Gen AI Foundational Models for NLP & Language Understanding
Master foundational NLP concepts and implement language models using PyTorch.Gen AI Foundational Models for NLP & Language Understanding
Master foundational NLP concepts and implement language models using PyTorch.Gen AI Foundational Models for NLP & Language Understanding
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Generative AI Engineering with LLMs Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
Instructors:
English
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What you'll learn
Implement word-to-feature conversion techniques
Build and train Word2Vec models for text analysis
Develop neural networks for document classification
Create N-gram language models using PyTorch
Implement sequence-to-sequence models
Evaluate text generation quality using metrics
Skills you'll gain
This course includes:
1.33 Hours PreRecorded video
5 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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There are 2 modules in this course
This comprehensive course focuses on foundational concepts in natural language processing and language model implementation. Students learn various text representation methods, including one-hot encoding, bag-of-words, and embeddings, while gaining hands-on experience with Word2Vec and sequence-to-sequence models. The curriculum covers neural network implementation for document classification, N-gram language modeling, and text generation, with practical applications using PyTorch and torchtext.
Fundamentals of Language Understanding
Module 1 · 3 Hours to complete
Word2Vec and Sequence-to-Sequence Models
Module 2 · 4 Hours to complete
Fee Structure
Instructors
Ph.D. Candidate in Health Informatics and Data Scientist at IBM
Fateme is a fourth-year Ph.D. candidate in Health Informatics at McMaster University, where she specializes in applying machine learning to detect behavior abnormalities in sensor data streams. In addition to her academic work, she is a data scientist at IBM. Fateme has published research in esteemed journals like ACM Transactions of Computing for Healthcare and has presented her work at leading institutions, including Mayo Clinic and the Duke Center for Health Informatics. Her contributions are advancing the field of data-driven healthcare solutions.
Pioneering Data Scientist Bridging AI Research and Education
Dr. Joseph Santarcangelo, a Data Scientist at IBM, brings a unique blend of academic excellence and practical expertise to the field of data science and artificial intelligence. With a Ph.D. in Electrical Engineering, his groundbreaking research focused on the intersection of machine learning, signal processing, and computer vision to understand how video content influences human cognitive processes. At IBM, he has established himself as a prominent educator and course developer, creating comprehensive learning materials that have reached hundreds of thousands of students worldwide. His teaching portfolio encompasses a wide range of technical subjects, from foundational Python programming to advanced topics in artificial intelligence, machine learning, and computer vision. Santarcangelo's ability to translate complex technical concepts into accessible learning experiences has made him an influential figure in data science education, maintaining consistently high ratings from learners while continuing to push the boundaries of applied machine learning and artificial intelligence research.
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