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On this accelerated Amazon SageMaker Studio for Data Scientists course, you will learn to boost productivity at every step of the ML lifecycle with Amazon SageMaker Studio for Data Scientists from an expert AWS instructor.
This 2 day, advanced level course helps experienced data scientists build, train, and deploy ML models for any use case with fully managed infrastructure, tools, and workflows to reduce training time from hours to minutes with optimized infrastructure. This course includes presentations, demonstrations, discussions, labs, and at the end of the course, you’ll practice building an end-to-end tabular data ML project using SageMaker Studio and the SageMaker Python SDK.
Accelerate the preparation, building, training, deployment, and monitoring of ML solutions by using Amazon SageMaker Studio Use the tools that are part of SageMaker Studio to improve productivity at every step of the ML lifecycle And much more
At the end of this course, you’ll achieve your Amazon SageMaker Studio for Data Scientists certification.
Through Firebrand’s Lecture | Lab | Review methodology, you’ll get certified at twice the speed of the traditional training and get access to courseware, learn from certified instructors, and train in a distraction-free environment.
This course is ideal for:
Module 1: Amazon SageMaker Setup and Navigation
Module 2: Data Processing Use Amazon SageMaker Studio to collect, clean, visualize, analyze, and transform data.
Module 3: Model Development Use Amazon SageMaker Studio to develop, tune, and evaluate an ML model against business objectives and fairness and explainability best practices.
Module 4: Deployment and Inference Use Model Registry to create a model group; register, view, and manage model versions; modify model approval status; and deploy a model.
Module 5: Monitoring Configure a SageMaker Model Monitor solution to detect issues and initiate alerts for changes in data quality, model quality, bias drift, and feature attribution (explainability) drift.
Module 6: Managing SageMaker Studio Resources and Updates List resources that accrue charges.
The Capstone lab will bring together the various capabilities of SageMaker Studio discussed in this course. Students will be given the opportunity to prepare, build, train, and deploy a model using a tabular dataset not seen in earlier labs. Students can choose among basic, intermediate, and advanced versions of the instructions. Capstone Lab: Build an End-to-End Tabular Data ML Project Using SageMaker Studio and the SageMaker Python SDK.
At the end of this accelerated course, you’ll achieve your Amazon SageMaker Studio for Data Scientists.
Your accelerated course includes:
Before attending this accelerated course, you should have:
We interview all applicants for the course on their technical background, degrees and certifications held, and general suitability. If you get through this screening process, it means you stand a great chance of passing.
Firebrand Training is an immersive training environment. You must be committed to the course. The above prerequisites are guidelines, but many students with less experience have other background or traits that have enabled their success in accelerated training through Firebrand Training.
If you have any doubts as to whether you meet the pre-requisites please call 09 - 31 587 431 and speak to one of our enrolment consultants, who can help you with a training plan.
We've currently trained 134.561 students in 12 years. We asked them all to review our Accelerated Learning. Currently,
96,41% have said Firebrand exceeded their expectations:
"Very impressed with the dedication from the instructor and how well structured the sessions are. The course is very intense since it's only 3 days long, however, the quality of the training makes it worthwhile. I'd recommend going in person since you will find it much easier to focus and likely get more out of the course overall."
Simon Brown, Softcat. (8/9/2023 (Friday) to 10/9/2023 (Sunday))
"Enrolling in Firebrand Training's AWS Solution Architect Associate course online instructor-led program was an outstanding decision for my career. The course was not only comprehensive but also delivered by highly knowledgeable instructors who made complex AWS concepts easy to grasp. The interactive nature of the online sessions and the practical hands-on labs ensured that I gained a deep understanding of AWS solutions and best practices. I can confidently say that Firebrand Training played a pivotal role in helping me achieve AWS Solution Architect Associate certification. I highly recommend this course to anyone looking to excel in AWS cloud architecture."
Omar Anwar. (4/9/2023 (Monday) to 7/9/2023 (Thursday))
"Course provided all the key knowledge required to prepare me for my organisation currently introducing AWS migrations"
AB, Marketaxess. (31/7/2023 (Monday) to 1/8/2023 (Tuesday))
"Trainer was excellent, a lot of information, great experience"
Olawale Abdullahi, BPP University. (31/7/2023 (Monday) to 1/8/2023 (Tuesday))
"The trainer provided excellent delivery and commitment to enabling me to understand the AWS platform, services and how they interact with each other. the topics where discussed in great depth with live demos and real world analogies and examples to help embed the knowledge rather than just reading from a slide deck. the course is extremely intense but the way the content delivery was structured with a mix of slides, live demos, labs and open classroom discussions helped enable me to gain a great insight into the AWS platform."
Matthew Bingham, Softcat PLC. (24/7/2023 (Monday) to 27/7/2023 (Thursday))
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