Early-Bird Pricing (50% off)

I am currently working on building this course. When it is released, there will be three pricing options:

  • $10/month
  • $30/year
  • $50 lifetime access


However, you may purchase lifetime access now for only $25.  That's 50% off. You will never have to pay again for this course and you will be notified when it's ready (likely May 2025).

Email me if you have any questions.

Ben

[email protected]

What you'll learn

These are some of the topics that the course will cover, en route to helping you pass the Professional Machine Learning Engineer exam.

  • Generative AI solution development including implementation of retrieval augmented generation (RAG) applications using Vertex AI Agent Builder

  • Responsible AI practices, including model explainability, bias monitoring, and building secure AI systems that protect against exploitation

  • MLOps and pipeline automation using Vertex AI Pipelines, Kubeflow, and CI/CD for model deployment and automated retraining

  • Scaling models from prototype to production, including distributed training, hardware selection (GPUs, TPUs), and hyperparameter tuning

  • Serving and scaling ML models with both batch and online inference, model registry organization, and A/B testing strategies

  • Performance optimization techniques for ML models in production, including tuning for latency, memory usage, and throughput

  • Monitoring AI solutions for training-serving skew, feature drift, and performance metrics using Vertex AI Model Monitoring

  • Model prototyping using Jupyter notebooks with various backends (Vertex AI Workbench, Colab Enterprise) and integration with common ML frameworks

  • Data management and preprocessing across Google Cloud services (BigQuery, Cloud Storage, Vertex AI) with focus on organizing different data types

  • Low-code AI solutions including BigQuery ML models, ML APIs, foundation models, and AutoML for different data types