This 5-day training provides participants with a deep dive into AWS SageMaker, Amazon’s fully managed machine learning platform. The course starts by introducing AWS machine learning fundamentals, data preparation techniques, and the SageMaker environment. Participants will gain a clear understanding of SageMaker’s built-in algorithms, supported frameworks, and the flexibility to bring their own models.
Through a series of hands-on labs, learners will work with regression, classification, and advanced algorithms such as XGBoost, PCA, Factorization Machines, and DeepAR for time-series forecasting. The training emphasizes practical skills such as preparing datasets, tuning hyperparameters, training and deploying models, and using SageMaker endpoints for real-time inference.
In addition, the course covers integration scenarios with other AWS services, including API Gateway and Lambda, to create production-ready ML pipelines. Learners also explore key AI services such as Comprehend, Translate, Polly, Lex, and Rekognition to broaden their skillset beyond core ML
By the end of the training, participants will be able to design, train, and deploy scalable ML solutions on AWS SageMaker, manage model performance, and apply best practices to build AI-powered applications. The program also provides a strong foundation for professionals preparing for the AWS Machine Learning Specialty certification.
Duration: 5 Days
Course Code: BDT 520
Learning Objectives:
After this training, participants will be able to:
Training material provided: Yes (Digital format)
