Programa del Curso

Introduction to Artificial Intelligence

  • What is AI and where is it used?
  • AI vs. Machine Learning vs. Deep Learning
  • Popular tools and platforms

Python for AI

  • Python basics refresher
  • Using Jupyter Notebook
  • Installing and managing libraries

Working with Data

  • Data preparation and cleaning
  • Using Pandas and NumPy
  • Visualization with Matplotlib and Seaborn

Machine Learning Basics

  • Supervised vs. Unsupervised Learning
  • Classification, regression, and clustering
  • Model training, validation, and testing

Neural Networks and Deep Learning

  • Neural network architecture
  • Using TensorFlow or PyTorch
  • Building and training models

Natural Language and Computer Vision

  • Text classification and sentiment analysis
  • Image recognition basics
  • Pre-trained models and transfer learning

Deploying AI in Applications

  • Saving and loading models
  • Using AI models in APIs or web apps
  • Best practices for testing and maintenance

Summary and Next Steps

Requerimientos

  • An understanding of programming logic and structures
  • Experience with Python or similar high-level programming languages
  • Basic familiarity with algorithms and data structures

Audience

  • IT systems professionals
  • Software developers seeking to integrate AI
  • Engineers and technical managers exploring AI-based solutions
 40 Horas

Número de participantes


Precio por Participante​

Próximos cursos

Categorías Relacionadas