Žan Bezjak

Intensive 26-week training (520 hours) covering the entire Data Science project lifecycle, from data collection and preparation to deploying Machine Learning and Deep Learning models to production. Key skills to be acquired: • Python programming, data manipulation and visualization (Pandas, NumPy, Matplotlib, Seaborn, SQL, BigQuery) • Statistical and inferential analysis (SciPy, Statsmodels) • Supervised and unsupervised Machine Learning (Scikit-learn, XGBoost) • Deep Learning and Transformers (TensorFlow, Keras, Hugging Face) • Model deployment (MLOps, Docker, FastAPI, Streamlit, Google Cloud Platform, MLflow) • LLMs & Gen AI (LLMs, RAGs, Reinforcement Learning, Agents, Evaluation, GANs) • Neural Networks & NLP Expansion • AI-first Python coding (latest coding best practices and how to code Python with AI properly) • Understanding of ethical issues, model explainability, and integration of generative AI (LLM, LangChain) Final project: TBD

A forward‑looking Master’s program designed to equip professionals with the technical, ethical, and strategic capabilities needed to build and deploy AI systems that drive sustainable innovation. The curriculum integrates advanced AI technologies with systems thinking, sustainability frameworks, and responsible tech development — preparing graduates to design, evaluate, and implement AI solutions with real‑world impact. Program focus areas • Applied Artificial Intelligence & Machine Learning • Sustainable technology development & impact‑driven innovation • Responsible AI, governance, and ethical decision‑making • Systems thinking, circular economy, and sustainable business models • AI strategy, digital transformation, and organizational implementation