Natural Language Processing with Attention Models (Coursera)

Offered by DeepLearning.AI,
Natural Language Processing with Attention Models (Coursera)

This course is for students of machine learning or artificial intelligence as well as software engineers looking for a deeper understanding of how NLP models work and how to apply them.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

In Course 4 of the Natural Language Processing Specialization, offered by DeepLearning.AI, you will:
a) Translate complete English sentences into German using an encoder-decoder attention model,
b) Build a Transformer model to summarize text,
c) Use T5 and BERT models to perform question-answering, and
d) Build a chatbot using a Reformer model.
Course 4 of 4 in the Natural Language Processing Specialization

Syllabus

WEEK 1
Neural Machine Translation
Discover some of the shortcomings of a traditional seq2seq model and how to solve for them by adding an attention mechanism, then build a Neural Machine Translation model with Attention that translates English sentences into German.

WEEK 2
Text Summarization
Compare RNNs and other sequential models to the more modern Transformer architecture, then create a tool that generates text summaries.

WEEK 3
Question Answering
Explore transfer learning with state-of-the-art models like T5 and BERT, then build a model that can answer questions.

WEEK 4
Chatbot
Examine some unique challenges Transformer models face and their solutions, then build a chatbot using a Reformer model.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Automated Report Generation with Generative AI (Coursera) Coursera
Coursera Instructor Network

Automated Report Generation with Generative AI (Coursera)

In today's data-driven world, generating reports efficiently is a valuable skill for professionals across various industries. This course introduces beginners to the world of automated report generation using AI-powered tools and techniques. You will learn how to leverage the capabilities of artificial intelligence to streamline the reporting process, save time, and improve data accuracy.

Aug 17th 2026
1 Week
Practical Machine Learning on H2O (Coursera) Coursera
H2O.ai

Practical Machine Learning on H2O (Coursera)

In this course, we will learn all the core techniques needed to make effective use of H2O. Even if you have no prior experience of machine learning, even if your math is weak, by the end of this course you will be able to make machine learning models using a variety of algorithms. We will be using linear models, random forest, GBMs and of course deep learning, as well as some unsupervised learning algorithms.

Aug 17th 2026
5-12 Weeks
Prompt Engineering for Web Developers (Coursera) Coursera
Scrimba

Prompt Engineering for Web Developers (Coursera)

Not quite getting the results you want from ChatGPT? Wondering how you can use AI language models to your advantage? Then this course is for you! If you’ve spent any amount of time with AI language models like ChatGPT and Google Bard, you may have noticed the results can sometimes be, well, frustrating. When it comes to leveraging AI language models, your output is often only as good as your input. In other words, it’s all about learning how best to communicate your desired results. Effective prompt engineering is the secret sauce for getting the most out of AI.

Aug 17th 2026
3 Weeks
Probabilistic Graphical Models 2: Inference (Coursera) Coursera
Stanford University

Probabilistic Graphical Models 2: Inference (Coursera)

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more.

Aug 17th 2026
5-12 Weeks
Use Generative AI as Your Thought Partner (Coursera) Coursera
Coursera Instructor Network

Use Generative AI as Your Thought Partner (Coursera)

This is a lesson from the comprehensive program, Navigating Generative AI for Leaders. In this lesson, you’ll learn how Coursera CEO, Jeff Maggioncalda, leverages generative AI models to be a more effective CEO. Jeff will discuss how he uses AI covering everything from his set up and model choices, through hands-on prompting examples.

Aug 17th 2026
1 Week
Machine Learning Rapid Prototyping with IBM Watson Studio (Coursera) Coursera
IBM

Machine Learning Rapid Prototyping with IBM Watson Studio (Coursera)

An emerging trend in AI is the availability of technologies in which automation is used to select a best-fit model, perform feature engineering and improve model performance via hyperparameter optimization. This automation will provide rapid-prototyping of models and allow the Data Scientist to focus their efforts on applying domain knowledge to fine-tune models. This course will take the learner through the creation of an end-to-end automated pipeline built by Watson Studio’s AutoAI experiment tool, explaining the underlying technology at work as developed by IBM Research.

Aug 17th 2026
4 Weeks
Experimentation for Improvement (Coursera) Coursera
McMaster University

Experimentation for Improvement (Coursera)

We are always using experiments to improve our lives, our community, and our work. Are you doing it efficiently? Or are you (incorrectly) changing one thing at a time and hoping for the best? In this course, you will learn how to plan efficient experiments - testing with many variables. Our goal is to find the best results using only a few experiments. A key part of the course is how to optimize a system.

Aug 17th 2026
5-12 Weeks
Designing Autonomous AI (Coursera) Coursera
University of Washington,Microsoft

Designing Autonomous AI (Coursera)

When children learn how to hit a baseball, they don’t start with fastballs. Their coaches begin with the basics: how to grip the handle of the bat, where to put their feet and how to keep their eyes on the ball. Similarly, an autonomous AI system needs a subject matter expert (SME) to break a complex process or problem into easier tasks that give the AI important clues about how to find a solution faster.

Aug 17th 2026
4 Weeks