Lectures related to Python Programming: Sorting and Indexing

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Introduces the CS-250 Algorithms course, covering its structure, objectives, and key topics in algorithmic problem-solving.

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

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

Python Functions: Basics and Arguments

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

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Explains the merge sort algorithm, its correctness, and time complexity compared to other sorting algorithms.

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

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

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

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Provides an overview of essential search and sort algorithms in computer science.

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

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Covers fundamental programming and object-oriented programming concepts in Java, including variables, types, control structures, and basic algorithmic concepts.

Python Programming: Control Structures and Functions

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

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

Introduction to Python Programming

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

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Covers the implementation of a Parallelogram class in Python.

Python Programming: File Handling and Exceptions

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

Python Programming: Dictionaries and Classes

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

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Covers scopes, lambdas, and pandas in data science with Python, including nested declarations, scoping, assignments, and pandas manipulation.

Programming Basics: Control Structures and Functions

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