1. Introduction to Programming and Python
Fundamental programming and Python concepts, such as: Variables and Data Types, Basic Operations.
2. Control Flow
Using conditional statements, logical and comparison operators, nested conditions.
3. Loops and Collections
Introduction to loops and loop control, lists and list operations and dictionaries.
4. Functions and Modules
What are functions and how to define them. Using built-in Python modules.
5. File I/O and Error Handling
Reading from and writing to text files. Introduction to 'try', 'except', storing and retrieving data using JSON.
6. Introduction to AI and Machine Learning
What is AI? How does it relate to machine learning and data? Introduction to basic AI tools and libraries.
7. Data Analysis and Visualization
Loading and cleaning data, identifying missing or incorrect data, sorting and filtering data.
8. Intro to Machine Learning Models
Understanding supervised learning. Classification vs regression. Using tools to train a basic classification model.
9. Model Evaluation and Improvement
Splitting data into training and testing sets. Understanding model performance and basic tuning.
10. Final Project and Presentations
Students choose and build a simple AI-powered application using their knowledge.