AI Engineering Training and Certification in Metro Manila, Philippines

This training on AI Engineering provides participants with a comprehensive understanding of designing, building, and deploying AI systems. The course focuses on the core concepts of machine learning, deep learning, and AI system architecture. Participants will gain hands-on experience with frameworks and tools used for data preprocessing, model development, and deployment in real-world applications. The training also explores best practices in scaling and managing AI solutions.

Foundations and Model Development

• Session 1: Introduction to AI Engineering

  • Overview of the AI lifecycle.
  • Tools and frameworks for AI Engineering.
  • Key principles of scalable and maintainable AI systems.

• Session 2: Data Preprocessing and Feature Engineering

  • Techniques for data cleaning and transformation.
  • Feature selection and extraction for model optimization.

• Session 3: Building and Training Models

  • Developing AI models using TensorFlow and PyTorch.
  • Training, validation, and evaluation best practices.

Integration, Deployment, and Optimization

• Session 4: AI Integration and Deployment

  • Deploying AI models as APIs using Flask or FastAPI.
  • Containerizing AI applications with Docker.

• Session 5: Scaling AI Systems

  • Real-time and batch processing pipelines using Apache Kafka and Apache Spark.
  • Techniques for optimizing AI model inference.

• Session 6: Responsible AI and Monitoring

  • Addressing bias and ethical considerations in AI.
  • Tools for monitoring and managing AI systems in production.

• Hands-On Lab

This training is designed to provide participants with the skills and knowledge required to engineer scalable and reliable AI systems, equipping them to meet the demands of AI-driven industries.