Advance Your Skills in Natural Language Processing

Unlock the potential of natural language processing (NLP) with this comprehensive learning path. Gain hands-on experience with spaCy for rule-based AI, work with recurrent neural networks (RNNs) using TensorFlow, and build applications with transformers. Each course is designed to deepen your understanding and practical skills in NLP. Start now to elevate your AI expertise and stay ahead in this rapidly evolving field.

Translate text data into powerful insights using Python.
Learn about transformers, the go-to architecture of NLP.
Build NLP apps with transformers.
Implement tokenization and word embeddings using TensorFlow.

Syllabus

Courses under this program:
Course 1: Advanced NLP with Python for Machine Learning
-Build upon your foundational knowledge of natural language processing by exploring more complex topics.

Course 2: Hands-On Natural Language Processing
-Learn to use natural language processing to make sense of text data and derive useful insights.

Course 3: Building NLP Pipelines with spaCy
-Learn the essentials of problem-solving with spaCy, the popular, open-source software library for advanced natural language processing.

Course 4: Deep Learning Foundations: Natural Language Processing with TensorFlow
-Learn foundational deep learning techniques to classify, predict, and generate text using different neural networks.

Course 5: Recurrent Neural Networks
-Learn the basics of recurrent neural networks to get up and running with RNN quickly.

Course 6: Generative AI: Working with Large Language Models
-Explore a user-friendly approach to working with transformers and large language models for natural language processing.

Courses

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2 hours 10 minutes
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Build upon your foundational knowledge of natural language processing (NLP) by exploring more complex topics such as word2vec, doc2vec, and recurrent neural networks.
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1 hour 7 minutes
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Learn the basics of recurrent neural networks to get up and running with RNN quickly.
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50 minutes
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Learn to use natural language processing to make sense of text data and derive useful insights.
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1 hour 9 minutes
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Explore a user-friendly approach to working with transformers and large language models for natural language processing.
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1 hour 48 minutes
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Learn foundational deep learning techniques to classify, predict, and generate text using different neural networks.
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1 hour 1 minute
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Learn the essentials of problem-solving with spaCy, the popular, open-source software library for advanced natural language processing.