Recommended Credentials

Recipients of the Uplimit Natural Language Processing certificates have learned the core NLP building blocks powering search engines like Google or voice assistants like Siri or Amazon Alexa. They developed an understanding of core NLP components — word vectors, intent classification, entity recognition and many more using transformer architectures like BERT and GPT — while building projects like embedding-based retrieval and smart-compose.

Certification criteria:

Actively participated in Uplimit's dynamic course on Natural Language Processing: attended lectures, project sessions, fireside chats with industry leaders, and more.

Built projects that use a NLP model, like a classification system, a system to locate and classify named entities mentioned in unstructured text, an embedded-based search system, and smart-compose system.

Instructor: Armando Banuelos and Samin Khan

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Developed familiarity with fundamentals of NLP, including Classification using PyTorch Lightning, Word Vectors, and Multilayer perceptron, Named-entity Recognition (RNNs, LSTMs, and NER), embedding-based retrieval including BERT, and smart compose.