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Start 5 June 2026 19:52
Einde 5 June 2026
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13 minutes
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Overzicht
Explore 8 cloud GPU providers offering various options from RTX 3060 to H100 GPUs, comparing features and pricing for machine learning and LLM fine-tuning projects.
Lesprogramma
- Introduction to Cloud GPU Providers
- Understanding GPU Architectures and Models
- Criteria for Selecting Cloud GPU Providers
- Detailed Comparison of 8 Cloud GPU Providers
- Performance Testing and Benchmarking
- Case Studies and Use Cases
- Best Practices for Renting Cloud GPUs
- Trends and Future Directions in Cloud GPUs
- Summary and Recommendations
- Final Project
- Course Wrap-Up and Q&A
Overview of the course objectives
Importance of GPUs in machine learning and LLM fine-tuning
Differences between consumer and data center GPUs
Detailed look at NVIDIA RTX 3060 to RTX 4090
Examination of NVIDIA A100 and H100 capabilities
Performance benchmarks
Cost-effectiveness
Availability and scalability
Support and additional features
Provider 1: Company Overview, GPU offerings, Pricing, Unique features
Provider 2: Company Overview, GPU offerings, Pricing, Unique features
Provider 3: Company Overview, GPU offerings, Pricing, Unique features
Provider 4: Company Overview, GPU offerings, Pricing, Unique features
Provider 5: Company Overview, GPU offerings, Pricing, Unique features
Provider 6: Company Overview, GPU offerings, Pricing, Unique features
Provider 7: Company Overview, GPU offerings, Pricing, Unique features
Provider 8: Company Overview, GPU offerings, Pricing, Unique features
Designing benchmarks for machine learning tasks
Evaluating performance for LLM fine-tuning
Analyzing results and drawing conclusions
Case Study 1: Machine learning project with RTX 3060
Case Study 2: LLM fine-tuning with H100
Case Study 3: Cost analysis for different provider setups
Cost-saving strategies
Efficient resource management
Optimizing workflows for different GPUs
Emerging technologies in accelerator hardware
Future of cloud-based AI projects
Key insights from provider comparisons
Final recommendations based on specific project needs
Conduct a comparative analysis on a chosen provider setup
Present findings and recommendations in a report
Summary of key learnings
Open discussion and additional questions
Vakgebieden
Programming