On June 3, 2026, the curriculum transitioned into text parsing, string methods, collection types, and the conceptual logic of rule-based chatbots.
1. Python Collections for State Mapping
We focused on two essential collection schemas: Lists and Dictionaries. We explored Lists for sequence modeling (e.g., maintaining lists of inputs, command histories, or user names), and Dictionaries for key-value pairings (e.g., mapping trigger words to structured replies). This mapped out the foundational storage structures that allow simple chatbots to operate.
2. Input Normalization & String Handling
Because user inputs are inherently chaotic, we focused on normalization operations like case formatting (lower/upper) and substring checking ('in' statements). This prevents matching bugs, ensuring that user commands like 'HELLO', 'hello', or 'Hello there' are routed to the same response key.
3. Rule-Based Chatbot Logic & The Whiteboard Session
For our core task, Rashmi gave the cohort 1 hour to build a functional CLI-based chatbot. Divy and I finished it in 60 seconds, then shifted to helping classmates. Recognizing our speed, Rashmi had me go to the whiteboard to show file handling on the board, and I spoke about the while loop code. I wrote advanced, production-ready python code for file handling which she later simplified so the class of diploma engineers could follow it.