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This lecture introduces the basics of scientific programming for engineers, focusing on the use of GIT for collaborative work. Topics covered include the importance of data interpretation, challenges in scientific software development, and the engineering production cycles. The instructor emphasizes the significance of automation in programming tasks and provides insights into the process of designing, implementing, and analyzing scientific software. Students will gain practical knowledge in using C/C++, Python, and various libraries for scientific computing. The lecture also includes hands-on exercises and guidance on version control systems like GIT.