Johns Hopkins University

Chatbots

This course is part of Social Computing Specialization

Ian McCulloh

Instructor: Ian McCulloh

Included with Coursera Plus

Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

13 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

13 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Explore the history and mechanics of chatbots, enhancing your understanding of their design and function.

  • Construct and evaluate machine learning classifiers using BERT for effective text classification tasks.

  • Gain hands-on experience in creating and configuring functional chatbots using AWS Chatbot services.

Details to know

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Recently updated!

September 2024

Assessments

8 assignments

Taught in English

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This course is part of the Social Computing Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
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There are 4 modules in this course

Explore the practical applications of machine learning through hands-on modules covering data pre-processing, feature extraction, model evaluation, and supervised learning techniques. Delve into specialized topics such as computer vision and learn to implement and assess various machine learning models. This course combines theoretical insights with practical lab activities to equip you with essential skills in applied machine learning

What's included

1 reading1 plugin

In this module, you'll delve into the fascinating world of chatbots, covering their historical development and evolution. Understand the basic mechanics behind how chatbots work and explore fundamental design principles essential for enhancing their performance. Gain practical insights into building and optimizing chatbots using Amazon Lex, a leading platform for developing conversational interfaces. By the end of this module, you'll have a comprehensive understanding of chatbot technology and its application across various industries.

What's included

2 videos2 readings3 assignments

In this module, you’ll focus on constructing and evaluating machine learning (ML) classifiers using crowdsourced data. You’ll learn how to leverage BERT (Bidirectional Encoder Representations from Transformers) in R and TensorFlow for text classification tasks. You’ll also gain hands-on experience in building ML models that classify text data effectively. You’ll learn to calculate and interpret ML performance metrics to assess classifier accuracy and reliability. By the end of this module, you'll be equipped with practical skills to develop robust classifiers capable of handling diverse datasets.

What's included

1 reading2 assignments1 ungraded lab

This module will guide you through the process of building your own chatbot using AWS (Amazon Web Services). You’ll begin with an introductory conceptual video outlining chatbot creation concepts. You’ll dive deep into practical implementation with AWS Chatbot, learning step-by-step how to set up and configure your chatbot. You will also explore strategies to make your chatbot operational and effective. You’ll collaborate with classmates to exchange ideas and troubleshoot challenges, fostering a supportive learning environment. By the end of this module, you'll have the skills and confidence to develop functional chatbots tailored to various applications.

What's included

3 readings3 assignments5 plugins

Instructor

Ian McCulloh
Johns Hopkins University
17 Courses947 learners

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