Complete Python Course Bootcamp | Python Libraries Unlocked
Complete Python Course Bootcamp | Python Libraries Unlocked, available at $69.99, has an average rating of 4.45, with 273 lectures, 1 quizzes, based on 21 reviews, and has 259 subscribers.
You will learn about Students will learn how to process images in Python Students will learn how to perform numeric operation using Python Numpy Students will learn how to visualize data using Matplotlib Students will learn how to analyze audio files in Python Students will learn how to extract information from any web page using Web Scraping technique. Students will learn how to mine data from text and how to find different types of patterns in text. This course is ideal for individuals who are Beginner Python Developer who wants to use Python as a Problem Solving Tool for Real-world Problems. or Python Developer who wants to become a Python Freelancer. or Py-Developer who wants to learn important Python Libraries. It is particularly useful for Beginner Python Developer who wants to use Python as a Problem Solving Tool for Real-world Problems. or Python Developer who wants to become a Python Freelancer. or Py-Developer who wants to learn important Python Libraries.
Enroll now: Complete Python Course Bootcamp | Python Libraries Unlocked
Summary
Title: Complete Python Course Bootcamp | Python Libraries Unlocked
Price: $69.99
Average Rating: 4.45
Number of Lectures: 273
Number of Quizzes: 1
Number of Published Lectures: 273
Number of Curriculum Items: 274
Number of Published Curriculum Objects: 273
Original Price: $19.99
Quality Status: approved
Status: Live
What You Will Learn
- Students will learn how to process images in Python
- Students will learn how to perform numeric operation using Python Numpy
- Students will learn how to visualize data using Matplotlib
- Students will learn how to analyze audio files in Python
- Students will learn how to extract information from any web page using Web Scraping technique.
- Students will learn how to mine data from text and how to find different types of patterns in text.
Who Should Attend
- Beginner Python Developer who wants to use Python as a Problem Solving Tool for Real-world Problems.
- Python Developer who wants to become a Python Freelancer.
- Py-Developer who wants to learn important Python Libraries.
Target Audiences
- Beginner Python Developer who wants to use Python as a Problem Solving Tool for Real-world Problems.
- Python Developer who wants to become a Python Freelancer.
- Py-Developer who wants to learn important Python Libraries.
In this course, students will learn how to use Pythonas real-world problems solving tool and we will go through all those important libraries of Python which every python beginner should know. From Image Processing to Audio Analysis, from Data Extraction to Data Visualization & from Web Scraping to Network Programming, students will learn each & every important concept which will let students become full-stack Python Developers.
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First of all, we will start from Pillow which is animage processing library, and with the help of this library students will learn how to play with images in Python.
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After this, we will learn our favorite library and that’s Numpy which will allow us to work with arrays and numeric operations in Python.
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And for data visualization, we will learn Matplotlib which is simple and easy to use.
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For storing purposes, we will use Google Firebase with the help of the Python Pyrebase library which will allow us to addstorage, database, and authentication features in our python apps.
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Nowadays audios are a very sophisticated way of data sharing and to process and analyze audio files, we will use the Pydub library.
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After learning all these things, every python beginner should also know about Networking as well and for Network Programming in Python, we will use a very well-known python library and that is Sockets.
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For finding different types of patterns for data extraction, we will learn Python regex or Re module.
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For text mining & text processing, we will learn Python’s easiest library and that is Textblob.
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Finally, students need to know about Web Scraping and for this purpose, we will use the BeautifulSouplibrary.
We will also update this course from time to time by adding more material regarding Python Development in order to keep students up-to-date for python development.
Course Curriculum
Chapter 1: Sequential Programming in Python
Lecture 1: What is Programming Language?
Lecture 2: Why is Python so popular?
Lecture 3: Preparing Environment
Lecture 4: IDLE Overview
Lecture 5: Variables
Lecture 6: Variables in Python
Lecture 7: Print Function
Lecture 8: Datatypes
Lecture 9: Datatypes in Python
Lecture 10: Escape Sequences in Python
Lecture 11: More on Python Strings
Lecture 12: Typecasting in Python
Lecture 13: Concatenation in Python
Lecture 14: Statement vs Comment
Lecture 15: Input Function
Lecture 16: Multiple Inputs: Split & Eval Function
Lecture 17: Quiz Program
Lecture 18: Operators and their types
Lecture 19: Arithmetic Operators
Lecture 20: Order of Precedence in Arithmetic Operators
Lecture 21: Comparison Operators
Lecture 22: Logical Operators
Lecture 23: Order Of Precedence in Logical Operators
Lecture 24: Python Math module
Chapter 2: Control Structures in Python
Lecture 1: Introduction to Conditional Programming in Python
Lecture 2: Installing VS Code
Lecture 3: If Conditional Statement
Lecture 4: Implementing If-Block in Python
Lecture 5: If-else Conditional Statements
Lecture 6: Implementing If-else Block in Python
Lecture 7: Implementing If-elif-else Block in Python
Lecture 8: Program -I
Lecture 9: Switch Statement in Python
Lecture 10: Loops
Lecture 11: Range Function
Lecture 12: For loop
Lecture 13: Program -II
Lecture 14: Nested For Loops
Lecture 15: Program -III: Square Pattern
Lecture 16: While Loop
Lecture 17: Program -IV: Pyramid Pattern
Lecture 18: Program -V: No. of digits
Lecture 19: Break Keyword
Lecture 20: Continue Keyword
Chapter 3: Collection Datatypes
Lecture 1: What are collection datatypes?
Lecture 2: Lists -I
Lecture 3: Lists -II
Lecture 4: Slicing
Lecture 5: Nested Lists
Lecture 6: Program -I
Lecture 7: Program -II
Lecture 8: List Comprehension
Lecture 9: Tuples
Lecture 10: Sets
Lecture 11: Maths Operations
Lecture 12: Dictionary
Lecture 13: Data Unpacking
Lecture 14: Sorting
Lecture 15: Dictionary Comprehension
Lecture 16: Strings
Chapter 4: Functional Programming in Python
Lecture 1: Introduction to Functions
Lecture 2: Function's "Hello World!"
Lecture 3: Passing Data to Functions
Lecture 4: Parameters vs Arguments
Lecture 5: return Keyword
Lecture 6: Program -I
Lecture 7: Named Tuple
Lecture 8: Doc Strings & help function
Lecture 9: Types of Arguments
Lecture 10: Implementation: Types of Arguments
Lecture 11: *args in Python
Lecture 12: **kwargs in Python
Lecture 13: Types of Variables
Lecture 14: Namespaces
Lecture 15: Recursion
Lecture 16: Program -II
Lecture 17: Program -III
Lecture 18: Iterators in Python
Lecture 19: Generators in Python
Lecture 20: Creating Custom Range Function
Lecture 21: Nested Functions
Lecture 22: Helper Functions
Lecture 23: Returning a nested function value
Lecture 24: Closures
Lecture 25: Program -IV
Lecture 26: Program -V
Lecture 27: Passing Function as an Argument
Lecture 28: Decorators
Lecture 29: Anonymous Function
Lecture 30: Lambda as a nested Function
Lecture 31: Lambda as Decorator
Lecture 32: Filter Function
Lecture 33: Program -VI
Lecture 34: Dictionary & Filter Function
Lecture 35: Map Function
Chapter 5: Object Oriented Programming in Python
Instructors
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Nileg Production
Software Developer -
Umair Ahmed Younas
Computer Enthusiastic
Rating Distribution
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- 2 stars: 0 votes
- 3 stars: 3 votes
- 4 stars: 1 votes
- 5 stars: 17 votes
Frequently Asked Questions
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