Learn to install the rasa framework in a Python 3.7 virtual environment using official docs, then initialize your project with setup commands to start building a chatbot.

Install and initialize the grool framework for building a rasa chatbot, train the initial model, and explore rasa init, interactive, and rasa x for testing conversations and custom actions.

Define stories as the building blocks of a chatbot in Rasa, showing how intents, entities, responses, and actions shape a conversation and guide outcomes.

Master domain.yml in a rasa 2x project by clarifying its three parts: intents with examples, regular actions, and custom actions. See how images, buttons, and widgets can be included.

Learn how stories.yml powers Rasa 2x chatbots by linking user intents like greed, happy, and unhappy to corresponding actions and responses, and see practical testing and deployment considerations.

Discover the roles of core RASA files—domain, stories, and custom actions—and see how actions.py and __init__.py enable python-based actions, packaging, and deployment, with configurable fallback, confidence thresholds, credentials, and endpoints.

Understand a university dataset for a chatbot: student records include names, gender, department, year, subjects and labs, attendance, marks, and secure IDs stored in a database.

Build a chatbot with RASA 2x that fetches real-time data from a database to show attendance and marks, check admissions, and read holidays from an Excel file, with credential checks.

Learn to build Rasa stories by drafting intents and actions, starting with greetings, then implement a login flow with username and password to fetch attendance and marks.

Create stories for intents like upcoming holidays, admission info, and attendance using data from an Excel file, with greetings and goodbyes as separate stories and actions in a RASA chatbot.

Learn to build NLU data for a Rasa chatbot by creating diverse intent examples for marks, attendance, and admissions, training with an Excel dataset and neural networks.

Build custom actions in Rasa 2x by implementing the run method and naming actions to trigger logic. Use action files and responses to fetch data such as marks and holidays.

Build and train a Rasa model, enable default policies and endpoints, run Rasa X and custom actions, and validate credentials to fetch and display student marks in real time.

Build a custom action that validates a registration number and password by reading tracker messages and querying a database. Display the student's marks and total, or credentials incorrect.

Builds a custom action for Rasa to fetch attendance data by validating registration number and password, counts present and absent days from a data frame, and returns an attendance summary.

Fixes action naming and builds an upcoming holidays flow in rasa 2x, using an Excel date-holiday file, dispatching a holiday list to a response template, with manual testing.

Deploy a chatbot to a web application by configuring the API on port 5021, enabling the API, and testing with a simple HTML and JavaScript chat widget.