Funded by the EU. The views and opinions expressed are solely those of the author(s) and do not necessarily reflect the views and opinions of the European Union or the Foundation for the Development of the Education System. . Neither the European Union nor the Foundation for the Development of the Education System are responsible for them.
The project „Artificial Intelligence in Programming – Qualification and Certification in Vocational Education” (2024-1-PL01-KA210-VET000253203) is co-financed by the Erasmus+ programme. Sector: KA210-VET – Small-scale Partnerships in School Education, Vocational Education and Training, Adult and Youth Education (KA210).
Support for teachers and entrepreneurs in collaboration with the education sector.
The project aims to enhance the competencies of future programming technicians in the use of AI and prepare them for work in the IT industry.
Duration: approximately 80 teaching hours + independent work.
Groups of individuals who may be interested in obtaining the qualification:
Graduates of technical and vocational schools: In particular, IT technicians and programming technicians, for whom the qualification represents a natural extension of their knowledge to include practical aspects of quality engineering, often omitted from standard curricula.
Junior/Mid-level programmers wishing to expand their skills to include ML and LLM technologies.
Reskilling individuals: Professionals from other industries with analytical predispositions who wish to enter the IT sector through a quality assurance path that combines soft and technical skills.
Data analysts and testers wishing to automate work using generative models.
The course consists of:
Module 1: AI Ontology, Ethics, AI Act, GDPR
Module 2: Linear Algebra, Statistics, Gradient Descent
Module 3: Python, venv/Docker, Jupyter, Git
Module 4: NumPy, Pandas, Data Cleaning, SQL + Visualization
Module 5: Supervised/Unsupervised ML, Metrics, GridSearchCV
Module 6: Neural Networks, CNN/RNN, TensorFlow/PyTorch
Module 7: LLM, Prompt Engineering, RAG, API
Module 8: Copilot/Cursor, Refactoring with AI, TDD + Security
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0).
https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en
Program kursu
- 8 Sections
- 30 Lessons
- 80 Hours
- Module 1: AI Ontology, Ethics, and Legislation6
- 1.11.1 The History of AI: From Expert Systems to the GenAI Era
- 1.21.2 Taxonomy: AI vs ML vs Deep Learning
- 1.3Test – AI in programming – Module 1A60 Minutes20 Questions
- 1.41.3 Legal Framework: AI Act, GDPR and Copyright
- 1.51.4 AI Ethics: Hallucinations, Bias, and Green AI
- 1.6Test – AI in Programming – Module 1B30 Minutes10 Questions
- Module 2: Mathematics and Statistics for AI4
- Module 3: Python and Data Science Environment5
- Module 4: Data Processing and EDA5
- Module 5: Classic ML Algorithms5
- Module 6: Neural Networks and Deep Learning5
- Module 7: LLM and Prompt Engineering5
- 7.17.1 Transformer Architecture: Tokenization, Pre-Training, RLHF
- 7.27.2 Prompt Engineering: Zero-Shot, Few-Shot, Chain of Thought
- 7.37.3 RAG Architecture: Vector Bases and Hallucination Reduction
- 7.47.4 API Integration: OpenAI, Hugging Face, Open-Source Models
- 7.5Test – AI in programming – Module 7135 Minutes45 Questions
- Module 8: AI-Assisted Development4
