QUICK INFORMATION
Duration
Level
Mode
Fees
Certificate Validity
Recognition
Placement Support
Language
Industry Rating
Time / Week
Avg Completion
Certification Overview
The AWS Certified Machine Learning - Specialty (MLS-C01) is a high-level, technical certification designed for professionals who perform development or data science roles. It covers the end-to-end process of building machine learning models on AWS, including data engineering, exploratory data analysis, modeling, machine learning implementation, and operations. Candidates must demonstrate deep expertise in choosing the right AWS services, such as Amazon SageMaker, AWS Glue, and Amazon Kinesis, to solve complex machine learning challenges effectively. This credential is highly respected in the cloud-native AI space and signals to employers that the holder can optimize AI workflows for scalability, performance, and cost-efficiency.
What You Will Learn
Advantages
Career Opportunities
Companies That Value This Certification
Amazon
Technology
Netflix
Entertainment
Accenture
Consulting
Capital One
Finance
Airbnb
Travel Tech
Deloitte
Consulting
IBM
Technology
Where To Get This Certification
AWS Training & Certification
Exam Readiness: AWS Certified Machine Learning - Specialty
Duration: Self-paced
Fees: Free
Mode: Online
Rating: 4.5/5
Udemy
AWS Certified Machine Learning Specialty 2024 - Hands On
Duration: 25 hours
Fees: $20
Mode: Video
Rating: 4.7/5
A Cloud Guru
AWS Certified Machine Learning - Specialty
Duration: 40 hours
Fees: $40/mo subscription
Mode: Online
Rating: 4.8/5
Whizlabs
AWS Certified Machine Learning Specialty Practice Tests
Duration: Self-paced
Fees: $30
Mode: Simulation
Rating: 4.4/5
Coursera
AWS Machine Learning Specialization
Duration: 6 months
Fees: $49/mo
Mode: Online
Rating: 4.6/5
Fee Breakdown
$300
Minimum Fee
$500
Average Fee
$1500
Premium Fee
$300
Exam Fees
$150
Renewal Fees
None
Hidden Costs
Eligibility
Minimum Qualification
Bachelor's degree or equivalent experience
Recommended Background
1-2 years of experience using AWS to develop, architect, or run ML workloads
Age Requirement
18+
Language Requirement
English (proficient)
Experience
Minimum 1-2 years hands-on with AWS ML services
Required Skills
Technical Prerequisites
Required Documents
Certification Roadmap
Enrollment
Register on AWS Training & Certification portal and schedule exam via Pearson VUE.
Learning
Master AWS SageMaker, Kinesis, Glue, and model evaluation metrics.
Projects
Build and deploy three end-to-end ML models on AWS.
Assessment
Take practice exams from reputable providers to gauge readiness.
Certification
Appear for the proctored exam and clear with 750/1000 score.
Placement
Update LinkedIn and resume with new credential to attract recruiters.
Career Growth
Pursue advanced roles like AI Architect or Principal ML Engineer.
Skills You Gain
Salary Impact
$100,000
Salary Before
$135,000
Salary After
$35,000
Increase
High
ROI
3 months
Payback Time
35%
Career Growth
Future Demand
95/100
Demand Score
98/100
AI Impact
Extremely High
Global Demand
Very High
India Demand
Low
Automation Risk
18% CAGR
Industry Growth
High
Future Stability
94/100
Overall Score