independent work, laboratory works.
Assessment methods and criteria
During the semester, the assessment is carried out in accordance with the types of work and the form of control, described in clause 7.1. The credit is awarded based on the results of the student's work during the semester and does not involve additional assessment activities. Students who score 60 points receive a "passed". Students who do not score 60 points receive a "failed".
Control forms: Answer at the seminar. Analysis report on scientific literature and lexicographic sources. Test with open answers. Laboratory work. Final test.
Language of instruction
Ukrainian, English
Lecturers
This discipline is taught by the following teachers
DEPARTMENT OF APPLIED INFORMATION SYSTEMS
Faculty of information Technology
Faculty of information Technology
Departments
The following departments are involved in teaching the above discipline
DEPARTMENT OF APPLIED INFORMATION SYSTEMS
Faculty of information Technology