Deep Learning and NLP: Seq2Seq Model Theory + ChatGPT Prizes (Udemy.com)
Learn the Theory of Deep Natural Language Processing with the Seq2Seq model and enjoy several ChatGPT Prizes at the end!
Created by: Hadelin de Ponteves
Last updated June 2026
What you will learn
- Why this is important
- Types of Natural Language Processing
- Classical vs. Deep Learning Models
- End to End Deep Learning Models
- Seq2Seq Architecture & Training
- Beam Search Decoding
How it compares
Against the other 126 rated Udemy courses in Deep Learning on CourseDuck:
- Rating4.3 out of 5higher than 18% of them
- Reviews4,924#19 of 127 by number of reviews
- Length8.3 hoursshorter than 56% of them
- Last updatedJune 2026more recently than 84% of them
Course Description
Learn the theory of Seq2Seq in only 2 hours! A straight to the point course for those of you who don't have a lot of time.
Embark on an academic adventure with our specialized online course, meticulously designed to illuminate the theoretical aspects of Seq2Seq (Sequence to Sequence) models within the realms of Deep Learning and Natural Language Processing (NLP).
What This Course Offers:
Exclusive Focus on Seq2Seq Model Theories: Our course curriculum is devoted to exploring the intricacies and theoretical foundations of Seq2Seq models. Delve into the principles and mechanics that make these models a cornerstone in NLP and Deep Learning.
In-Depth Conceptual Insights: We take you through a comprehensive journey, dissecting the core concepts, architectures, and training of Seq2Seq models. Our focus is on fostering a deep understanding of these complex theories.
Theory-Centric Approach: Emphasizing theoretical knowledge, this course intentionally steers away from practical coding exercises. Instead, we concentrate on building a robust conceptual framework around Seq2Seq models.
Ideal for Theoretical Enthusiasts: This course is perfectly suited for students, educators, researchers, and anyone with a keen interest in the theoretical aspects of Deep Learning and NLP, specifically in the context of Seq2Seq models.
Join us to master the theoretical nuances of Seq2Seq models in Deep Learning and NLP. Enroll now for an enlightening journey into the heart of these transformative technologies!
And last but not least you will get a great series of Prizes providing extra case studies in Artificial Intelligence made by ChatGPT.
Can't wait to see you inside the class,
Kirill & Hadelin
Instructor Details
- 4.3 Rating
4,924 Reviews
Hadelin de Ponteves
Hadelin is one of Udemy’s top instructors and a recognized leader in AI education. He has taught AI to over 2.6 million learners worldwide and is a frequent guest speaker at prominent industry events. Hadelin has created more than 30 top-rated courses on topics such as AI, Machine Learning, Deep Learning, Blockchain, and Cloud Computing, empowering learners around the globe to upskill in cutting-edge technologies.
In addition to his partnership with Udemy, Hadelin is the co-founder of CloudWolf and SuperDataScience. He is passionate about education and is on a mission to make complex technologies simple, practical, and widely accessible to all.
As a side activity, he is also an actor who acted in seven films, and a movie producer of two films (Indian and French).
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Reviews
By De Jarous Bell on 4/14/2021
This course, though very challenging, helped my finalize exactly what to specialize in as a ML Scientist. I've been looking for months to define the skills to begin creating my application. Come to find out, it's NLP. The reason I was able to understand what NLP could offer to my abstract idea was through the lectures of this course.
By Abdul Rab Ansari on 12/27/2020
Very Practical Training and explained well!
By Frederick Zhang on 12/20/2020
This course was quite an adventure and a fine way to top off the AI Engineer learning track. I think, by far, this has been the most coding-intensive course in the track, as a lot of material is stuffed into one Python script. With documentation (you should always comment on your code, especially when learning), mine exceeded 600 lines. I do wish the script was broken up into multiple files to be made more modular, though. I was also disappointed to learn that the architecture taught in this course, Seq2seq, is not supported in TensorFlow 2.0. Still, you learn the basics of DNLP thoroughly to build off of it using future frameworks.
By Bharat on 12/20/2020
Need some more explanation like why we are excluding the last column of targets........ it has been fast forwarded which is confusing a bit
By Big Pappa E on 12/6/2020
The topics covered in this course are quite advanced and will require a lot of pre existing knowledge or lengthy study to understand to even an appreciable level. That understanding in mind; this level of depth is delivered flawlessly! You will have a functioning, powerful deep learning model at the end of it!
By Evandruce Filbert on 11/24/2020
The code it's not capable for the new library
By Bharat_Subbu on 11/20/2020
Nice course for NLP beginner
By Bharath Bandla on 11/20/2020
it was very good
By Square Winter68 on 11/14/2020
I got much more than I expected. community support and in depth explanations, amazing.
By Vipul Kumar Gupta on 10/23/2020
Nice explanations
By Ng Jun Yi on 10/23/2020
Course was great overall, with a few lacking points:
Code is outdated. Using tensorflow 1.0.0 but tensorflow has already been updated past version 2.0.0, with many of the functions phased out or integrated with other functions.
The course is too short, it is generally understandable for people with some Python background.. But for people just starting out, there is a lack of explanation for the deeper intricacies of the course, even with the documentation provided.
But otherwise, course was explained clearly and succinctly, and you can always feel excited about learning with the enthusiasm exuded by the instructors. Cheers!
By Shubham Chauhan on 10/22/2020
In the earlier phases everything seems to be fine and the instructor explained well. Once the training started he started rushing and didn't even tested his own test in a positive manner. At least he should highlight the time to be taken in the training. The beam search chatbot was not explained at all.
Quality Score
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Overall Score : 86 / 100
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