Intro to Python
For AI

1Welcome and course overview

• Introduction to the bootcamp structure
• Setting expectations and goals
• Brief history of Python and its applications

2Basic Python concepts

• Variables and data types (integers, floats, strings, booleans)
• Print statements and string formatting
• Basic math operations in Python
• Using the input() function for user interaction

3Interactive exercises

• Writing and running simple Python scripts

4Hands-on project: Get to Know Someone

Development of a simple Python script that asks the user for their name, age, and whether they like ice cream or not. The script will then print out a message with this information.

1Conditional statements

• If, elif, and else statements
• Comparison operators
• Logical operators (and, or, not)

2Loops

• For loops and their applications
• While loops and when to use them
• Loop control statements (break, continue)

3Lists and basic list operations

• Creating and accessing list elements
• List methods (append, remove, len, etc.)
• Iterating through lists

4Hands-on project: Number Guessing Game

Students will develop a simple number guessing game using conditional statements and loops. The game will generate a random number between 1 and 100, and the user will have to guess it.

1Functions in Python

• Defining and calling functions
• Function parameters and return values
• Scope of variables (local vs. global)

2Built-in Python modules

• Importing and using modules
• Overview of common built-in modules (math, random, time)

3Introduction to external libraries

• Pip and package management (basic introduction)
• Importing and using external libraries

4Hands-on project: Personal Library Organizer

Students will develop a Python script that organizes their personal library. The script will allow users to add, remove, search, list, and recommend books in their collection.

1What is AI?

• Definition and brief history of AI
• Types of AI (narrow vs. general)
• AI vs Human Intelligence
• Applications of AI in real-world scenarios

2Key Components of AI

• Main components needed for AI systems

3Introduction to machine learning

• Definition and types of machine learning
• Supervised vs. unsupervised learning
• Reinforcement learning

4Neural Networks and Deep Learning

• Introduction to neural networks
• How neural networks work at a basic level
• Overview of deep learning
• Applications of deep learning in real-world scenarios

5Common Misconceptions about AI

• Debunking common myths and misconceptions about AI
• Ethical considerations in AI development

6Game: AI or Human?

Interactive game to test the audience's ability to distinguish between AI-generated and human-generated images