AI Engineering - Development and Optimisation.

Description of the programme content After completing the programme, the student shall have knowledge of - The AI Engineer Path and career paths. - Principles and terminology in AI. - Ethics and sustainability in AI. - API use and programming for AI. - Advantages and disadvantages of open and closed source code. - The concept of embeddings and their use. - Semantic search and use of a vector-based database such as Supabase. - Concepts in AI agents. - Prompt engineering for effective AI agents. - Constructing and managing interactions for AI agents. - OpenAI's Assistants API and its areas of use. - Overview of LangChain and its areas of use in AI. - Design and development of AI-driven applications with LangChain. - Interactive work with user interfaces and memory management in AI. After completing the programme, the student shall have the skills to - Create and use AI APIs. - Create effective prompts for AI models. - Work practically with AI tools. - Use HuggingFace.js for AI model training. - Apply basic AI techniques and terminology. - Apply open source code in text-to-speech and image transformation. - Explore and benefit from open source projects. - Generate and manipulate embeddings for different data types. - Use vector-based databases such as Supabase for efficient data management. - Perform semantic search and optimal searches. - Build and test their own AI agents. - Create effective AI agents through prompt engineering. - Develop AI agents for interaction with people and systems. - Create and manage AI assistants with OpenAI's Assistants API. - Apply the Assistants API in practical projects and problem solving. - Design and develop AI-driven applications with LangChain. - Integrate user interfaces with AI components. - Manage data and memory in AI applications. - Plan and carry out independent projects with integrated AI knowledge. - Create AI solutions or innovations with a focus on technical complexity and creative problem solving.