How to Build Chatbot with Python & Rasa Open Source
How to Build Chatbot with Python & Rasa Open Source, available at $74.99, has an average rating of 4.13, with 43 lectures, based on 122 reviews, and has 691 subscribers.
You will learn about Gain a comprehensive understanding of the principles and concepts behind conversational AI and the role of Rasa in building chatbots. Master the techniques to create powerful Natural Language Understanding (NLU) models using Rasa NLU, enabling your chatbot to comprehend user inputs accurately. Learn how to integrate external APIs to fetch real-time data, demonstrated through the development of a Weather Chatbot that provides weather information. Explore advanced techniques for NLU enhancement, including entity recognition, synonym handling, and context-sensitive intent recognition Develop skills in building interactive and dynamic conversations using Rasa Forms Understand how to design fallback mechanisms for handling user queries that the chatbot doesn't understand Learn how to integrate Rasa with a MySQL database to store and retrieve user data Discover different deployment options and strategies for your Rasa chatbot, including Facebook, Slack, Telegram, Ngrok and Whatsapp Learn how to integrate your Rasa Chatbot with Flask Web Application This course is ideal for individuals who are Beginner who are interested building Chatbots with Python It is particularly useful for Beginner who are interested building Chatbots with Python.
Enroll now: How to Build Chatbot with Python & Rasa Open Source
Summary
Title: How to Build Chatbot with Python & Rasa Open Source
Price: $74.99
Average Rating: 4.13
Number of Lectures: 43
Number of Published Lectures: 43
Number of Curriculum Items: 43
Number of Published Curriculum Objects: 43
Original Price: $19.99
Quality Status: approved
Status: Live
What You Will Learn
- Gain a comprehensive understanding of the principles and concepts behind conversational AI and the role of Rasa in building chatbots.
- Master the techniques to create powerful Natural Language Understanding (NLU) models using Rasa NLU, enabling your chatbot to comprehend user inputs accurately.
- Learn how to integrate external APIs to fetch real-time data, demonstrated through the development of a Weather Chatbot that provides weather information.
- Explore advanced techniques for NLU enhancement, including entity recognition, synonym handling, and context-sensitive intent recognition
- Develop skills in building interactive and dynamic conversations using Rasa Forms
- Understand how to design fallback mechanisms for handling user queries that the chatbot doesn't understand
- Learn how to integrate Rasa with a MySQL database to store and retrieve user data
- Discover different deployment options and strategies for your Rasa chatbot, including Facebook, Slack, Telegram, Ngrok and Whatsapp
- Learn how to integrate your Rasa Chatbot with Flask Web Application
Who Should Attend
- Beginner who are interested building Chatbots with Python
Target Audiences
- Beginner who are interested building Chatbots with Python
Welcome to the comprehensive course, “How to Build Chatbot with Python and Rasa Open Source.” If you’re interested to dive into the exciting world of conversational AI, this course is your gateway to creating powerful, intelligent chatbots from scratch using Python and Rasa Open Source.
Course Description:
In today’s digital landscape, chatbots have become an integral part of user engagement and customer support. This course is meticulously designed to equip you with the skills needed to creat sophisticated chatbots using Python and also leverage the capabilities of Rasa Open Source, a leading conversational AI framework.
Key Focus Areas:
-
Understanding Rasa NLU: Lay the foundation by grasping the core concepts of Rasa NLU (Natural Language Understanding). Learn how to preprocess and extract meaning from user messages, forming the basis for accurate interactions.
-
Building Weather Chatbot and API Calls: Dive into practical implementation as you build a Weather Chatbot that interacts with external APIs to provide real-time weather information. Understand how to integrate API calls seamlessly into your chatbot flow.
-
Advanced NLU Techniques: Elevate your chatbot’s understanding of user intent and entities. Explore advanced techniques to enhance NLU performance, including entity recognition and synonym handling.
-
Rasa Forms: Discover the power of Rasa Forms in creating structured conversations. Implement dynamic forms that guide users through complex interactions, ensuring a seamless and user-friendly experience.
-
Fallback and Human Handoff: Learn how to gracefully handle user queries that fall outside the chatbot’s capabilities using fallback mechanisms. Explore strategies for seamless transition to human agents when necessary.
-
Rasa and MySQL Database: Integrate Rasa with MySQL databases to store and retrieve user-specific data, enabling personalized interactions and a more engaging user experience.
-
Deploy Rasa Chatbot: Take your chatbot from development to deployment. Explore deployment options and strategies, ensuring your chatbot is accessible to users across various platforms.
-
Rasa and Flask Integration: Extend the capabilities of your chatbot by integrating it with Flask, a powerful web framework. Learn how to create a user-friendly web interface for your chatbot.
By the end of this course, you’ll gain the skills and knowledge to create intelligent chatbots that can understand user intents, retrieve and present information, and provide a delightful conversational experience. Whether you’re a developer looking to enter the world of AI-driven chatbots or a professional aiming to enhance customer interactions, this course empowers you to build and deploy sophisticated chatbots with Python and Rasa Open Source. Enroll now and embark on a journey into the exciting realm of conversational AI.
Course Curriculum
Chapter 1: Section Introduction
Lecture 1: Course Introduction
Lecture 2: Course Requirements
Chapter 2: Introduction to Rasa and Conversational AI
Lecture 1: Conversational AI & Rasa
Lecture 2: Rasa Overview and It is Key Components
Lecture 3: Setting Up the Development Environment
Lecture 4: Create Rasa Project
Lecture 5: Rasa Project Structure
Chapter 3: Understanding Rasa NLU
Lecture 1: Hello World Chatbot From Scratch
Lecture 2: Overview of Rules.yml File
Lecture 3: Overview of NLU File
Lecture 4: Overview of Domain File
Lecture 5: Overview of Story File
Lecture 6: Entity Extraction
Lecture 7: Adding More Functionality
Chapter 4: Building Weather Chatbot and API Calls
Lecture 1: Creating Intent and Entities for Weather Bot
Lecture 2: Rasa Pipeline
Lecture 3: What are Slots
Lecture 4: Rasa Policies
Chapter 5: Advanced NLU Techniques
Lecture 1: Rasa Synonyms
Lecture 2: Entity Extraction with Regex
Lecture 3: Rasa Lookup Table
Lecture 4: Movie Recommendation Chatbot Part One
Lecture 5: Movie Recommendation Chatbot Part Two
Lecture 6: Choosing Right Pipeline in Rasa
Chapter 6: Rasa Forms
Lecture 1: Rasa Form Introduction
Lecture 2: Rasa Forms Practical Example
Chapter 7: Fallback and Human Handoff
Lecture 1: Fallback and Human Handoff
Lecture 2: Fallbacks in Rasa
Lecture 3: NLU Fallback
Lecture 4: Handling Low Action Confidence
Lecture 5: Two Stage Fallback
Chapter 8: Rasa and MySQL Database
Lecture 1: Creating Basic Chatbot
Lecture 2: Adding Data to Database
Lecture 3: Show All Data
Chapter 9: Deploy Rasa Chatbot
Lecture 1: Connect Rasa to Ngrok
Lecture 2: Integrate Rasa Chatbot with Facebook Messenger
Lecture 3: Rasa Chatbot Integration with Slack
Lecture 4: Rasa and Telegram Integration
Lecture 5: Integrate Rasa Chatbot with WhatsApp
Chapter 10: Rasa and Flask Integration
Lecture 1: Section Introduction
Lecture 2: Create Flask and Rasa Chatbot
Lecture 3: Handle User Input in Chatbox
Lecture 4: Send User Message to the Server
Instructors
-
Parwiz Forogh
Programmer
Rating Distribution
- 1 stars: 3 votes
- 2 stars: 4 votes
- 3 stars: 16 votes
- 4 stars: 41 votes
- 5 stars: 58 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
You may also like
- Top 10 Video Editing Courses to Learn in November 2024
- Top 10 Music Production Courses to Learn in November 2024
- Top 10 Animation Courses to Learn in November 2024
- Top 10 Digital Illustration Courses to Learn in November 2024
- Top 10 Renewable Energy Courses to Learn in November 2024
- Top 10 Sustainable Living Courses to Learn in November 2024
- Top 10 Ethical AI Courses to Learn in November 2024
- Top 10 Cybersecurity Fundamentals Courses to Learn in November 2024
- Top 10 Smart Home Technology Courses to Learn in November 2024
- Top 10 Holistic Health Courses to Learn in November 2024
- Top 10 Nutrition And Diet Planning Courses to Learn in November 2024
- Top 10 Yoga Instruction Courses to Learn in November 2024
- Top 10 Stress Management Courses to Learn in November 2024
- Top 10 Mindfulness Meditation Courses to Learn in November 2024
- Top 10 Life Coaching Courses to Learn in November 2024
- Top 10 Career Development Courses to Learn in November 2024
- Top 10 Relationship Building Courses to Learn in November 2024
- Top 10 Parenting Skills Courses to Learn in November 2024
- Top 10 Home Improvement Courses to Learn in November 2024
- Top 10 Gardening Courses to Learn in November 2024