Hydroponic Farming in Space: GrowBotHub

Related lectures (27)

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Covers the implementation of a Python function to detect duplicates in a list of integers.

Introduces Python programming basics using Anaconda and JupyterLab, with practical exercises on syntax and libraries.

Covers the implementation of a Parallelogram class in Python.

Introduces Python programming concepts, focusing on dictionaries and classes, including their definitions, usage, and practical examples.

Introduces fundamental programming concepts in Python, focusing on control structures like conditions and loops.

Discusses numerical methods, focusing on stopping criteria, SciPy for optimization, and data visualization with Matplotlib.

Covers NumPy arrays and their graphical representations using Matplotlib, focusing on array creation, manipulation, and visualization techniques.

Introduces the Computational Science option at EPFL, detailing course objectives and programming fundamentals using Python.

Introduces Jupyter exercises on Differential Privacy, covering random generators, understanding data intrusion impact, and practical applications.

Introduces NumPy and Matplotlib, essential tools for scientific computing and data visualization in Python.