Practical Data Science with Amazon SageMaker Course in Saudi Arabia

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

4600 EnrolledEnrolled Learners

4.8/5

4600 EnrolledEnrolled Learners

Overview

What you will master with us

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

Upcoming sessions

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

Meet your Trainer

Our Trainer

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.

Learning Outcomes

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?

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.

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Frequently asked questions

Our Practical Data Science with Amazon SageMaker course in KSA is a comprehensive program that covers end-to-end machine learning workflows. It teaches you how to prepare datasets, train models, evaluate performance, and deploy them using Amazon SageMaker. With hands-on labs and real-world applications, the course ensures that you gain the practical skills needed to solve business problems using machine learning, positioning you as a valuable asset in the growing data science field.

To enrol in this course, you should have a basic understanding of programming and data science concepts. A background in Python or a similar programming language is beneficial. While prior machine learning knowledge is not mandatory, it will be helpful. The course is suitable for professionals looking to upskill in data science and machine learning, including analysts, engineers, and developers.

This training is ideal for aspiring data scientists, ML engineers, developers, analysts, and even non-technical professionals interested in applied AI. Whether you're new to ML or have some experience in Python or data analytics, this course offers the practical, step-by-step guidance needed to gain real-world skills using Amazon SageMaker.

Participants gain hands-on experience in the entire machine learning lifecycle, from data preparation with SageMaker Data Wrangler, model building, and hyperparameter tuning, to deploying models using real-time endpoints. You also get exposure to no-code ML with SageMaker Canvas, responsible AI practices, and MLOps automation. We make you job-ready in operationalising ML solutions.

Our learners can pursue roles such as Data Scientist, Machine Learning Engineer, AI Developer, and Data Analyst across several industries in Saudi Arabia.

Yes, this Practical Data Science with Amazon SageMaker certification covers no-code ML using SageMaker Canvas, making it accessible for non-coders. You gain enough technical grounding to effectively manage ML projects, evaluate model performance, and communicate better with your data teams. This adds a strategic edge to your leadership role.