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Gen AI Foundational Models for NLP & Language Understanding

Joseph Santarcangelo and Fateme Akbari

4.4

Based on 45 ratings

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Joseph Santarcangelo and Fateme Akbari

This IBM course will teach you how to implement, train, and evaluate generative AI models for natural language processing (NLP). The course will help you acquire knowledge of NLP applications including document classification, language modeling, language translation, and fundamentals for building small and large language models.

You will learn about converting words to features. You will understand one-hot encoding, bag-of-words, embedding, and embedding bags. You also will learn how Word2Vec embedding models are used for feature representation in text data.

You will implement these capabilities using PyTorch.

The course will teach you how to build, train, and optimize neural networks for document categorization. In addition, you will learn about the N-gram language model and sequence-to-sequence models. This course will help you evaluate the quality of generated text using metrics, such as BLEU.

You will practice what you learn using Hands-on Labs and perform tasks such as implementing document classification using torchtext in PyTorch. You will gain the skills to build and train a simple language model with a neural network to generate text and integrate pre-trained embedding models, such as word2vec, for text analysis and classification. In addition, you will apply your new skills to develop sequence-to-sequence models in PyTorch and perform tasks such as language translation.

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What's inside

Syllabus

Fundamentals of Language Understanding

In this module, you will learn about one-hot encoding, bag-of-words, embeddings, and embedding bags. You will also gain knowledge of neural networks and their hyperparameters, cross-entropy loss, and optimization. You will then delve into the concept of language modeling with n-grams. The module also includes hands-on labs on document classification with PyTorch and building a simple language model with a neural network.

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Covers basic natural language processing concepts, which is standard in AI and machine learning

In-demand AI skill that can boost employability in various industries

Builds a strong foundation in NLP theory and tools for beginners

Taught by renowned instructors with expertise in NLP

Requires some familiarity with PyTorch and NLP concepts; may not be suitable for absolute beginners

May need to supplement with additional resources for a comprehensive understanding of NLP

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Gen AI Foundational Models for NLP & Language Understanding with these activities:

NLP Basics

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Review the fundamentals of NLP to strengthen your foundational understanding.

Browse courses on Natural Language Processing

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Read introductory materials on NLP concepts and techniques.
Complete practice exercises to reinforce your understanding of NLP basics.

Course Materials Compilation

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Organize your course materials for easy reference and review.

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Gather and organize course notes, assignments, quizzes, and exams.
Create a centralized repository for all materials.

NLP Discussion Group

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Engage with peers in discussions to enhance your understanding and retention of NLP concepts.

Browse courses on NLP

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Join or create a study group focused on NLP.
Participate actively in discussions, sharing insights and asking questions.

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Hands-on Word2Vec

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Enhance your understanding of Word2Vec embeddings through guided tutorials.

Browse courses on Word2Vec

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Follow online tutorials on Word2Vec implementation and usage.
Experiment with different Word2Vec parameters to optimize performance.

NLP Expert Guidance

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Seek guidance from experienced NLP professionals to deepen your understanding and career development.

Browse courses on NLP

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Identify NLP experts through online platforms or professional networks.
Reach out to potential mentors and request guidance.

Sequence-to-Sequence Practice

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Master sequence-to-sequence models through consistent practice to improve accuracy and efficiency.

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Solve coding problems on sequence-to-sequence tasks.
Participate in online coding challenges to test your skills.

Natural Language Classifier

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Solidify your knowledge of document classification by building a classifier from scratch.

Browse courses on Document Classification

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Choose a dataset and preprocess the text data.
Define a neural network model for document classification.
Train and evaluate your model on the chosen dataset.

Chatbot Development

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Gain practical experience in NLP by developing a chatbot using the skills learned in the course.

Browse courses on Chatbots

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Design the chatbot's conversation flow and user interface.
Implement the chatbot's natural language processing capabilities using course-learned techniques.
Test and refine the chatbot's performance through user interaction.

Career center

Learners who complete Gen AI Foundational Models for NLP & Language Understanding will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 50 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Gen AI Foundational Models for NLP & Language Understanding.

Deep Learning

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More advanced treatment of generative AI models, covering the mathematical foundations of the field and the latest research results. It is written by two of the leading researchers in the field, and it is suitable for readers with a strong background in AI.

Deep Learning (Adaptive Computation and Machine...

Hardcover

$$$

Deep Learning (Adaptive Computation and Machine...

Kindle Edition

$$$

Natural Language Processing with Transformers,...

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Dives into contemporary topics by focusing on Transformer models, which are central to modern language modeling, including Large Language Models (LLMs). It provides a practical, hands-on approach using the popular Hugging Face library, making it highly relevant for practitioners and those wanting to deepen their understanding of current techniques.

Gen AI Foundational Models for NLP & Language Understanding

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What's inside

Syllabus

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