AI Engineering is a practical, hands-on course designed to transform students into skilled practitioners capable of designing, building, deploying, and maintaining real-world AI systems.
The course blends foundations of machine learning, deep learning, and modern AI architectures (including LLMs and generative AI) with the engineering best practices required for production environments.
Students learn how to:
Build and evaluate machine learning models
Work with large-scale datasets
Deploy AI systems using modern MLOps tools
Integrate LLMs and multimodal models into applications
Ensure reliability, security, ethics, and responsible AI usage
Ship production-grade AI features end-to-end
By the end of the course, students will complete a capstone project deploying a scalable AI application using real-world engineering workflows.
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Yes
One-time for 1 person
AI Engineering is a practical, hands-on course designed to transform students into skilled practitioners capable of designing, building, deploying, and maintaining real-world AI systems.
The course blends foundations of machine learning, deep learning, and modern AI architectures (including LLMs and generative AI) with the engineering best practices required for production environments.
Students learn how to:
Build and evaluate machine learning models
Work with large-scale datasets
Deploy AI systems using modern MLOps tools
Integrate LLMs and multimodal models into applications
Ensure reliability, security, ethics, and responsible AI usage
Ship production-grade AI features end-to-end
By the end of the course, students will complete a capstone project deploying a scalable AI application using real-world engineering workflows.
Lessons
Quizzes
Tasks
Resources
(Average)
Human Resources Manager at BrightEdge
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