AWS: Model Training , Optimization & Deployment
Completed by Jesse Galdal-Gibbs
January 14, 2026
8 hours (approximately)
Jesse Galdal-Gibbs's account is verified. Coursera certifies their successful completion of AWS: Model Training , Optimization & Deployment
What you will learn
Explore built-in algorithms in Amazon SageMaker such as Linear Learner, XGBoost, LightGBM, and k-NN for ML model development.
Configure key training parameters like epochs, batch size, and steps to train and evaluate ML models effectively.
Compare real-time and batch inference approaches to determine the best strategy for model deployment.
Skills you will gain
- Category: Amazon Elastic Compute Cloud
- Category: Classification Algorithms
- Category: Continuous Deployment
- Category: Continuous Integration
- Category: Model Optimization
- Category: Cloud Deployment
- Category: Model Training
- Category: Debugging
- Category: Model Deployment
- Category: Model Evaluation
- Category: Predictive Modeling
