Natural Language Processing with Probabilistic Models
This course is part of Natural Language Processing.
This comprehensive course explores probabilistic methods in Natural Language Processing. Students learn to implement autocorrect using minimum edit distance, apply Hidden Markov Models for part-of-speech tagging, create N-gram language models for autocomplete, and develop word embeddings using neural networks. Through hands-on programming assignments, learners build practical NLP tools while understanding the underlying mathematical concepts.
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What you'll learn
Build an autocorrect system using minimum edit distance
Implement part-of-speech tagging using Hidden Markov Models
Create N-gram language models for text prediction
Develop word embeddings using neural networks
Evaluate language models using intrinsic and extrinsic methods
Skills you'll gain
This course includes:
3.32 Hours PreRecorded video
8 assignments
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FullTime access
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There are 4 modules in this course
This course provides a thorough exploration of probabilistic approaches in Natural Language Processing. The curriculum is structured around four key modules: autocorrect systems using dynamic programming, part-of-speech tagging with Hidden Markov Models, N-gram language models for autocomplete, and word embeddings using neural networks. Each module combines theoretical foundations with practical implementation, featuring extensive programming assignments and real-world applications.
Autocorrect
Module 1 · 6 Hours to complete
Part of Speech Tagging and Hidden Markov Models
Module 2 · 5 Hours to complete
Autocomplete and Language Models
Module 3 · 8 Hours to complete
Word embeddings with neural networks
Module 4 · 9 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Natural Language Processing
Instructors
Stanford AI Educator Pioneers Global Learning Through Course Innovation and EdTech Leadership
Younes Bensouda Mourri is a distinguished AI educator and entrepreneur who has significantly impacted global tech education. Born and raised in Morocco, he earned his B.S. in Applied Mathematics and Computer Science and M.S. in Statistics from Stanford University, where he now teaches Artificial Intelligence both on campus and online. As the founder of LiveTech.AI, he develops AI tools to transform academic institutions, while his courses have reached over 1.3 million learners worldwide, with 23% securing AI-related jobs after completion. His contributions include co-creating Stanford's Applied Machine Learning, Deep Learning, and Teaching AI courses, as well as developing the highly successful Natural Language Processing Specialization for DeepLearning.AI. Starting as a teaching assistant in Andrew Ng's Machine Learning course, he rose to become an Adjunct Lecturer at Stanford by age 22, demonstrating his commitment to democratizing AI education. Through his work with major companies like ASML, CISCO, and Boston Consulting Group, he continues to advance AI education while focusing on developing innovative NLP tools for personalized feedback and chain-of-thought reasoning
Pioneering AI Education and Product Management
Eddy Shyu is a prominent AI Product Manager at Cisco, with a notable background in curriculum development as the former Curriculum Product Manager at DeepLearning.AI. He has played a crucial role in creating approximately 40 online courses focused on artificial intelligence, which have reached over 2 million learners across platforms such as Coursera, DeepLearning.AI, Udacity, and Cisco Networking Academy. Eddy's expertise extends to designing educational content that simplifies complex AI concepts for diverse audiences, ensuring accessibility and engagement in learning. His work includes leading the creation of Andrew Ng’s Machine Learning Specialization, which has become a foundational resource for aspiring AI professionals. With a passion for education and innovation, Eddy continues to shape the future of AI learning and product management, empowering individuals to leverage artificial intelligence effectively in their careers.
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