Learn Pro Advanced Python Programming
Learn Pro Advanced Python Programming, available at $69.99, has an average rating of 4.51, with 174 lectures, based on 821 reviews, and has 5813 subscribers.
You will learn about Advance Level Programming in Python Make real time advance applications using Advance Level Concepts Make Machine Learning Models Use Machine Learning Models to make real time Applications Learn the Mathematics behind Machine Learning Models This course is ideal for individuals who are Anyone curious to learn Advance Level Programming or Anyone curious to make Advance Level Applications or Anyone Curious about Machine Learning Models It is particularly useful for Anyone curious to learn Advance Level Programming or Anyone curious to make Advance Level Applications or Anyone Curious about Machine Learning Models.
Enroll now: Learn Pro Advanced Python Programming
Summary
Title: Learn Pro Advanced Python Programming
Price: $69.99
Average Rating: 4.51
Number of Lectures: 174
Number of Published Lectures: 174
Number of Curriculum Items: 174
Number of Published Curriculum Objects: 174
Original Price: $124.99
Quality Status: approved
Status: Live
What You Will Learn
- Advance Level Programming in Python
- Make real time advance applications using Advance Level Concepts
- Make Machine Learning Models
- Use Machine Learning Models to make real time Applications
- Learn the Mathematics behind Machine Learning Models
Who Should Attend
- Anyone curious to learn Advance Level Programming
- Anyone curious to make Advance Level Applications
- Anyone Curious about Machine Learning Models
Target Audiences
- Anyone curious to learn Advance Level Programming
- Anyone curious to make Advance Level Applications
- Anyone Curious about Machine Learning Models
In this course, I am going to make you a professional programmer by teaching you Advance Level Programming in Python. The Basic of any programming language is not enough to make real time applications therefor, i have covered most of the Advance Level Concepts in depth in this course. As grabbing the main concept behind Advance Topics is not simple therefor, special attention is given to the intuition part of each concept where we gonna understand these concepts with proper animated slides.
Also not only understanding these advance concepts are important but to make something real out of it is very important or else there is no reason to learn Advance Programming therefor we will also make real time Advance level Applications in Python using Advance level concepts. We will also learn Machine Learning in Python in depth by covering the Mathematics behind each model as well. Also we will use these Machine Learning Models to make something real out of it.
I believe that after taking this course, you gonna feel much more satisfied and comfortable with your programming skill in Python as you will then be a professional programmer who is capable to give any job interview..Also after taking this course, learning any Advance Level concept in any other language will be 10x more simpler.
I wish you very best for the Course.
Course Curriculum
Chapter 1: Python Comprehension
Lecture 1: Section Overview
Lecture 2: Introduction to Comprehension
Lecture 3: List Comprehension Part-1
Lecture 4: List Comprehension Part-2
Lecture 5: List Comprehension vs Lambda Function
Lecture 6: Parsing a File Using List Comprehension
Lecture 7: Accessing Function using List Comprehension
Lecture 8: Dictionary Comprehension
Lecture 9: Set Comprehension
Lecture 10: Generator Comprehension
Chapter 2: Descriptors in Python
Lecture 1: Section Overview
Lecture 2: Introduction to Descriptors
Lecture 3: Invoking Descriptors
Lecture 4: Purpose of Descriptors Part-1
Lecture 5: Purpose of Descriptors Part-2
Lecture 6: Creating Descriptors using Property
Lecture 7: Creating Descriptors using Class
Lecture 8: Creating Descriptors using @
Lecture 9: Uses of Descriptors
Chapter 3: Linked List in Python
Lecture 1: Section Overview
Lecture 2: Singly and Doubly Linked List
Lecture 3: Intro to Linked Lists
Lecture 4: Create and Traverse – Singly Linked List
Lecture 5: Insertion – Singly Linked List
Lecture 6: Deletion – Singly Linked List
Lecture 7: Creating – Doubly Linked List
Lecture 8: Insertion – Doubly Linked List
Lecture 9: Appending – Doubly Linked List
Lecture 10: Deletion – Doubly Linked List
Chapter 4: OpenCV – Image/Video Processing in Python
Lecture 1: Installing the OpenCV Module
Lecture 2: Showing the Image
Lecture 3: Keyboard Events in OpenCV
Lecture 4: Drawing Different Shapes on Images
Lecture 5: Capturing Video with OpenCV
Lecture 6: Writing the Video
Lecture 7: Different Video Properties
Lecture 8: Events
Lecture 9: Implementing Mouse Events
Lecture 10: Image Thresh holding
Lecture 11: Object Detection with OpenCV
Chapter 5: Generators in Python
Lecture 1: Understanding Generators
Lecture 2: Creating Generator – Part-1
Lecture 3: Creating Generator – Part-2
Lecture 4: Generator – Example
Chapter 6: Managing Files in Python
Lecture 1: Section Overview
Lecture 2: Introduction to File Handling
Lecture 3: Creating a Text File
Lecture 4: Modes in Files
Lecture 5: Modes for other File Types
Lecture 6: Reading from a Text File
Lecture 7: Renaming a Text File
Lecture 8: Writing to a Text File
Lecture 9: Saving Data to a File
Lecture 10: Appending to a File
Lecture 11: Closing a File
Lecture 12: Deleting a File
Lecture 13: With Statement
Lecture 14: Saving Dictionary to a File
Chapter 7: Magic Functions in Python
Lecture 1: Section Overview
Lecture 2: Introduction to Magic Methods
Lecture 3: Various Magic Methods
Lecture 4: Magic Methods based on Object Usefulness
Lecture 5: Initialization and Construction
Lecture 6: Unary Operators – Magic Methods
Lecture 7: Strings – Magic Methods
Lecture 8: Operators – Magic Methods
Lecture 9: Augmented Assignment Operator
Lecture 10: Magic Methods for Binary Operators
Chapter 8: Thread Programming in Python
Lecture 1: Section Overview
Lecture 2: Concurrency vs Parallelism
Lecture 3: Multiprocessing vs Multi-Threading
Lecture 4: Introduction to Thread
Lecture 5: The Threading Module
Lecture 6: Creating a Thread
Lecture 7: Determining the Current Thread
Lecture 8: Daemon vs non_Daemon
Lecture 9: Enumerating Threads
Chapter 9: The Arcade Module
Lecture 1: Introduction to Arcade Module
Lecture 2: Sad Images – Arcade Module
Lecture 3: Still Images – Arcade Module
Lecture 4: Auto Timer – Arcade Module
Lecture 5: Auto Snow – Arcade Module
Lecture 6: Auto Radar – Arcade Module
Lecture 7: User Controlled Moving Object – Arcade Module
Chapter 10: PDF Audio Reader Application
Lecture 1: PDF Audio Reader Application Part-1
Lecture 2: PDF Audio Reader Application Part-2
Lecture 3: PDF Audio Reader Application Part-3
Lecture 4: PDF Audio Reader Application Part-4
Lecture 5: PDF Audio Reader Application Part-5
Lecture 6: PDF Audio Reader Application Part-6
Instructors
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Data Scientist
Software Engineer, Data Scientist and Entrepreneur
Rating Distribution
- 1 stars: 29 votes
- 2 stars: 26 votes
- 3 stars: 67 votes
- 4 stars: 164 votes
- 5 stars: 535 votes
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