Amazon SageMaker Studio for Data Scientists Training in Oman

Build, train, and deploy models with Amazon SageMaker Studio

Gain real-world experience in data processing, training, and deployment

Receive guidance from top industry professionals

Master everything from data wrangling to model optimisation

Gain in-demand skills for high-level data science roles

Flexible and intensive Training

Convenient and hassle-free payment plans

4.7/5

5517 EnrolledEnrolled Learners

4.7/5

5517 EnrolledEnrolled Learners

Overview

What our training includes

Master Amazon SageMaker Studio for end-to-end ML model development
Use SageMaker Data Wrangler and AWS Glue for data processing
Leverage SageMaker Experiments for model training and tuning
Learn automated ML with SageMaker Autopilot and bias detection
Deploy models using SageMaker Pipelines and Model Registry
Gain hands-on experience with SageMaker Debugger for performance optimisation

Upcoming sessions

Curriculum

JupyterLab Extensions in SageMaker Studio

Demonstration: SageMaker user interface demo

Using SageMaker Data Wrangler for data processing

Hands-On Lab: Analyze and prepare data using Amazon SageMaker Data Wrangler

Using Amazon EMR

Hands-On Lab: Analyze and prepare data at scale using Amazon EMR

Using AWS Glue interactive sessions

Using SageMaker Processing with custom scripts

Hands-On Lab: Data processing using Amazon SageMaker Processing and SageMaker

Python SDK

SageMaker Feature Store

Hands-On Lab: Feature engineering using SageMaker Feature Store

SageMaker training jobs

Built-in algorithms

Bring your own script

Bring your own container

SageMaker Experiments

Hands-On Lab: Using SageMaker Experiments to Track Iterations of Training and Tuning

SageMaker Debugger

Hands-On Lab: Analyzing, Detecting, and Setting Alerts Using SageMaker Debugger

Automatic model tuning

SageMaker Autopilot: Automated ML

Demonstration: SageMaker Autopilot

Bias detection

Hands-On Lab: Using SageMaker Clarify for Bias and Explainability

SageMaker Jumpstart

SageMaker Model Registry

SageMaker Pipelines

Hands-On Lab: Using SageMaker Pipelines and SageMaker Model Registry with SageMaker

Studio

SageMaker model inference options

Scaling

Testing strategies, performance, and optimization

Hands-On Lab: Inferencing with SageMaker Studio

Amazon SageMaker Model Monitor

Discussion: Case study

Demonstration: Model Monitoring

Accrued cost and shutting down

Updates

Environment setup

Challenge 1: Analyze and prepare the dataset with SageMaker Data Wrangler

Challenge 2: Create feature groups in SageMaker Feature Store

Challenge 3: Perform and manage model training and tuning using SageMaker Experiments

(Optional) Challenge 4: Use SageMaker Debugger for training performance and model

optimization

Challenge 5: Evaluate the model for bias using SageMaker Clarify

Challenge 6: Perform batch predictions using model endpoint

(Optional) Challenge 7: Automate full model development process using SageMaker Pipeline

Meet your Trainer

Our Trainers

We take immense pride in our skilled instructors and trainers who excel in their chosen fields. Our trainers are globally recognised for their expertise and experience.Learners Point adopts a data driven research approach to learning so the experience is highly customizable and thoroughly engaging for learners from all walks of life. The sessions are classroom-based and led by an instructor. For those who seek more flexibility, we also offer high quality live and interactive sessions online.

Learning Outcomes

After you complete this training, you will be able to:

Learn data processing with SageMaker Data Wrangler and AWS Glue for seamless ML workflows

Use SageMaker Debugger to optimise model performance for real-time training insights & alerts

Automate machine learning pipelines with SageMaker Autopilot & SageMaker Pipelines

Master Model deployment and version control using SageMaker Model Registry

Identify and mitigate bias using SageMaker Clarify to ensure fair and explainable models

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Frequently asked questions

Our Amazon SageMaker Studio for Data Scientists Training in Oman is an advanced training ideal for experienced data scientists. This course helps you to build, train, and deploy machine learning models with Amazon SageMaker Studio. Our curriculum includes 6 in-depth modules and one capstone project. The course focuses on data wrangling, model optimisation, automated machine learning, deployment strategies, and real-time monitoring.

Our Amazon SageMaker Studio for Data Scientists course is a unique training program. This course specifically focuses on Amazon SageMaker, one of the most powerful ML platforms. Unlike other data science courses, this training deals with AWS-specific tools and services. Learners gain specialised knowledge directly applicable to real-world projects using AWS.

Apart from Data Scientists, our course is ideal for Machine Learning professionals and anyone who wants to upskill themselves with AWS tools. This course is perfect for broadening your knowledge in cloud-based data science and the capabilities of Amazon SageMaker Studio. With this training, candidates stand out in the competitive field of data science in Oman.

Not at all. While the course is aimed at professionals, it is structured with guided labs and real-world use cases that help newer learners build confidence. If you understand basic ML principles, you’ll find this Amazon SageMaker Studio training highly valuable and career-boosting.

After completing the Amazon SageMaker Studio course, individuals can apply for the following in-demand job roles in Oman:

Data Engineer
Machine Learning Engineer
AI & ML Specialist
Model Operations Engineer
Cloud Data Architect

The key topics that are covered in this course are mentioned below:

Setting up Amazon SageMaker Studio
Data Processing Using SageMaker Data Wrangler & EMR
Model Development using SageMaker Experiments & Autopilot
Model Optimisation with SageMaker Debugger
Model Monitoring using SageMaker Model Monitor
Bias Detection with SageMaker Clarify

Yes, this training is designed for busy professionals. We offer flexible scheduling options including evening or weekend classes, along with recorded sessions and self-paced lab access. We make sure you learn at your convenience without interrupting your work schedule.