Python Chatbot Bootcamp w/ Pandas, NumPy and SciKit

Mammoth interactive, an online school founded in 2012 by programmer and teacher John Baraa, teaches in-demand tech skills and helps people of all ages build project-based skills to land jobs.

Learn online effectively with active industry teachers, fast, project-based learning, and a strong portfolio by finishing projects, learning what you need, and learning at your own pace.

Learn Python basics from scratch with practical code in Google Colab, covering variables, operators, conditionals, loops, functions, and classes to build real programs.

Explore how Python variables act as data placeholders and store the program’s state. Learn booleans, integers, floats, and strings, dynamic typing, and basic type conversion with simple code examples.

Explore Python type conversion with practical examples of integers, floats, strings, and booleans. See how conversion creates new values without altering originals and how true and false mapping works.

Explore Python operators, including arithmetic, assignment, comparison, and logical operators. See how numbers and strings behave, and when operators modify variables versus producing new results.

Explore Python collections: lists, tuples, dictionaries, and ranges, and learn how they store multiple values, access elements by index or key, and the differences between mutable and immutable types.

Explore how to create and manipulate lists and multidimensional lists, i.e., matrices, in Python, access and modify elements by row and column, and use append, insert, pop, and clear.

Explore tuples in Python by creating and accessing items, comparing them to lists, and using count, index, and length to illustrate immutability and index-based retrieval.

Build and manipulate Python dictionaries with key-value pairs to create an inventory, access and modify items by key, use get for access, and remove or clear entries, order doesn't matter.

Explore Python ranges, including start, end, and step parameters, reversing, and using in and not in checks. Learn converting range objects to lists and practical examples from 1 to 10.

Explore conditionals in Python, from basic if statements to elif and else, and use them to control flow, test multiple conditions with and, or, and handle complex logic.

Master Python control flow using if statements, elif and else, and the ternary operator, through a game-style movement example and a look at consecutive, nested, and multi-condition tests.

Explore how Python loops work, comparing while and for loops and their break and continue controls. Build loop examples with ranges and lists to manage iteration and avoid infinite loops.

Learn how functions act as self-contained blocks of code you call when needed, accept parameters, return values, and manage global and local scope to reuse code effectively.

Learn to extend Python functions with parameters and return values, use default parameters, and implement bounds checks for a move function that tracks position between start and end.

Understand how classes serve as blueprints for objects and manage state with fields and methods, including initialization. Explore inheritance and static members, with examples like move and take damage.

Demonstrate inheritance in Python by subclassing a game character into a player character, adding max health and lives, and overriding take damage and is dead while using super() to initialize.

Explore how static members belong to the class, using static variables and a static method to affect all game characters, and compare them with instance members and constants.

Review Python basics by covering variables, operators, collections, and classes; apply if statements, loops, and functions, and explore Pandas and NumPy for data analysis and machine learning.

Load the frequently asked questions CSV, convert it to a pandas DataFrame, drop null values, and train a tf-idf vectorizer on the questions and answers to prepare for chat interactions.

Build a faq chatbot by vectorizing questions, comparing user input with cosine similarity, selecting the closest match, and returning the corresponding answer in an interactive loop.

Build a context aware chatbot by defining a basic intent classifier with a patterns dictionary of keywords (greeting, access, expiry, release, revisit) and implement a classify method to test text.

Build a basic generative model for a chatbot by creating an answer generator that maps intents to responses, covering greeting, access, expiry, release, and revisited questions.

Test the chatbot by looping user input, classifying intents, and generating answers. Explore greeting handling and a default fallback, and discuss self-learning risks.