Class PIA22.

Professional Roles - Application developer specialising in AI - Python developer specialising in AI - Systems developer in Python The graduate has knowledge of... - Theoretical and practical programming in Python - Business acumen and personal responsibility for one's own professional development in a corporate environment - Commonly used models for machine learning, deep learning and AI - The principles of object orientation: concepts such as class, inheritance, polymorphism - Different models of neural networks, for example RNN (Recurrent Neural Networks) and CNN (Convolutional Neural Networks) - Techniques for training ML and AI models - The functionality of deep learning, for example in image analysis and natural language processing - Knowing and understanding the mathematical foundations underlying machine learning - Models for predictions - Basic problem solving methods in automation - Agile methods, processes and ways of working The graduate has skills in... - Apply algorithms in Python's web frameworks (for example Django, Flask) - Communicate and present project work - Use machine learning models for prediction and as a basis for decisions - Build machine learning models with Python - Understand and apply problem solving methods in automation - Train an AI algorithm - Use version control systems for correcting and debugging code - Construct well-functioning classes in their code - Use AI platforms to develop smart system solutions and automated functions - Reflect critically on the advantages and disadvantages of machine learning and AI - Apply agile ways of working and methods The graduate has the competence to... - Critically evaluate their own work, for example their own applications in Python - Work with AI applications to develop application solutions - Independently both work in and lead agile projects - Work independently as a Python programmer - Work with systems and design based on object-oriented analysis - Complete projects in their role as a Python developer focused on AI - Monitor, update and evaluate an AI solution that is actively in production - Identify risks with an AI solution, and understand and process data