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Deep Learning: Natural Language Processing with Transformers (Udemy.com)

Use Huggingface transformers and Tensorflow to build Sentiment analysis, Translation, Q&A, Search, Speech,... projects

Created by: Neuralearn Dot AI

Last updated February 2026

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What you will learn

  • The Basics of Tensors and Variables with Tensorflow
  • Mastery of the fundamentals of Machine Learning and The Machine Learning Developmment Lifecycle.
  • Basics of Tensorflow and training neural networks with TensorFlow 2.
  • Sentiment Analysis with Recurrent neural networks, Attention Models and Transformers from scratch
  • Neural Machine Translation with Recurrent neural networks, Attention Models and Transformers from scratch
  • Recurrent Neural Networks, Modern RNNs, training sentiment analysis models with TensorFlow 2.
  • Intent Classification with Deberta in Huggingface transformers
  • Conversion from tensorflow to Onnx Model
  • Building API with Fastapi
  • Deploying API to the Cloud
  • Neural Machine Translation with T5 in Huggingface transformers
  • Extractive Question Answering with Longformer in Huggingface transformers
  • E-commerce search engine with Sentence transformers

How it compares

Against the other 126 rated Udemy courses in Deep Learning on CourseDuck:

  • Rating4.2 out of 5higher than 10% of them
  • Reviews242#97 of 127 by number of reviews
  • Length28.9 hourslonger than 91% of them
  • Last updatedFebruary 2026more recently than 75% of them

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Course Description

Deep Learning is a hot topic today! This is because of the impact it's having in several industries. One of the fields in which deep learning has the most influence today is Natural Language Processing.

To understand why Deep Learning based Natural Language Processing is so popular; it suffices to take a look at the different domains where giving a computer the power to understand and make sense out of text and generate text has changed our lives.

Some applications of Natural Language Processing are in:

  • Helping people around the world learn about any topic ChatGPT

  • Helping developers code more efficiently with Github Copilot.

  • Automatic topic recommendation in our Twitter feeds

  • Automatic Neural Machine Translation with  Google Translate

  • E-commerce search engines like those of Amazon

  • Correction of Grammar with Grammarly

The demand for Natural Language Processing engineers is skyrocketing and experts in this field are highly paid, because of their value. However, getting started in this field isn’t easy. There’s so much information out there, much of which is outdated and many times don't take the beginners into consideration :(

In this course, we shall take you on an amazing journey in which you'll master different concepts with a step-by-step and project-based approach. You shall be using Tensorflow 2 (the world's most popular library for deep learning, built by Google) and Huggingface transformers (most popular NLP focused library ). We shall start by understanding how to build very simple models (like Linear regression model for car price prediction and RNN text classifiers for movie review analysis) using Tensorflow to much more advanced transformer models (like Bert, GPT, BlenderBot, T5, Sentence Transformers and Deberta).

After going through this course and carrying out the different projects, you will develop the skill sets needed to develop modern deep learning for NLP solutions that big tech companies encounter.

You will learn: 

  • The Basics of Tensorflow (Tensors, Model building, training, and evaluation)

  • Text Preprocessing for Natural Language Processing.

  • Deep Learning algorithms like Recurrent Neural Networks, Attention Models, Transformers, and Convolutional neural networks.

  • Sentiment analysis with RNNs, Transformers, and Huggingface Transformers (Deberta)

  • Transfer learning with Word2vec and modern Transformers (GPT, Bert, ULmfit, Deberta, T5...)

  • Machine Learning Operations (MLOps) with Weights and Biases (Experiment Tracking, Hyperparameter Tuning, Dataset Versioning, Model Versioning)

  • Machine translation with RNNs, attention, transformers, and Huggingface Transformers (T5)

  • Model Deployment (Onnx format, Quantization, Fastapi, Heroku Cloud)

  • Intent Classification with Deberta in Huggingface transformers

  • Named Entity Relation with Roberta in Huggingface transformers

  • Neural Machine Translation with T5 in Huggingface transformers

  • Extractive Question Answering with Longformer in Huggingface transformers

  • E-commerce search engine with Sentence transformers

  • Lyrics Generator with GPT2 in Huggingface transformers

  • Grammatical Error Correction with T5 in Huggingface transformers

  • Elon Musk Bot with BlenderBot in Huggingface transformers

  • Speech recognition with RNNs


If you are willing to move a step further in your career, this course is destined for you and we are super excited to help achieve your goals!

This course is offered to you by Neuralearn. And just like every other course by Neuralearn, we lay much emphasis on feedback. Your reviews and questions in the forum will help us better this course. Feel free to ask as many questions as possible on the forum. We do our very best to reply in the shortest possible time.


Enjoy!!!

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Instructor Details

Neuralearn Dot AI

We provide world class courses in Mathematics for Deep Learning (Linear Algebra, Calculus, Probability, Statistics, Optimization), Core Deep Learning Theory (Going from the basics of Machine Learning up to most recent state of art Deep Learning Algorithms) and Practical Deep Learning applied in fields like Computer vision and Natural Language Processing, using modern tools like TensorFlow, PyTorch, HuggingFace, KubeFlow, …

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Reviews

4.2

242 ratings on Udemy

Select a bar to show only those reviews.Select the bar again to show every rating.

By Joffrey Graham on 7/6/2024

Great intro to NLP with Deep Learning! The course uses clear explanations and practical examples to make complex concepts understandable. I particularly liked the practical projects that helped me solidify my learning. Highly recommend!

By Leanse Sangeerth on 1/12/2024

Accent and voice quality is highly breaking what he is trying to say. course structure is good. Didnt meet expectations in terms of teaching. Feels like our classmate teaches concept just before day of exam

By Evan Tait-Styles on 8/3/2023

The sound quality could definitely be better. The drawings + diagrams as well, I'm only at the very start but the drawings are sometimes quite confusing. I'd also suggest running a spell check, "requiscite" is misspelled for example.

By Nimish Shandilya on 7/26/2023

This is a really good course. It starts from the basics and then covers each topic in depth like what actually goes inside the blackbox of our model code, this allows us to get intuition as to what actually the model is doing. Amazing!!

By Amit Tomar on 7/9/2023

Great explanation of core concepts, each and every output of command execution is analyzed in very detail. Slow and steady and since some of this goes very technical, its good to go a bit slow to give time to understand. The input / output and vector transformations become complex very fast.

By Amit Rai Chowdhury on 7/6/2023

The content is really good, but the delivery could be improved. The instructor keeps droning on the same point again and again making it boring. Something that could be covered in 10 mins is stretched to 40 mins. Have tried to go through the videos many times now, but just lose interest after a while. But give full marks for the content. He has covered quite interesting projects.

By John Vilder on 6/26/2023

The first part of the course focuses on building transformers from scratch, while the next part makes use of the Huggingface library. This way of building from first principles and at same time using modern tools was great for me!

By Favour Gabriele Hugo on 6/1/2023

very helpful and practical course that thoroughly took me through building simple ML models to state of art NLP models. I'm especially glad i'm able to work much fluently with Huggingface models. Definitely recommended!

By Nichole Juan on 5/21/2023

I'd recommend this course to anyone (like myself) who wants to get started with practical nlp. The course strikes a good balance between teaching the details of how transformers work and how we can tackle problems using huggingface transformers.

By Chiron Bang on 2/24/2023

Good course. It teaches important fundamental as well as more advanced concepts all in a simple way. It shows how good the teacher is. The teacher goes through current models such as BERT, RoBERTa and so on without neglecting the building concepts which are Transformers. I am happy to have taken this course!

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Overall Score : 84 / 100