Mastering Conversational AI: Creating Dynamic Chatbots with Python and Rasa Open Source

What you'll 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

Requirements
Basic Python

Description
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.

Who this course is for
Beginner who are interested building Chatbots with Python