The Python Programming Course for AI offers a comprehensive course to learn how to Programming in Python with a focus on artificial intelligence and machine learning. Through these teaching modules, students will master everything from the Python basics, the data processing and visualisation up to the creation and training of AI models using libraries such as NumPy, Pandas, Matplotlib, Scikit-learn and TensorFlow/Keras.
Cross-cutting
AI Academy
10 a.m.
Python Programming for AI
AI Academy
10 a.m.
Introduction
Objectives
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To know the Python syntax and basic structures to develop efficient scripts.
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Handling and processing data with Pandas and NumPy for AI applications.
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View information via Matplotlib and Seaborn for exploratory analysis.
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Understanding the fundamentals of machine learning and its main algorithms.
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Create, train and assess classification, regression and clustering models.
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Getting started with the neural network development and practical applications in image and text recognition.
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Apply best practice in programming and data pre-processing for AI projects.
Table of Contents
TEACHING UNIT 1. PYTHON BASICS FOR AI
Python: syntax and basic structures
Data types and control structures
Functions, modules and packages
Error handling and debugging
Using essential libraries: NumPy and Pandas
Reading and processing data (CSV, JSON, etc.)
TEACHING UNIT 2. SCIENTIFIC PROGRAMMING AND DATA PROCESSING
Advanced data manipulation with Pandas
Visualisation using Matplotlib and Seaborn
Linear algebra and matrix operations with NumPy
Data pre-processing for AI
Introduction to Scikit-learn and ML workflows
Splitting data: training, validation and testing
TEACHING UNIT 3. INTRODUCTION TO AI WITH PYTHON
Fundamentals of Machine Learning
Classification, regression and clustering with Scikit-learn
An Introduction to Neural Networks with TensorFlow/Keras
Creating and training basic models
Model evaluation: metrics and cross-validation
Practical applications: image and text recognition
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