Practical Data Science with Amazon SageMaker Course

Master ML with Amazon SageMaker

Get real-world insights from certified instructors

Apply machine learning to tackle real business challenges

Gain in-demand ML skills and boost your job prospects

Learn at your own pace with flexible, instructor-led sessions

Master the full ML workflow and its practical applications

Convenient and hassle-free payment plans

4.8/5

5469 Enrolled

Overview

What our training includes:

Learn data preparation techniques using SageMaker Data Wrangler
Train models with powerful algorithms like XGBoost on SageMaker
Evaluate and optimize models with hyperparameter tuning using SageMaker
Deploy models to real-time endpoints with Amazon SageMaker
Master MLOps practices for automating and monitoring model deployment
Hands-on experience with no-code ML using Amazon SageMaker Canvas

Learning Objectives

Upon finishing the training, you will:

Master data preparation using SageMaker Data Wrangler for efficient data processing

Train models with advanced algorithms like XGBoost and optimize with hyperparameter tuning

Deploy machine learning models to real-time endpoints using Amazon SageMaker for predictions

Apply MLOps practices for automating, monitoring, and managing deployed models

Gain hands-on experience with no-code machine learning through SageMaker Canvas

Ready to get started?

Overall ratings by our students

Upcoming sessions

Our Trainers

Learners Point has a reputation for high-quality training that makes a difference in people's lives. We undertake a practical and innovative approach to working closely with businesses to improve their workforce. Our expertise is wide-ranging with ample support from our expert trainers who are globally recognized and hold a diverse set of experiences in their field of expertise. We are proud of our instructors who take ownership of our distinctive and comprehensive training methodologies, help our students imbibe those with ease, and accomplish gracefully.

We at Learners Point believe in encouraging our students to embark upon a journey of lifelong learning and self-development, with the aid of our comprehensive and distinctive courses tailored to current market trends. The manifestation of our career-oriented approach is what we assure through a pleasant professional enriched environment with cutting-edge technology, and an outstanding while highly acknowledged training staff that uses up-to-date methodologies and quality course material. With our aim to mold professionals to be future leaders, our industry expert trainers provide the best in town mentorship to our students while endowing them with the thirst for knowledge and inspiring them to strive for professional and human excellence.

KHDA Certificate

Earn a KHDA attested Course Certificate. The Knowledge and Human Development Authority (KHDA) is the educational quality assurance and regulatory authority of the Government of Dubai, United Arab Emirates.

Learners Point Certificate

Earn a Course Completion Certificate, an official Learners Point credential that confirms that you have successfully completed a course with us.

Related courses

Curriculum

Benefits of machine learning (ML)
Types of ML approaches
Framing the business problem
Prediction quality
Processes, roles, and responsibilities for ML projects

Data analysis and preparation
Data preparation tools
Demonstration: Review Amazon SageMaker Studio and Notebooks
Hands-On Lab: Data Preparation with SageMaker Data Wrangler

Steps to train a model
Choose an algorithm
Train the model in Amazon SageMaker
Hands-On Lab: Training a Model with Amazon SageMaker
Amazon CodeWhisperer
Demonstration: Amazon CodeWhisperer in SageMaker Studio Notebooks

Model evaluation
Model tuning and hyperparameter optimization
Hands-On Lab: Model Tuning and Hyperparameter
Optimization with Amazon SageMaker

Model deployment
Hands-On Lab: Deploy a Model to a Real-Time Endpoint
and Generate a Prediction

Responsible ML
ML team and MLOps
Automation
Monitoring
Updating models (model testing and deployment)

Different tools for different skills and business needs
No-code ML with Amazon SageMaker Canvas
Demonstration: Overview of Amazon SageMaker Canvas
Amazon SageMaker Studio Lab
Demonstration: Overview of SageMaker Studio Lab
(Optional) Hands-On Lab: Integrating a Web Application
with an Amazon SageMaker Model Endpoint

Frequently asked questions

The Practical Data Science with Amazon SageMaker course is a hands-on training program designed to teach you how to build, train, and deploy machine learning models using AWS SageMaker. This course covers data preparation, model optimization, real-time deployment, and MLOps practices, providing you with the essential tools and skills needed to apply machine learning to real-world business challenges. By the end of the course, you'll be proficient in SageMaker tools like Data Wrangler, XGBoost, and SageMaker Canvas.

We recommend that participants of this course have:
• AWS Technical Essentials
• Entry-level knowledge of Python programming
• Entry-level knowledge of statistics

The Practical Data Science with Amazon SageMaker certification is highly recognized in industries that use AWS tools for machine learning. It’s particularly valued in regions like North America, Europe, the Middle East, and Asia, where AWS adoption is high. This certification validates your expertise in machine learning and AWS services, enhancing your professional credibility.

After completing this course, you can pursue roles such as:

Data Scientist: Build and deploy machine learning models to solve business problems
Machine Learning Engineer: Design, develop, and implement ML models at scale
DevOps Engineer: Deploy and manage machine learning models in production environments
AI/ML Consultant: Provide expert guidance on ML model development and deployment

This course offers flexible learning options, including online self-paced modules, live instructor-led sessions, and recorded classes for review. You can study at your own pace and schedule, making it ideal for working professionals who need to balance their training with their job responsibilities.

You will master a range of AWS tools, including Amazon SageMaker Studio, SageMaker Data Wrangler, SageMaker Canvas, and XGBoost. Additionally, you will learn MLOps techniques for automating model deployment and monitoring, enabling you to manage machine learning models effectively in production.