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Turbocharge your teams' skills on
Amazon SageMaker & simplify ML Workflows

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Participants can gain mastery over Amazon SageMaker with our SageMaker Training Program, thoughtfully designed for comprehensive learning. Each day targets specific objectives, blending introductory concepts, hands-on projects, and advanced topics. Prioritizing practical application with real-world case studies, interactive sessions, and continuous feedback, it fosters networking opportunities.

The course modules are structured to give an empirical value and understanding to the candidates. However, all course modules are highly customizable and can be structured to suit the requirements of your organization.

Course Outcome

Gain a comprehensive understanding of Amazon SageMaker and its role in machine learning workflows
Become proficient in navigating and utilizing the AWS cloud platform
Get familiarized with SageMaker components and can create and manage SageMaker notebooks effectively
Understand data requirements for SageMaker and can preprocess data for machine learning
Train models using SageMaker built-in algorithms and customize training jobs according to specific requirements
Comprehend hyperparameter tuning and other strategies for improving model performance

Why Mazenet?

  • Expert Faculty

    Our Faculty comprises of 300+ SMEs with many years of experience. All our trainers possess a minimum of 8+ years of experience.

  • Proven Track Record

    We have served over 200+ global corporate clients, consistently maintaining a 99% success rate in meeting training objectives for 300+ technologies with quick turnaround time.

  • Blended Learning

    We provide course content over any platform that our clients prefer. You can choose an exclusive platform or a combination of ILT, VILT, and DLP.

  • Learning Paths

    The learning paths are very defined with clear benchmarks. Quantitative assessments at regular intervals measure the success of the learning program.

  • Case Study

    We have amassed over 10,000 case studies to support training delivery. Candidates will be trained to work on any real-time business vertical immediately after the training.

  • 24*7 Global Availability

    We are equipped to conduct training on any day, date or time. We have delivered training pan India, Singapore, North America, Hong Kong, Egypt and Australia.

Key Features

  • Customized Training Modules

    Training programs are highly flexible with module customizations to suit the requirements of the business units.

  • Certification

    The training can be supplemented with appropriate certifications that are recognized across the industry.

  • Multi-language Support

    Course content can be delivered in English, Spanish, Japanese, Korean or any other language upon request.

  • Personalized Training Reports

    Candidates are assessed individually at regular intervals and are provided unique learning suggestions to suit their learning calibre.

  • Industry-Oriented Training

    Industry-oriented training, completing which, candidates can be immediately deployed for billable projects.

  • Diverse Training Platforms

    Choose from Instructor-Led Training, Virtual Instructor-Led Training, Digital Learning Platform and Blended Training platforms

Course Preview

  • Understanding the AWS cloud platform
  • Creating an AWS account and setting up Amazon SageMaker

  • Creating and managing SageMaker notebooks.
  • Understanding data requirements for SageMaker.
  • Preprocessing data for machine learning.

  • Training models using SageMaker built-in algorithms
  • Customizing training jobs with your own algorithms
  • Hyperparameter tuning with SageMaker
  • Strategies for improving model performance

  • Configuring endpoints for real-time predictions
  • Performing batch transformations with SageMaker
  • Managing and monitoring deployed models

  • Examining real-world applications of Amazon SageMaker
  • Case studies and success stories

  • Participant Q&A Session with Experts
  • Final Hands-on Project
  • Certification Ceremony and Closing Remarks