WEEK 1: Python Essentials for AI Development

• Session 1:

o What is AI/NLP/chatbot?

o Install & set up Google Colab

o Python basics: variables, strings, print(), input()

• Session 2:

o Data types (int, float, string, list, dict)

o Control structures: if, else, elif

• Session 3:

o Functions, arguments, return values

o Simple terminal chatbot logic (input() + print())

WEEK 2: Deeper Python + Project Setup

• Session 4:

o Loops: for, while, nested logic

o String formatting & dynamic responses

• Session 5:

o Lists, dictionaries – chatbot as a key-value lookup

o Build: rule-based FAQ chatbot (dictionary driven)

• Session 6:

o Organize Python code: modules, file structure

o Project planning: chatbot_v1 folder setup

WEEK 3: Intro to NLP and AI

• Session 7:

o What is NLP? Tokenization, language models

o Real chatbot architecture (intents, context, responses)

• Session 8:

o Hugging Face Intro

o Install transformers, torch in Colab or local

• Session 9:

o Load & test pipeline("text-generation") using GPT2

o Parameters: temperature, max_length, top_p, etc.

WEEK 4: AI Chatbot Backend

• Session 10:

o Wrap model call in Python functions

o Improve prompts: prompt engineering basics

• Session 11:

o Design a Python-based chatbot CLI (terminal interface)

o Add logging & basic session memory (history)

• Session 12:

o Test different models (DistilGPT2 vs GPT2)

o Use conversation pipeline (optional)

WEEK 5: Web App with Streamlit – UI Fundamentals

• Session 13:

o Install and run Streamlit

o Streamlit widgets: st.text_input, st.button, st.write

• Session 14:

o Build basic chatbot UI

o Link: user input > Hugging Face model > response

• Session 15:

o Format responses, markdown, styling

o Add title, chatbot avatar, header/footer

WEEK 6: Advanced Features & Interactivity

• Session 16:

o Add reset/clear button, welcome message, chatbot name

o Use session state to store chat history

• Session 17:

o Add personality: role-based prompting

o Use emojis, themes, loading animations

• Session 18:

o Optional: Add voice input/output using gTTS & speech_recognition

WEEK 7: Full Project Integration

• Session 19:

o Finalize chatbot logic + UI

o Add configuration options (choose model, temperature slider)

• Session 20:

o Test end-to-end: input > AI > output

o Catch exceptions, clean responses

• Session 21:

o Git & GitHub (optional): push your chatbot project

o Prepare for deployment

WEEK 8: Final Project, Review & Demo

• Session 22:

o Project polishing: branding, docs, cleanup

• Session 23:

o Live demo and peer feedback

o Optional: Deploy app to Streamlit Cloud

• Session 24:

o Review, showcase best projects, discuss future paths (LangChain, RAG, GPT APIs)

BCA TU