Data Science with Python

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Related lectures (30)

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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.