Natural Language Processing: NLP, Gemini & Transformers

About this course

Explore natural language processing through language examples, Gemini demonstrations and an introduction to transformer models. This course helps you connect AI terminology with the practical question behind an NLP application: what should a system understand from a piece of text, and how will you check its answer?

You begin by distinguishing artificial intelligence, machine learning and data science, then move into conversational AI and language workloads. The Gemini API and emotional-analysis example provide a starting point for examining inputs and outputs. Later recordings introduce transformers, discuss the model architecture presented in the lessons and demonstrate NLP applications.

What you can practise

Recognise common language-processing tasks and define the result you need.

Connect transformer and NLP vocabulary with the examples in the curriculum.

Compare interpretations of ordinary, ambiguous and mixed-sentiment text.

Build a small test set before deciding whether a demonstration works reliably.

The final reading workshops make evaluation concrete. Examine how text cleaning can remove useful meaning, then use a contrast set to test sentiment analysis. Keep the original message, your expected interpretation and the observed result together so that you can explain a disagreement.

This course suits learners exploring NLP and developers who want an accessible bridge from concepts to experiments. Basic programming familiarity helps with technical demonstrations. Recorded model names and interfaces reflect the tools used when filming, including earlier ChatGPT examples; consult current provider documentation for setup and availability. Choose the course for an introduction you can investigate and extend, with attention to evidence as well as fluent output.

From an AI demonstration to a question you can investigateA language application can look convincing long before its behaviour is understood.

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