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Professional Certificate in RISELab Ray
-- ViewingNowThe Professional Certificate in RISELab Ray, spanning 10 comprehensive units, addresses the surging industry demand for high-performance computing expertise. This program is vital for professionals aiming to leverage GPU acceleration in scientific computing and data analytics.
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2个月完成
每周2-3小时
随时开始
无等待期
课程详情
- Introduction to Ray: Fundamentals and Architecture
- Parallel and Distributed Computing with Ray
- Ray Actors and Tasks: Building Scalable Applications
- Ray Datasets: Data Processing and Manipulation
- Ray Tune: Hyperparameter Optimization and Model Tuning
- Ray Serve: Building and Deploying Scalable Microservices
- Advanced Ray: Scaling and Performance Optimization
- Ray Integration with other Frameworks (e.g., TensorFlow, PyTorch)
- Real-world Applications of Ray: Case studies and examples
- Deployment and Monitoring of Ray Applications
职业道路
Role Description Primary Keywords Secondary Keywords Data Scientist (RISELab Ray) Develop and deploy machine learning models using RISELab Ray technologies.
Analyze large datasets to extract actionable insights.
Data Science, Machine Learning, RISELab Ray, Distributed Computing Python, Spark, Big Data, Cloud Computing Software Engineer (RISELab Ray) Design, develop, and maintain software applications utilizing RISELab Ray for high-performance computing.
Contribute to open-source projects.
Software Engineering, RISELab Ray, Parallel Computing, High-Performance Computing C++, Java, Kubernetes, Docker Machine Learning Engineer (RISELab Ray) Build and optimize machine learning pipelines leveraging RISELab Ray for scalability and efficiency.
Implement models in production environments.
Machine Learning Engineering, RISELab Ray, Model Deployment, MLOps TensorFlow, PyTorch, AWS, Azure
入学要求
- 对主题的基本理解
- 英语语言能力
- 计算机和互联网访问
- 基本计算机技能
- 完成课程的奉献精神
无需事先的正式资格。课程设计注重可访问性。
课程状态
本课程为职业发展提供实用的知识和技能。它是:
- 未经认可机构认证
- 未经授权机构监管
- 对正式资格的补充
成功完成课程后,您将获得结业证书。
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