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657 tutors in 31 topics, built by 75 teachers. Each one follows a lesson plan its teacher wrote.

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Text classification from baseline to transformer

Text classification from baseline to transformer

Build text classifiers step by step, starting with a strong simple baseline and honest metricsBeginnerMachine learning4.3(4)74 lessonsSample
Nadia Haddad$5
Word and sentence embeddings

Word and sentence embeddings

Understand how meaning becomes vectors, compute similarity yourself and choose embeddings wiselyBeginnerNLP4.7(3)74 lessonsSample
Nadia Haddad$5
Machine translation: how it works and fails

Machine translation: how it works and fails

Understand how machines translate, judge translation quality and know when a human translator is neededAll levelsNLP4.3(3)74 lessonsSample
Nadia Haddad$6
Sentiment analysis done carefully

Sentiment analysis done carefully

Measure opinions in text without fooling yourself about sarcasm, mixed views or skewed averagesBeginnerNLP4.3(3)59 lessonsSample
Nadia Haddad$4
Tokenisation: how text becomes numbers

Tokenisation: how text becomes numbers

See how models split text into tokens, why it matters for cost and context, and where it trips upBeginnerHow language models work4.7(3)56 lessonsSample
Nadia HaddadFree
Speech to text pipelines

Speech to text pipelines

Turn recordings into accurate, timestamped transcripts and understand where speech recognition failsBeginnerAudio and voice AI4.7(3)54 lessonsSample
Nadia Haddad$5
Summarisation systems and their failure modes

Summarisation systems and their failure modes

Build and judge summaries that stay faithful to the source, from short notes to long reportsAll levelsNLP4.7(3)46 lessonsSample
Mateo Rojas$6
NLP for multilingual and low resource languages

NLP for multilingual and low resource languages

Build and evaluate language technology for languages that most datasets and models leave behindAll levelsNLPNew
Nadia Haddad$7