Hands-on guide to Amazon SageMaker, MLOps, Deep Learning, and AI Services like Rekognition. Pass the MLS-C01 exam!
Description
Machine Learning is transforming our world, and Amazon Web Services (AWS) is the number one platform where this revolution is happening. To build a future-proof career in technology, mastering the AWS Machine Learning stack is no longer just an advantage—it’s a necessity. This course, fully updated for August 2025, is the only resource you need to go from a beginner to a confident AWS ML practitioner.
This is not just a theoretical overview. It is a comprehensive, hands-on journey designed to give you the practical skills you’ll use on the job and need to pass the AWS Certified Machine Learning – Specialty (MLS-C01) exam.
Who is this course for?
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Data Scientists who want to break free from local machine limitations and scale their models in the cloud.
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Software Developers aiming to build the next generation of intelligent, AI-powered applications.
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Solutions Architects who need to design robust, scalable, and cost-effective ML infrastructure.
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Aspiring ML Engineers looking for a structured path to mastering the most in-demand cloud skills.
What will you learn by doing? We will cover the entire AWS Machine Learning ecosystem in depth, with a focus on practical application:
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Master Amazon SageMaker: Go from A-to-Z with the flagship AWS ML service. You will perform data labeling, build processing jobs, train models with built-in algorithms and your own custom code, perform hyperparameter tuning, and deploy production-ready endpoints.
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Implement MLOps: Learn the critical skill of automating ML workflows. We will build robust CI/CD pipelines for your models using SageMaker Pipelines and AWS Step Functions.
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Leverage AI Services: Go beyond model building and learn to integrate powerful, pre-trained AI services like Amazon Rekognition (image/video analysis), Comprehend (NLP), and Transcribe (speech-to-text) directly into your applications.
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Build Data Pipelines for ML: Understand how to properly ingest, store, and process massive datasets using S3, AWS Glue, and Athena.
By the end of this course, you won’t just be prepared for the certification exam—you’ll be ready for the job. Enroll today and take the definitive step to becoming an expert in cloud machine learning.
| Total Students | 29 |
|---|---|
| Duration | 541 questions |
| Language | English (US) |
| Original Price | |
| Sale Price | 0 |
| Number of lectures | 0 |
| Number of quizzes | 5 |
| Total Reviews | 0 |
| Global Rating | 0 |
| Instructor Name | Bikash Mallik |
Course Insights (for Students)
Actionable, non-generic pointers before you enroll
Student Satisfaction
78% positive recent sentiment
Momentum
Steady interest
Time & Value
- Est. time: 541 questions
- Practical value: 5/10
Roadmap Fit
- Beginner → → Advanced
Key Takeaways for Learners
- Hands-on practice
- Real-world examples
- Project-based learning
Course Review Summary
Signals distilled from the latest Udemy reviews
What learners praise
Clear explanations and helpful examples.
Watch-outs
No consistent issues reported.
Difficulty
Best suited for
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