The Complete Course of Rasa Chatbot

Name: The Complete Course of Rasa Chatbot
Rating: 3.4 (15 reviews)

Learn how to build a Python Chatbot in a Professional way. Become an expert in Rasa framework and NLU, from A to Z!

Created byThe Tech Courses

Last updated 1/2025

English

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What you'll learn

At the end of the course you will fully master Rasa, to be able to deploy your own python conversational chatbots from scratch
You will be able to develop your own codes, understanding all the logic and ending with advanced practical examples & step by step projects
You will become familiar with the Rasa structure and basic commands, and you will master all the phases of the configuration process
You will learn in a professional way how to Build Rasa NLU (Natural Language Understanding) chatbots
You will develop step-by-step a Rasa Weather Bot, modifying the domain files, the data files, and the custom actions, and deploying it via the react app
You will learn Learn the Advanced Rasa NLU and Rasa Core Techniques, including, for example, deploying Rasa Chatbot to Watsapp or Telegram
You will develop from scratch Raina (Lung Cancer Risk Assessment Chatbot), mastering all the phases of the creation and deploying it to messaging paltforms
You will learn the Rasa Interactive, understanding its basis
You will learn how to use ChatGPT to build Rasa Chatbots
You will master the advanced Tips and Tricks to Rasa framework, and you will discover the best resources to stay updated
You will be able to practice the content learned in a practical way by following all the steps in the complete exercises and the complete projects
You will start with the basics and progressively carry out more complex steps until you reach an advanced level and absolute mastery at the end of the course

Course content

8 sections • 31 lectures • 6h 47m total length

Basic Introduction to Rasa10:24
Explore the open source Rasa framework for building conversational AI, covering NLU and Core, plus Rasa X and modular architecture for chatbots and virtual assistants.
Capabilities of Rasa4:29
Explore the capabilities of Rasa, including natural language understanding, dialog management, and customization with custom actions and components, plus seamless integration with channels and APIs to build versatile chatbots.
About Rasa NLU5:52
Explore how Rasa NLU interprets user input by classifying intents and extracting entities, supports multilingual models, and uses a configurable machine learning pipeline for training and evaluation.
Quiz
About Rasa Core7:52
Explore how Rasa core manages dialogue and context to drive natural, dynamic conversations, and learn dialog flow design, contextual understanding, and custom actions with Rasa NLU.
Live Coding: Rasa Installation, Structure of domain.yml, nlu.yml, & config.yml11:15
Learn to install Rasa with Python 3.8 and initialize it. Explore the structure of domain.yml, nlu.yml, and config.yml through live coding, training, and testing with Rasa shell.

Understanding Training data and rules23:32
Learn how to collect and structure Rasa training data from user generated text, patterns, and logs using stories and rules. Apply interactive learning and checkpoints to refine intents and NLU.
Overview of the domain file8:40
Explore the domain file in Rasa, the brain of a chatbot, defining intents, entities, slots, actions, and templates to shape responses and behavior.
Understanding entities18:32
Explore how Rasa entities are defined and extracted, including Duckling and SpaCy integration, regex patterns, synonyms, and rows and groups, to power precise conversation understanding.
Understanding Slots14:07
Explore how slots act as the long-term memory in a conversation, storing information and influencing the flow, with definitions in domain.yml and detections from entities.

Introduction to development of weather bot5:37
Develop a fully functional weather bot in Rasa with a weatherboard UI that answers weather conditions across countries. Build the bot with intents, slots, and entities and test live conversations.
Modifying Rasa domain files and data files( nlu.yml, sturies.yml, rules.yml)19:25
Set up a Python project with Rasa, define weather intents and entities in the domain.yml, configure slots and responses, and craft stories and rules for weather bot with custom actions.
Modifying the custom actions and deploying via the react app21:09
Define and deploy custom actions in a rasa chatbot, including action weather with OpenWeatherMap api calls, and connect a React user interface to run rasa as an api.

Introduction to Rasa deployment for production12:36
Learn how to deploy a Rasa chatbot for production by making it live on render and on messaging platforms like WhatsApp and Telegram.
Deploying Rasa with render22:02
Deploy a Rasa chatbot to production with render, exposing its API via ngrok, and implement NLU, domain, stories, and custom actions while deploying from GitHub.
Deploying Rasa to WhatsApp platform14:12
Deploy your Rasa chatbot to the WhatsApp platform using Twilio, configure a sandbox, integrate credentials and ngrok webhooks, and test messaging via WhatsApp.
Deploying Rasa to Telegram platform9:12
Deploy a rasa chatbot to Telegram by creating a bot with BotFather, configuring token and username, setting the webhook via ngrok, and running rasa with API and actions.

Common Rasa commands and their uses15:28
Learn common Rasa commands and their uses, including init, train, shell, run actions, run with enable API, test, data split, validate, export, interactive, visualize, migrate, and license checks.
Review of the steps Involved in starting and training a Rasa project9:21
Learn to start and train a Rasa project by installing Rasa, initializing a project, defining domain and data, creating stories and rules, defining custom actions, and testing with Rasa shell.
Role of Chatbots and assistants in industries20:13
Explore how chatbots and assistants transform industries with 24/7 support, quick responses, task automation, and improved customer service across retail, e-commerce, banking, travel, and healthcare.

Introduction to Section 63:36
Apply the Rasa chatbot framework to real-life scenarios by building a lung cancer risk assistant. Ask users questions, collect details, and determine whether they are at risk of lung cancer.
Understanding the Problem Statement8:45
Explore how Reina, a Rasa powered lung cancer risk assessment chatbot, clarifies the problem statement and demonstrates early detection, accessibility, privacy and security, and user-friendly AI driven healthcare guidance.
ChatBot in Action6:43
See a Rasa chatbot in action named Rina as it guides users through a lung cancer risk assessment on Telegram, using dynamic questions and clickable input buttons.
Development of Raina Part 115:50
Set up a Rasa chatbot project using PyCharm or VS Code, initialize Rasa, and build the NLU and domain configurations, including a lung cancer form with slots mapped from entities.
Development of Raina Part 226:54
Define and map slots for Reina, a Rasa chatbot, including smoking history, secondhand smoke, carcinogens, family history, personal history, symptoms, payloads and buttons in forms to assess lung cancer risk.

Introduction to Section 7, Building the custom actions for Raina27:19
Learn to build a Rasa chatbot named Rina, defining custom actions and domain, wiring slots, and rules to assess lung cancer risk and reset slots.
Deploying Raina to Messaging Platforms (Telegram)7:29
Deploy your Rasa chatbot to Telegram and other messaging platforms by configuring bot credentials and webhooks. Set up Ngrok, port 5005, and the action server with rasa run actions.
Overview of Rasa Interactive13:29
Learn how Rasa Interactive lets you fine-tune your chatbot, train models, and dramatically boost accuracy from 60% to over 8,090%.

Introduction to Section 85:09
Explore why Rasa differs from ChatGPT, how ChatGPT can enhance Rasa chatbot development, and recap the journey from basics to practical Rasa components.
The Future of Rasa in comparison to ChatGpt17:20
Explore the future of Rasa versus ChatGPT, weighing open-source scalability, easy integration, and security against AI generative capabilities, while highlighting Rasa's context handling and enterprise trust.
Using ChatGpt to build Rasa Chatbots14:54
ChatGPT complements Rasa by generating chatbot ideas, enabling prompt engineering, and guiding updates to NLU, domain, rules, and stories for a financial planning bot.
Recap of the course and Conclusion6:12
Recaps the complete Rasa course, covering Rasa NLU and Rasa Core, installation, domain and config files, training data, and deploying chatbots to render, WhatsApp, and Telegram.

Requirements

Having basic notions of Rasa and machine learning can help, but if not, do not worry cause the course starts from scratch
Installing Rasa and preparing the needed environment (if you don't know how, don't worry, it's very easy, free, and I'll explain it to you in the course!)
A decent computer and of course, desire to learn!

Description

Become a Rasa chatbot developer professional and learn one of employer's most requested skills nowadays!

This comprehensive course is designed so that Data Scientists, Developers, Engineers, Students... can learn Rasa AI Platform from scratch to use it in a practical and professional way. Never mind if you have no experience in the topic, you will be equally capable of understanding everything and you will finish the course with total mastery of the subject.

After several years working in software engineering, we have realized that nowadays mastering Rasa is essential for deploying conversational AI chatbots using Natural Language Processing (NLU) and Python. Knowing how to use this open-source framework can give you many job opportunities and many economic benefits, especially in the world of the AI.

The big problem has always been the complexity to perfectly understand Intune it requires, since its absolute mastery is not easy. In this course we try to facilitate this entire learning and improvement process, so that you will be able to carry out and understand your own projects in a short time, thanks to the step-by-step and detailed examples of every concept.

With almost 7 exclusive hours of video and 31 lectures, this comprehensive course leaves no stone unturned! It includes both practical exercises and theoretical examples to fully master Rasa framework. The course will teach you how to create any python chatbot in a practical way, from scratch, and step by step.

We will start with the Rasa installation and needed environment, and then, we'll cover a wide variety of topics, including:

Introduction to Rasa, NLU and course dynamics
Rasa installation, configurations and needed set-up
General familiarization with the user interface and elements
How to Build Rasa NLU
Development of Rasa Weather Bot
Advanced Rasa NLU and Rasa Core Techniques: deploying Rasa to Whatsapp, Telegram...
Development of Raina: Lung Cancer Risk Assessment Chatbot
Rasa Interactive
Using ChatGPT to build Rasa Chatbots
Advanced Tips and Tricks to Master Rasa and the best resources to stay updated in the future
Mastery and application of absolutely ALL the functionalities of Rasa Chatbot
Practical exercises, complete projects and much more!

In other words, what we want is to contribute our grain of sand and teach you all those things that we would have liked to know in our beginnings and that nobody explained to us. In this way, you can learn to manage a wide variety of real applications cases quickly and make versatile and complete use of Rasa Chatbot. And if that were not enough, you will get lifetime access to any class and we will be at your disposal to answer all the questions you want in the shortest possible time.

Learning Rasa has never been easier. What are you waiting to join?

Who this course is for:

Beginners who have never used Rasa before
Data Scientists, Developers, Engineers, Students... who want to learn a new a way to develop python chatbots
Intermediate or advanced Rasa Chatbot users who want to improve their skills even more!

The Complete Course of Rasa Chatbot

What you'll learn

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Course content

Introduction to Rasa5 lectures • 40min

Building Rasa NLU4 lectures • 1hr 5min

Development Of Rasa Weather Bot3 lectures • 46min

Advanced Rasa NLU Techniques4 lectures • 58min

Advanced Rasa Core Techniques3 lectures • 45min

Development of Raina: Lung Cancer Risk Assessment ChatBot5 lectures • 1hr 2min

Continuation on Raina Development, Overview of Rasa Interactive3 lectures • 48min

Conclusion4 lectures • 44min

Requirements

Description

Who this course is for: