Details - Tematika

Soft Skillls (GAINBAN-TRANSZIS-1)

Basic data

Name and type of the study programme

Computer Science Engineering, undergraduate program

Curriculum

2022

Classes / consultation hours

0 + 1 + 0 (L+S+Labs)

Credits

1 credits

Theory – Practice

Theory: 0%, Practice: 100%

Recommended semester

Semester 3

Study mode

full-time

Prerequisites

Evaluation type

Mid-term evaluation

Course category

Compulsory

Language

English

Instructors

Responsible instructor

Dr. Pap-Szigeti Róbert

Responsible department

Department of Information Technologies

Instructor(s)

Sári Bence

Checked by

Kovács Márk

Course objectives

Developing of knowledge, abilities, skills and competencies necessary for effective participation in the university education process and the successful practice of the profession.

Course content

Seminars

Weeks 1-2: Self-Awareness Develop a deeper understanding of personal strengths, weaknesses, and emotional intelligence. Weeks 3-5: Communication Techniques Learn effective verbal, non-verbal, and written communication techniques and active listening skills. Weeks 6-8: Teamwork and Basics of Project Management Enhance teamwork skills and understand the fundamentals of project management. Weeks 9-10: Job Search Methods Explore various job search strategies and techniques to find suitable employment opportunities. Week 11: Creating a Resume Learn how to create a professional and compelling resume that highlights your skills and experiences. Weeks 12-13: Preparing for a Job Interview Prepare for job interviews by practicing common questions, body language, and interview etiquette.

Acquired competences

Knowledge

–

Skills

- He/she cooperates with other computer science engineers, electrical engineers during team work, and with other experts during the analysis and solution of a problems.

Attitude

- He/she makes decisions with full respect for the law and ethical standards in decision-making situations requiring a complex approach. - He/she understands and embraces the ethical principles and legal implications of his/her profession. - He/she makes an effort to work efficiently and to high standards.

Autonomy and responsibilities

- He/she feels responsible for IT systems analysis, development and operation, both individually and as part of a team.

Additional professional competences

- Knowledge of the labour market consequences of structural changes of digitalisation and automation in production, supply chain, and in the organisation of production processes

Requirements, evaluation and grading

Mid-term study requirements

Active participation in lessons, solving of assigned tasks.

Generative AI usage

Use of GAI tools is fully permitted, provided their use is properly cited and does not compromise achieving the learning outcomes defined in the course description.

Study aids, laboratory background

Practical aids are uploaded to Teams.

Readings

Compulsory readings

[1] Barbara Oakley: Learning to Learn. Oakland University, Rochester, MI 48309. https://www.oakland.edu/Assets/upload/docs/UG-Education/Retention_Conference/Retention_Presenations/2014_Ret_Conf_Presentations/03_Learn_to_Learn.pdf