Basics of Chatbots with Machine Learning & Python

Preview this course

Let’s learn the basic concepts for developing chatbots with machine learning models. This compact course will help you learn to use the power of Python to evaluate your chatbot datasets based on conversational notes, online resources, and websites. Garner hands-on practice in text generation with Python for chatbot development.

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51 on-demand videos & exercises
Level: Beginner
3hrs 3mins
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What to know about this course

Chatbots are software applications used for online chat conversations through text or text-to-speech instead of providing direct contact with a live human agent. Chatbots are used in dialog systems for various purposes, including customer service, request routing, or information gathering.

This course begins with a brief overview of chatbots, their need, and the types of chatbots. We will explore rule-based versus self-learning chatbots. We will understand the working mechanism of chatbots. We will explore machine learning-based chatbots and understand the ML-based architecture of chatbots.

You will learn about the purpose of ML-based chatbots and their impact. We will get an overview of the Natural Language Toolkit (NLTK). You will learn to install packages and create a corpus with Python. We will delve into text preprocessing and helper function deployment, generate responses, and implement term-frequency times inverse document-frequency. We will train and test rule-based chatbots and finally work on a project developing an artificial intelligence question-answer chatbot using NLTK.

Upon course completion, you will be able to relate the concepts and theories for chatbots in various domains, understand and implement machine learning models for building real-time chatbots, and evaluate machine learning models in chatbots. All resources are available at:

Who's this course for?

This course delivers content to people wishing to advance their skills in applied machine learning, master data analysis with machine learning, build customized chatbots for their applications, and implement machine learning algorithms for chatbots.
This course is for you if you are passionate about rule-based and conversational chatbots. Machine learning practitioners, research scholars, and data scientists can benefit from the course.
No prior knowledge of chatbots, or machine learning, is needed. You will need to know basic to intermediate Python coding, which is not taught separately in the course.

What you'll learn

  • Learn about chatbot types, rule-based and self-learning chatbots
  • Learn text preprocessing and develop helper functions with Python
  • Explore the impact and overview of the Natural Language Toolkit
  • Gain hands-on practice, generate text in Python to develop chatbots
  • Explore testing and training of chatbot with machine learning
  • Implement term-frequency times inverse document-frequency hands-on

Key Features

  • Learn chatbot basics, rule- and self-learning chatbots, and chatbot machine-learning architecture
  • Explore machine learning technology’s impact on chatbots and Natural Language Toolkit (NLTK)
  •  Implement hands-on term/inverse document-frequency, chatbot testing/training with machine learning

Course Curriculum

About the Author

AI Sciences

AI Sciences are experts, PhDs, and artificial intelligence practitioners, including computer science, machine learning, and Statistics. Some work in big companies such as Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM. AI sciences produce a series of courses dedicated to beginners and newcomers on techniques and methods of machine learning, statistics, artificial intelligence, and data science. They aim to help those who wish to understand techniques more easily and start with less theory and less extended reading. 

Today, they publish more comprehensive courses on specific topics for wider audiences. Their courses have successfully helped more than 100,000 students master AI and data science.

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