Course Overview
- Course Title: [ES] Curso de Certificación Profesional en Ingeniería de IA
- Instructor: Jet Drag Academy
- Target Audience:
- Advanced AI and machine learning practitioners
- Engineers seeking to transition from theory to production-level AI systems
- Prerequisites:
- Completion of a beginner or intermediate AI or machine learning course
- Solid understanding of Python programming, including experience with functions, classes, and libraries like NumPy and Pandas
- Familiarity with deep learning fundamentals, including neural networks and basic model architectures
- Previous experience with tools like Jupyter Notebook, TensorFlow, or PyTorch
- Practical knowledge of mathematics for AI, including linear algebra, probability, and calculus
- A computer (Windows, macOS, or Linux) with reliable internet access and the ability to install development tools
- Willingness to explore complex production-level systems and invest time in practical coding, model experimentation, and deployment workflows
Curriculum Highlights
- Key Topics Covered:
- Model tuning and optimization
- Convolutional Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs), LSTMs, and GRUs
- Transformers and attention mechanisms
- Transfer learning and fine-tuning
- AI agents for autonomous decision-making
- MLOps practices
- Key Skills Learned:
- Adjust and optimize machine learning models using advanced techniques
- Build and train CNNs for image classification and computer vision tasks
- Develop RNNs, LSTMs, and GRUs for time series and sequence modeling
- Understand and implement transformers and attention mechanisms
- Apply transfer learning to fine-tune pre-trained models
- Design and analyze AI agents for autonomous decision-making
- Use TensorFlow and PyTorch for deep learning projects
Course Format
- Duration: 16 hours of on-demand video
- Format: Self-paced online course
- Resources:
- 5 articles
- 5 downloadable resources
- Access on mobile and TV
- Certificate of completion