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Covers the basics of scientific programming for engineers, emphasizing the importance of GIT for collaborative work and providing insights into challenges in scientific software development.
Covers systems engineering, project management, quality assurance, and space mechanisms, emphasizing the importance of proper requirements and verification.
Explores how AI/ML is shaping the future workplace, focusing on enterprise systems and processes, and discusses the current state of AI/ML adoption in enterprises.
