The learning resoources and schedule that I would follow in order to have deep foundation knowledge in becoming a machine learning practitioner, a software engineer that can build AI-empowered applications.
- Python Tricks
- Test-Driven Development with Python: Obey the Testing Goat: Using Django, Selenium, and JavaScript
- Working Effectively with Legacy Code
- Berkeley CS168: Introduction to the Internet: Architecture and Protocols
- Stanford CS145: Data Management and Data Systems
- Stanford CS245: Principles of Data-Intensive Systems
- Stanford CS349D: Cloud Computing Technology
- Stanford CS149: Parallel Computing
- MIT 6.824: Distributed Systems
- 深入淺出大型網站架構設計
- CMU: Foundations of Software Engineering
- Working Effectively with Legacy Code
- Domain-Driven Design
- 大話設計模式
- Test-Driven Development with Python: Obey the Testing Goat: Using Django, Selenium, and JavaScript
- Architecture Patterns with Python: Enabling Test-Driven Development, Domain-Driven Design, and Event-Driven Microservices
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