Lectures related to Data Science with Python

Python Programming: List Comprehensions and Higher Order Functions

Explores advanced Python programming concepts, focusing on list comprehensions and higher order functions.

Python Basics: Syntax, Variables, Functions

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

Discusses image processing techniques, focusing on seam carving and pixel manipulation in Python programming.

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.

Functions and Control Structures in Python

Introduces functions and control structures in Python, emphasizing their importance for code organization and reusability.

Python Programming: Lists and Functions Overview

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

Python Programming: Dictionaries and Classes

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

Control Flow in Python: Conditional Statements and Loops

Covers control flow in Python, focusing on conditional statements and loops.

Programming Basics: Python Fundamentals

Covers the basics of programming with Python, emphasizing practical exercises and self-learning resources.

Python Basics

Covers Python basics, Git, control structures, functions, file handling, and debugging using PDB.

Python Programming Basics

Covers the basics of Python programming, focusing on flow control structures, interactive mode, script mode, and variables.

Python Programming: Immutable and Mutable Objects

Explains the differences between mutable and immutable objects in Python, focusing on lists, sets, and their behaviors.

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.

Scopes and Lambdas: Data Science with Python

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

NumPy Arrays and Graphical Representations: Introduction

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

Python for Engineers: Basics and Functions

Covers Python basics, functions, and practical applications for engineers, emphasizing data manipulation, functional programming, and data structures.

Introduction to Programming with Python

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

Data Science for Engineers: Part 2

Explores data manipulation, exploration, and visualization in data science projects using Python.