Oliyarnyk, Yuriy2024-02-282024-02-282024https://er.auk.edu.ua/handle/234907866/48Software projects are crucial for creativity, productivity, and organizational performance. However, their complexity can lead to risks and failures. Despite modern project management tools improving success rates, significant investment waste and project failures persist. In 2020, 11.4% of investment was lost due to poor project performance, and in 2021, 33% of IT projects failed, resulting in significant budget losses. As organizations enter 2022, challenges in big data, analytics, and AI projects are increasing, highlighting the need for a paradigm change in project management techniques. The Monte Carlo approach, a quantitative risk analysis technique, is gaining popularity to reduce uncertainty in software projects and provide more reliable estimations. The current implementation uses Jupyter Notebooks technology and decreases a steep learning curve for users.en-USProject management, quantitative risk analysis, stochastic experiment, simulationThesis