Python Case Studies: Build Chatbots, Apps & Systems

Overview

By completing this course, learners will design, implement, and validate real-world Python projects while gaining hands-on experience in natural language processing, database-driven applications, and text-processing automation. They will develop a rule-based chatbot, build and enhance an expense manager app, and implement a full markup processing system with PDF generation. The course begins with chatbot development, where learners set up their environment, apply NLTK tools, and refine reflection dictionaries and pairs to create intelligent conversational agents. Next, learners will design and enhance an expense manager app, focusing on form creation, SQL integration, data visualization, and advanced category management to deliver a fully functional financial tracking tool. The course concludes with the Instant Markup project, guiding learners through parsing, rules, filters, and handlers to transform raw text into structured documents, ending with PDF output and internet-based data gathering. Unlike traditional Python tutorials, this course is case-study driven, meaning every skill is applied in a practical context. Learners not only master Python coding but also apply Bloom’s higher-order skills—analyzing, designing, and implementing solutions to real-world problems. By the end, participants will be equipped to tackle projects that combine NLP, database operations, and automated text processing.

Syllabus

Building a Rule-Based Chatbot

This module introduces learners to the foundations of chatbot development using Python and NLTK. It covers environment setup, the reflection dictionary, pairs, and validation methods to create a functional rule-based chatbot capable of handling real conversations.

Designing an Expense Manager App

This module focuses on designing and developing an expense manager app using Python, HTML, and SQL. Learners will build input forms, manage expense entries, and apply Bootstrap for user-friendly interfaces.

Enhancing the Expense Manager

This module extends the expense manager app with advanced category management, data visualization, and final refinements. Learners will implement IDs, build charts, query expenses, and refine Python class-based methods for efficient application design.

Instant Markup – Text Processing Foundations

This module introduces the Instant Markup project, where learners explore parsing, rules, filters, and handlers. It emphasizes text structuring and rule-based processing for automated document handling.

Advanced Markup and Final Implementation

This module finalizes the Instant Markup project by integrating scripts, preparing data, and generating outputs. Learners will apply rule scripts, implement the main program, and create final outputs including PDF generation and internet-based data gathering.