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⇱ Chatbots with Keras & NLP: Build & Evaluate | Coursera


Chatbots with Keras & NLP: Build & Evaluate

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Chatbots with Keras & NLP: Build & Evaluate

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Gain insight into a topic and learn the fundamentals.
5.0

10 reviews

8 hours to complete
Flexible schedule
Learn at your own pace

Gain insight into a topic and learn the fundamentals.
5.0

10 reviews

8 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Apply preprocessing and vectorization in NLP.

  • Build ML and neural chatbot models with Keras.

  • Evaluate and optimize conversational AI systems.

Details to know

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Assessments

12 assignments

Taught in English

Build your subject-matter expertise

This course is part of the Keras Deep Learning Projects with TensorFlow Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 3 modules in this course

Learners will be able to analyze text data, implement preprocessing techniques, apply vectorization methods, design machine learning and neural models, and evaluate advanced chatbot systems. This hands-on course guides learners step by step through the process of building chatbots with Keras and TensorFlow, ensuring both foundational and advanced skills are developed.

The course begins with essential NLP preprocessing techniques, including Bag of Words, TF-IDF, stop word removal, stemming, and lemmatization. Learners then progress to applying classical ML models, TF-IDF, and Word2Vec embeddings before mastering neural networks and generative chatbot architectures. In the final module, learners explore attention mechanisms, advanced architectures, and evaluation strategies to create context-aware, high-performing conversational AI. By completing this course, learners gain practical coding experience, industry-ready workflows, and the ability to confidently design and deploy chatbots for real-world applications. Unlike purely theoretical courses, this program emphasizes hands-on implementation, progressive complexity, and evaluation-driven learningβ€”making it uniquely suited for those who want to design, implement, and assess intelligent chatbots with cutting-edge NLP techniques.

This module introduces learners to the essential foundations of Natural Language Processing (NLP) for chatbot development. It covers preprocessing techniques, feature extraction methods, and the basics of text normalization that ensure clean and structured input for building intelligent chatbot systems.

What's included

10 videos4 assignments

10 videosβ€’Total 85 minutes
  • Introduction to Projectβ€’6 minutes
  • Bow Modelβ€’8 minutes
  • Count Vectorizerβ€’11 minutes
  • Text Dataβ€’8 minutes
  • Text Data Continueβ€’10 minutes
  • Limit Number of Featuresβ€’8 minutes
  • Stop Wordsβ€’8 minutes
  • Stemmingβ€’11 minutes
  • Stemming Continueβ€’10 minutes
  • Lemmatizationβ€’7 minutes
4 assignmentsβ€’Total 60 minutes
  • Foundations of Text and Preprocessing – Graded Quizβ€’30 minutes
  • Getting Started With Text Projectsβ€’10 minutes
  • Preparing and Cleaning Text Dataβ€’10 minutes
  • Mastering Text Normalizationβ€’10 minutes

This module transitions from classical machine learning techniques to neural approaches for chatbot building. Learners will explore vectorization strategies like TF-IDF and Word2Vec, implement models using Keras, and gain practical experience with hands-on coding and neural network fundamentals.

What's included

9 videos4 assignments

9 videosβ€’Total 71 minutes
  • ML Model on Text Dataβ€’8 minutes
  • TF-TF-IDF Vectorizerβ€’6 minutes
  • Spacy Word2Vecβ€’9 minutes
  • Requirementsβ€’7 minutes
  • Hindson Implementationβ€’7 minutes
  • Hindson Implementation Continueβ€’9 minutes
  • Neural Networksβ€’9 minutes
  • Generative Chatbots Part 1β€’10 minutes
  • Generative Chatbots Part 2β€’7 minutes
4 assignmentsβ€’Total 60 minutes
  • Classical and Neural Approaches – Graded Quizβ€’30 minutes
  • From Vectors to Modelsβ€’10 minutes
  • Setting Up and Implementingβ€’10 minutes
  • Neural Foundations for Chatbotsβ€’10 minutes

This module delves into advanced chatbot architectures, including generative models with attention mechanisms and performance evaluation strategies. Learners will master cutting-edge NLP methods to design, implement, and evaluate context-aware and high-performing chatbot systems.

What's included

9 videos4 assignments

9 videosβ€’Total 73 minutes
  • Generative Chatbots Part 3β€’12 minutes
  • Generative Chatbots Part 4β€’12 minutes
  • Generative Chatbots Part 5β€’6 minutes
  • Attentive Chatbots Part 1β€’11 minutes
  • Attentive Chatbots Part 2β€’6 minutes
  • Attentive Chatbots Part 3β€’5 minutes
  • Advanced Chatbotβ€’11 minutes
  • Advanced Chatbot - Evaluationβ€’3 minutes
  • Conclusionβ€’6 minutes
4 assignmentsβ€’Total 60 minutes
  • Building Advanced Chatbots – Graded Quizβ€’30 minutes
  • Generative Chatbots Deep Diveβ€’10 minutes
  • Attention and Contextβ€’10 minutes
  • Beyond Basics – Advanced Chatbotsβ€’10 minutes

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Instructor

EDUCBA
1,663 Coursesβ€’338,914 learners

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Learner reviews

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Showing 3 of 10

AT
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Reviewed on May 5, 2026

The course provides a deep understanding of Keras for NLP. The evaluation frameworks are a unique addition that adds immense professional value to the curriculum.

VB
Β·

Reviewed on Jun 2, 2026

The instructor makes advanced deep learning concepts feel effortless. Complex NLP logic is broken down into simple, logical pieces.

DP
Β·

Reviewed on May 29, 2026

I appreciate how the course treats NLP as a rigorous science rather than just a coding trick. The clarity on hyperparameter tuning was a major highlight for me.

Frequently asked questions

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,