Completion of multiple online courses (with certificates and badges) corresponding to min. 50 % of possible points.

Obligatory:

• DataCamp, online platform [online]. Dostupné z: https://www.datacamp.com/
• CS50, Harvard university, online course [online]. Dostupné z: https://cs50.harvard.edu/x/
• Project Management Institute [online]. Dostupné z: https://www.pmi.org/learning/ai-in-project-management

The main teaching methods include:

Guided self-study – working with online courses, tutorials, documentation, and other digital learning resources.

Hands-on learning – acquiring practical skills through direct work with IT tools and platforms.

Learning by doing – applying theoretical concepts to practical tasks, exercises, and real-world scenarios.

Project-based learning – completing individual or team-based projects that integrate knowledge and skills from different course modules.

Consultations and guided discussions – limited in-person meetings focused on discussing progress, addressing difficulties, sharing experience, and reflecting on the practical use of IT technologies.

Peer learning – sharing experiences, solutions, and examples of good practice with other students.

Presentations and demonstrations – presenting completed work.

Guided self-study and in-person meetings as announced.

1. Introduction

2. IT Orientation

3. Low Code/No Code

4. Databases and SQL

5. AI/ML

6. Tools for Project Managers

7. Deepening of Knowledge in Elective Modules

By the end of the course, students will be able to:

Construct and interpret SQL queries to retrieve, filter, and summarize data from a relational database.

Evaluate cybersecurity risks and apply fundamental security practices to protect personal and organizational data and systems.

Explain the core concepts, capabilities, and limitations of artificial intelligence and generative AI, and apply this understanding to project management contexts.

Design and build a working no-code/low-code application or automated workflow to solve a defined business problem.

Justify the selection of a business intelligence tool appropriate to a given business scenario.

Communicate technical knowledge effectively to a non-specialist audience through a self-organized learning session.

Synthesize knowledge gained from peers' learning sessions and integrate it into their own professional skill set.

Apply generative AI tools to a hands-on project, critically assessing their outputs for accuracy, bias, and appropriate use.

Evaluate the ethical implications of using AI and automation tools in academic and professional work, and apply principles of responsible, attributed technology use.