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Python syntax and semantics
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Related lectures (30)
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Python Programming: File Handling and Exceptions
Explores file handling and exceptions in Python programming, covering reading, writing, and error handling strategies.
Multi-Regional Input Output Analysis: EXIOBASE 3
Covers the computation of Economy-Wide Material Flow Analysis for Switzerland using EXIOBASE 3.
Python: Dictionaries and Tuples
Explores dictionaries, tuples, mutable objects, and variable-length arguments in Python.
Python Lists: Manipulation and Comprehension
Covers Python list manipulation and comprehension, emphasizing memory representation and mutability.
Python Modules and Pandas
Introduces Python modules, scoping, lambdas, and pandas for data manipulation and analysis.
Exception Handling in Python
Covers exception handling in Python, including try, raise, except, else, and finally blocks, with examples.
General Introduction to Data Science
Offers a comprehensive introduction to Data Science, covering Python, Numpy, Pandas, Matplotlib, and Scikit-learn, with a focus on practical exercises and collaborative work.
Python Recap: Modules and Objects
Covers Python modules, objects, and data containers like lists and NumPy arrays.
Data Science Visualization with Pandas
Covers data manipulation and exploration using Python with a focus on visualization techniques.
File Handling: Text and Bytes
Covers file handling, string operations, and character encodings in Python.
Binary Sentiment Classifier Training
Covers the training of a binary sentiment classifier using an RNN.
Functions in Python
Introduces functions in Python, covering predefined and user-defined functions, formal and effective parameters, and the importance of docstrings.
Programming Basics: Control Structures and Functions
Introduces fundamental programming concepts in Python, focusing on control structures like conditions and loops.
Python Programming: Data Structures and Functions
Covers advanced Python programming concepts, including data structures and functions.
Programming Basics: Python Fundamentals
Covers the basics of programming with Python, emphasizing practical exercises and self-learning resources.
Python Complement: Numpy, Scipy, Matplotlib
Covers advanced Python topics like numpy operations, scipy linear algebra, and matplotlib for creating figures.
Python Programming Basics
Covers the basics of Python programming, focusing on flow control structures, interactive mode, script mode, and variables.
Introduction to Programming with Python
Introduces Python programming basics, covering data types, operators, variables, functions, and code tracing.
Atomic-Scale Modeling: Fundamentals
Introduces atomic-scale modeling and computational predictions, emphasizing materials science fundamentals and Python programming skills.
Debugging and Computational Methods
Covers debugging techniques in Python and computational methods like frequency power calculation and bird sound detection.
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