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Data Science with Python
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Related lectures (56)
Functions and Lists: Complements and Manipulation
Explores functions' complements, parameter order, and list manipulation, including counting occurrences and solving the '100 prisoners problem'.
Python Programming: Control Structures and Functions
Covers advanced topics in Python programming, focusing on control structures and functions.
Programming Basics: Python Fundamentals
Covers the basics of programming with Python, emphasizing practical exercises and self-learning resources.
Python Programming Basics
Covers the basics of Python programming, focusing on flow control structures, interactive mode, script mode, and variables.
Python Programming: Data Structures and Functions
Covers advanced Python programming concepts, including data structures and functions.
Variables, Objects, Types
Introduces variables, objects, and types in Python, emphasizing the significance of object mutability and its implications when passing objects to functions.
Introduction to Programming with Python
Introduces Python programming basics, covering data types, operators, variables, functions, and code tracing.
Python Basics: Functions and Lists
Introduces Python basics, functions, lists, and lambda functions for concise coding.
Python: Dictionaries and Tuples
Explores dictionaries, tuples, mutable objects, and variable-length arguments in Python.
Python Programming: List Comprehensions and Higher Order Functions
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Explores advanced Python programming concepts, focusing on list comprehensions and higher order functions.
Python Basics: Syntax, Variables, Functions
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Covers Python basics such as syntax, variables, and functions, introducing the Renku platform for collaborative data science.
Image Processing Techniques: Seam Carving and Pixel Manipulation
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Discusses image processing techniques, focusing on seam carving and pixel manipulation in Python programming.
Python Programming: Lists and Functions Overview
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Introduces Python programming concepts, focusing on lists, functions, and their applications in problem-solving.
Python Programming: Dictionaries and Classes
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Introduces Python programming concepts, focusing on dictionaries and classes, including their definitions, usage, and practical examples.
Control Flow in Python: Conditional Statements and Loops
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Covers control flow in Python, focusing on conditional statements and loops.
Python Basics
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Covers Python basics, Git, control structures, functions, file handling, and debugging using PDB.
NumPy Arrays and Graphical Representations: Introduction
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Covers NumPy arrays and their graphical representations using Matplotlib, focusing on array creation, manipulation, and visualization techniques.
Python Programming: Immutable and Mutable Objects
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Explains the differences between mutable and immutable objects in Python, focusing on lists, sets, and their behaviors.
Python for Engineers: Basics and Functions
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Covers Python basics, functions, and practical applications for engineers, emphasizing data manipulation, functional programming, and data structures.
Data Science for Engineers: Part 2
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Explores data manipulation, exploration, and visualization in data science projects using Python.
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