Complete Python Tutorial| Jupyter Lab| Spyder| 0 To 100

Python Programming Language

What you'll learn

Python programming language's basic concepts

data structures in Python and their applications

functions and modules in Python (including module creation)

advanced concepts of functions in Python

classes and objective programming in Python

advanced concepts of objective programming in Python

Requirements

no prerequisites is needed. You will learn everything you need.

Description

Are you ready to embark on a comprehensive journey to mastering Python programming? My course is designed to take you from absolute beginner to accomplished Python developer. Whether you have no prior programming experience or are looking to consolidate and advance your existing Python skills, this course covers everything you need. This course provides a step-by-step guide through the fundamentals of Python, including data types, control structures, functions, and object-oriented programming. You'll also delve into more advanced topics such as modules, file handling, and error handling. I ensure that the learning process is hands-on and engaging, with plenty of exercises and projects to apply what you've learned. One of the highlights of this course is the use of Jupyter Lab and Spyder, two of the most powerful tools in the Python ecosystem. Jupyter Lab offers an interactive environment that's perfect for data science and scientific computing, while Spyder provides a robust integrated development environment (IDE) tailored for Python development. You'll learn to leverage these tools to write, test, and debug your Python code efficiently. By the end of this course, you'll have built a solid foundation in Python and will be capable of tackling real-world projects with confidence. Join us and transform your programming skills from 0 to 100 with expert guidance and a structured learning path!

Overview

Section 1: Introduction

Lecture 1 Python introduction and installation

Lecture 2 Familiarity with Python

Lecture 3 Ch03-Familiarity with Python

Lecture 4 Ch04-familiarity with Python

Section 2: data structure In Python

Lecture 5 05-data structure

Lecture 6 06- data structure

Lecture 7 Dictionaries

Lecture 8 Data structures-dictionaries-part 2

Lecture 9 Data structures-sets

Lecture 10 Data structures-sets and tuples

Section 3: Function and modules

Lecture 11 Functions and modules

Lecture 12 Function and modules-part 2

Lecture 13 Function and modules-part3

Lecture 14 Function and modules-part 4

Lecture 15 Function and modules-part5

Section 4: Classes

Lecture 16 Class

Lecture 17 Class-part2

Lecture 18 Class-part3

Lecture 19 Class-part4

Lecture 20 Class-part5

Section 5: File

Lecture 21 Files(read-and-write)

Lecture 22 JSON files

Lecture 23 Try-except blocks

Section 6: advanced level

Lecture 24 Data structures and algorithms (advanced level)

Lecture 25 Last n items

Lecture 26 Largest-smallest n items

Lecture 27 Dicts and slicing

Lecture 28 Itemgetter and attrgetter

Lecture 29 Named tuples

Lecture 30 Chainmap

Lecture 31 Exercises

Lecture 32 String and text

Lecture 33 Fnmatch

Lecture 34 Unicode data-ascii

Lecture 35 Strings and text

Lecture 36 Alignment

Lecture 37 HTML

Lecture 38 Exercises

Those interested in learning the python programming language and working in the field of data science.