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Certified Machine Learning Engineer (CMLE)
The "Certified Machine Learning Engineer (CMLE)" program equips participants to build and deploy scalable ML solutions. You’ll master model training, evaluation, MLOps, and production-grade ML pipelines. As ML systems process sensitive data, security is a critical requirement. This course emphasizes data protection, adversarial robustness, model hardening, and monitoring for security breaches. Graduates will ensure that their ML systems not only perform accurately but also remain resilient under cyber threat scenarios in mission-critical applications.
Course Overview
None
Learning Objectives
- Understand the fundamental concepts and algorithms of machine learning.
- Apply various machine learning techniques for tasks such as classification, regression, and clustering.
- Develop and train machine learning models using relevant datasets and tools.
- Evaluate the performance of machine learning models and address issues like overfitting.
- Deploy and maintain machine learning models in real-world applications.
- Machine learning is crucial for developing intelligent security systems for threat detection and anomaly analysis, significantly impacting cybersecurity.
Framework Connections
The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):
Competency Areas
Feedback
If you would like to provide feedback on this course, please e-mail the NICCS team at NICCS@mail.cisa.dhs.gov. Please keep in mind that NICCS does not own this course or accept payment for course entry. If you have questions related to the details of this course, such as cost, prerequisites, how to register, etc., please contact the course training provider directly. You can find course training provider contact information by following the link that says “Visit course page for more information...” on this page.