Software engineers need new skills in the age of AI
AI is transforming software engineering, changing what software engineers do and the skills they need to succeed. A new survey from Uplevel, of over 100 senior engineering leaders at mid-to-large technology companies, looks at what they believe will be the most important skills for their teams.
It finds that validation of AI outputs and quality assurance (QA) is valued highest, cited by 66 percent of leaders, followed by performance monitoring and optimization (39 percent), and system architecture and integration skills (34 percent)
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Although creating a machine learning pipeline or developing a working prototype of a software system from that pipeline is easy and straightforward nowadays, the journey toward a professional software system is still extensive.
Machine Learning Infrastructure and Best Practices for Software Engineers will help you get to grips with various best practices and recipes that will help software engineers transform prototype pipelines into complete software products. The book begins by introducing the main concepts of professional software systems that leverage machine learning at their core.