09-21-2024, 02:31 AM
Complete Python Tutorial| Jupyter Lab| Spyder| 0 To 100
Published 8/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 18.65 GB | Duration: 23h 21m
Python Programming Language
[b]What you'll learn[/b]
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
[b]Requirements[/b]
no prerequisites is needed. You will learn everything you need.
[b]Description[/b]
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.
[b]What you'll learn[/b]
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
[b]Requirements[/b]
no prerequisites is needed. You will learn everything you need.
[b]Description[/b]
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.