Description
The Practical Data Science With Amazon SageMaker course explores the practical application of Amazon SageMaker in solving real-world use cases using Machine Learning. Participants will gain hands-on experience in each phase of the Data Science workflow, including dataset analysis, visualization, data preparation, and feature engineering.
Moreover, the course focuses on building, training, tuning, and deploying models with Amazon SageMaker, providing practical insights into its implementation. A specific use case covered in the course is customer retention analysis, which demonstrates the practical application of ML in optimizing customer loyalty programs.
Interactive Training with Zoom
Join our Zoom-based courses to benefit from real-time discussions, immediate solutions to problems, and guidance from our seasoned instructors.
Audience
Data Scientists
Developers
Did you know? According to Global Knowledge's 2022 IT Skills and Salary Report, AWS Certified Solutions Architect - Associate was one of the top-paying IT certifications, with an average salary of over $130,000.
Prerequisites
Commercial experience with Python
Commerical experience with Machine Learning
"The ones who are crazy enough to think they can change the world, are the ones that do." - Steve Jobs
Deliverables
Assemble a training dataset
Develop and assess a machine learning model
Automate the fine-tuning of a machine learning model
Create a machine learning model that can be used in production
Examine the output of machine learning models critically
Earn a Certificate
Earn a certificate to showcase your skills on LinkedIn, enhancing your professional credibility.
"Cloud training initiatives can have a return on investment of up to 2–6x." - Source: ACG: The ROI of Cloud Training
