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Code generation is the use of AI to automatically write, complete, or suggest source code based on natural language descriptions or partial code. Modern code generation tools understand programming context and can produce functional code across many languages.
AI code generation accelerates software development, reduces boilerplate work, and lowers the barrier to entry for people learning to programme.
GitHub Copilot suggests entire functions and code blocks as developers type, drawing on patterns from millions of open-source repositories.
Large Language Model (LLM)
A large language model is an AI system trained on vast quantities of text data that can understand, generate, and reason about human language. LLMs use the transformer architecture and contain billions of parameters, enabling them to perform a wide range of language tasks.
Content Generation
Content generation is the use of AI to create text, images, audio, video, or other media automatically. Generative AI models learn the patterns and structures of existing content and produce new, original material based on prompts.
Prompt Engineering
Prompt engineering is the practice of crafting and refining the instructions (prompts) given to an AI model to get the best possible output. It involves techniques like providing context, examples, and constraints to guide the model's response.
Our programme follows a structured Level 4 curriculum with project-based learning, practical workflows, and guided implementation across business and career use cases. Funded route available for UK citizens and ILR holders.