Practical Data Science with Amazon SageMaker Course in Australia
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 complete ML workflow and its practical applications
Convenient and hassle-free payment plans
4.8/54.8/5Overview
What you will learn:
- Learn data preparation techniques using Amazon SageMaker Data Wrangler
- Train models with powerful algorithms like XGBoost on Amazon SageMaker
- Evaluate and fine-tune models with hyperparameter optimisation in SageMaker
- Deploy models to real-time endpoints with Amazon SageMaker for seamless integration
- Master MLOps practices to automate and monitor model deployment
- Gain hands-on experience in no-code machine learning with 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 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.
Learning Outcomes
Successful completion of the training will help professionals in the following ways:
1
Master data preparation with SageMaker Data Wrangler to streamline data processing
2
Train models using advanced algorithms like XGBoost and fine-tune with hyperparameter optimisation
3
Deploy machine learning models to real-time endpoints with Amazon SageMaker for seamless predictions
4
Implement MLOps practices for automating, monitoring, and managing model deployments
5
Gain practical experience in no-code machine learning using SageMaker Canvas
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
The Practical Data Science with Amazon SageMaker course in Australia trains professionals to use Amazon SageMaker for machine learning. It includes training on preparing data, training, and tuning machine learning models to deploy them in live production environments. Professionals can leverage the robust tools of SageMaker to simplify machine learning workflows and spur innovation.
Additional resources such as career services, job placement assistance, and networking opportunities are often available. You'll also gain access to a community of data science professionals to share knowledge and opportunities.
Compared to other certifications, our Practical Data Science with Amazon SageMaker course provides a dedicated, hands-on machine learning experience with practical applications. It is most useful for those specialising in Amazon's machine learning environment.
Our course is specifically tailored for working professionals. You can take the course online and attend live sessions at convenient hours. The self-paced modules of the course also enable you to learn according to your schedule, making it more convenient for you to manage work and study.
The certification gives you an edge in the employment market, proving your proficiency in Amazon SageMaker. This popular machine learning platform enhances your credibility and provides new career prospects, making you more desirable to leading AI and data science employers.
Industries are increasingly adopting machine learning and AI technologies. Some are:
- Tech
- Finance
- Healthcare
- E-commerce
- Telecommunications
Completing our Practical Data Science with Amazon SageMaker course opens doors to these fast-growing fields.
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