Advanced Chatbots with Deep Learning and Python
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Advanced Chatbots with Deep Learning and Python
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What you'll learn
Identify the key differences between conventional and AI-based chatbots.
Explain how deep learning enhances chatbot functionalities across different industries.
Build a chatbot using Python and deep learning libraries like TensorFlow and Keras.
Examine the architecture and workflow of encoder-decoder models in chatbot development.
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3 assignments
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There are 3 modules in this course
Updated in May 2025.
This course now features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. This course is designed to equip learners with the knowledge and skills required to develop advanced chatbots using deep learning and Python. The initial modules provide an overview of chatbots, their evolution, and the benefits of incorporating AI into chatbot development. Learners will gain an understanding of the fundamental differences between conventional chatbots and those powered by deep learning, including generative and retrieval models. As the course progresses, you will delve into the architecture and development of deep learning-based chatbots. Through hands-on modules, you will explore the entire process, from understanding the architecture of encoders and decoders to practical implementations. By working through real-world examples, you will learn to set up environments, import necessary libraries, and prepare data for chatbot training and testing. Each step is clearly outlined to ensure a smooth learning experience. Towards the end, you will focus on building a fully functional chatbot, integrating it with deep learning models, and testing its capabilities. The course concludes with a series of projects that help you consolidate your learning by applying the concepts in various domains such as healthcare, business, and e-commerce. By the end of this journey, you will have developed the proficiency to create robust chatbots that can be deployed in diverse applications. This course is ideal for developers, data scientists, and AI enthusiasts who are interested in building intelligent chatbots. A basic understanding of Python programming and machine learning is recommended to get the most out of this course.
In this module, we will cover the foundational details of the course and instructor, introducing learners to the benefits of learning through the AI Sciences platform. Weβll explore the overall course structure, highlighting key topics like chatbot technology, its comparison to other systems, and the deep learning frameworks involved.
What's included
3 videos1 reading
3 videosβ’Total 7 minutes
- Course and Instructor Introductionβ’2 minutes
- AI Sciences Introductionβ’1 minute
- Course Descriptionβ’3 minutes
1 readingβ’Total 10 minutes
- Full Course Resourcesβ’10 minutes
In this module, we will explore the core fundamentals of chatbots, focusing on how deep learning enhances chatbot capabilities. We will compare conventional chatbots with AI-based ones and dive into specific use cases, such as how chatbots function in healthcare, business, and ecommerce, delivering tailored experiences and operational efficiencies.
What's included
7 videos
7 videosβ’Total 31 minutes
- Module Introductionβ’4 minutes
- Conventional Versus AI Chatbotsβ’6 minutes
- Generative Versus Retrieval Chatbotsβ’4 minutes
- Benefits of Deep Learning Chatbotsβ’5 minutes
- Chatbots in Medical Domainβ’5 minutes
- Chatbots in Businessβ’5 minutes
- Chatbots in Ecommerceβ’3 minutes
In this module, we will dive deep into the architecture and development of chatbots using deep learning. Learners will build chatbots from scratch by implementing frameworks, preparing data, tokenizing text, and training models using tools like TensorFlow and Keras. The module culminates in testing chatbot predictions and optimizing performance.
What's included
17 videos3 assignments
17 videosβ’Total 80 minutes
- Module Introductionβ’3 minutes
- Deep Learning Architectureβ’2 minutes
- Encoder Decoderβ’2 minutes
- Steps Involvedβ’2 minutes
- Project Overview and Packagesβ’4 minutes
- Importing Librariesβ’5 minutes
- Data Preparationβ’7 minutes
- Develop Vocabularyβ’5 minutes
- Max Story and Question Lengthβ’4 minutes
- Tokenizerβ’3 minutes
- Separation and Sequenceβ’5 minutes
- Vectorize Storiesβ’10 minutes
- Vectorizing Train and Test Dataβ’6 minutes
- Encodingβ’7 minutes
- Answer and Responseβ’6 minutes
- Model Completionβ’5 minutes
- Predictionsβ’5 minutes
3 assignmentsβ’Total 90 minutes
- Full Course Practice Assessmentβ’15 minutes
- Deep Learning-Based Chatbot Architecture and Development - Assessmentβ’15 minutes
- Full Course Assessmentβ’60 minutes
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Frequently asked questions
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. Youβll be able to submit assignments once the session starts.
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. Youβll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.
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