What You'll Learn
- Operationalize ML workflows using AWS SageMaker and MLOps best practices.
- Deploy and scale machine learning models using real-time and batch inference.
- Monitor model performance and implement automated retraining pipelines.
- Implement data security, governance, and compliance within AWS ML services.
- Optimize ML infrastructure for cost and performance on the AWS Cloud.
- Prepare for the MLA-C01 Certification exam with hands-on lab scenarios.
Prerequisites
Essential skills you should have beforehand:
- Basic understanding of AWS Cloud Infrastructure (S3, IAM, Lambda).
- Familiarity with Python and common ML libraries (Scikit-learn, TensorFlow).
- Knowledge of the Machine Learning Lifecycle (Training, Tuning, Inference).
Career & Salary Outlook
MLOps Engineer$120,000 - $175,000
AWS ML Specialist$135,000 - $190,000
Cloud AI Architect$150,000 - $210,000
Machine Learning Engineer$125,000 - $185,000
* Salaries vary based on location, experience, and company size.
Who Is This For?
DevOps Engineers
Data Engineers
Cloud Architects
Machine Learning Practitioners
IT Professionals seeking MLA-C01