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Building on “Introduction to Python for Computational Science”, this course covers additional aspects: (i) advanced Python, (ii) additional libraries such as numpy, scipy, pandas, sympy, (iii) research software engineering and testing, and (iv) application examples with focus on physics and engineering problems.
Parts (i) to (iii) are covered in the beginning of the course. Part (iv) is delivered at the end of the week, and can be omitted if not relevant to the participant.
Topics include: