Python e IA para principiantes: aprenda, cree y explore proyectos de IA

In this hands-on class, students will explore the fundamentals and practical applications of Artificial Intelligence (AI) using Python. Designed for learners with basic Python knowledge, this course will guide them through the entire AI workflow—from data scraping to model deployment, while focusing on hands-on projects that bring AI concepts to life.

What Will Be Taught?

Data Scraping: Learn how to collect data from websites using BeautifulSoup.
Data Processing/Cleaning: Understand how to clean and prepare raw data for analysis.
Data Transformation: Explore techniques for transforming data into a usable format.
Exploratory Data Analysis (EDA): Use tools like Pandas and Matplotlib to analyze and visualize data patterns.
AI Model Selection: Understand how to choose the right machine learning models for different tasks.
Model Training: Learn to train AI models using popular libraries like Scikit-learn.
Model Evaluation: Evaluate model performance using various metrics.
Deployment: Deploy models with Flask and make them accessible online.
Monitoring and Maintenance: Learn best practices for monitoring and maintaining deployed models.
Class Structure and Teaching Style:

Each lesson is designed to be interactive and engaging, with a mix of lectures, hands-on coding, and project work. Students will work on real-world AI projects, using tools like Google Colab or Jupyter Notebooks to build and deploy their models. My approach focuses on creating a collaborative environment where students can troubleshoot, ask questions, and work through challenges together. Expect a balance of theory and practical work with lots of opportunities to experiment with AI techniques.

Student Interaction:

Learners will actively participate in discussions, complete coding exercises, and share their progress with the class. I will be available for Q&A and feedback during each session to ensure personalized attention. Interactive quizzes and group discussions will reinforce key concepts.

Tools and Platforms:

Programming Languages: Python
Libraries: Pandas, Numpy, Scikit-learn, Matplotlib, Seaborn, BeautifulSoup
Development Platforms: Google Colab, Jupyter Notebooks
Deployment Tools: Flask
This course provides students with a comprehensive understanding of AI workflows, preparing them for future projects and further learning in the AI field.