Lectures related to Hydroponic Farming in Space: GrowBotHub

Covers the basics of writing functions in Python and working with function arguments.

Covers the basics of programming, including types, variables, methods, functions, conditions, loops, and boolean logic.

Introduces Python programming concepts, focusing on lists, functions, and their applications in problem-solving.

Covers the basics of programming in Python, focusing on practical skills and hands-on exercises.

Covers the basics of Python programming, focusing on strings and variables, with practical examples and exercises.

Introduces Python programming basics, covering data types, operators, variables, functions, and code tracing.

Covers advanced Python programming concepts, including data structures and functions.

Explores file handling and exceptions in Python programming, covering reading, writing, and error handling strategies.

Covers Python programming concepts related to sorting and indexing.

Covers advanced topics in Python programming, focusing on control structures and functions.

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.