How to Build Chatbot with Python & Rasa Open Source

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:

1. 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.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.
7. 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.
8. 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.
9. More on Rasa Forms: In this section we are going to learn more about Rasa Forms, and we add more information on Rasa usage.
10. Creating News Bot: In this section we want to interact with API and create a news Bot
11. Rasa with OpenAI LLMs: In this section we want to talk about LLMs, and how we can integrate OpenAI (GPT) LLMs with Rasa Open Source
12. Rasa with Cohere LLMs: In this section we are going to integrate Rasa with Cohere LLMs.
13. Rasa with Google Gemini: In this section we are going to talk about Google Vertex AI, and how we can integrate Google Gemini with Rasa Open Source.
14. Rasa with Hugging Face: In this section we want to learn how to integrate Rasa Open Source with Hugging Face Models.

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.