Python The complete guide

Python – The complete guide, available at $69.99, has an average rating of 4.5, with 106 lectures, based on 8 reviews, and has 63 subscribers.

You will learn about Python basics & advanced Python must used libraries Use MySQL databases with Python Django with MySQL (CRUD) PyQt5 with MySQL (CRUD) NumPy – work with multi-dimensional arrays Matplotlib – bar chart, pie chart, etc Pandas – manage CSV, manage JSON, clean data Machine Learning overview Build Web, Desktop & Mobile App with Python This course is ideal for individuals who are Python developers curious to learn or Web App developers or Desktop App developers It is particularly useful for Python developers curious to learn or Web App developers or Desktop App developers.

Enroll now: Python – The complete guide

Summary

Title: Python – The complete guide

Price: $69.99

Average Rating: 4.5

Number of Lectures: 106

Number of Published Lectures: 106

Number of Curriculum Items: 106

Number of Published Curriculum Objects: 106

Original Price: 84.99

Quality Status: approved

Status: Live

What You Will Learn

Python basics & advanced

Python must used libraries

Use MySQL databases with Python

Django with MySQL (CRUD)

PyQt5 with MySQL (CRUD)

NumPy – work with multi-dimensional arrays

Matplotlib – bar chart, pie chart, etc

Pandas – manage CSV, manage JSON, clean data

Machine Learning overview

Build Web, Desktop & Mobile App with Python

Who Should Attend

Python developers curious to learn

Web App developers

Desktop App developers

Target Audiences

Python developers curious to learn

Web App developers

Desktop App developers

A complete practical Python course in which you will learn to create your own web/desktop app with MySQL database. The course covers everything to start with and to be a professional in Python. Understand very useful libraries such as: 

NumPy – to work faster with multidimensional arrays

Matplotlib – present your data graphically

Pandas – analyze, clean and plot your data

Scikit-learn – get a large overview on Machine Learning, know how to split your dataset to training & testing data

Use Django frameworks with other great libraries to create very quickly real-world web application. Learn how to use Urls, Views, Models, Templates, and Forms. Learn how to upload file to your server.

Use PyQt5 to create your own multi-platform desktop application with modern design. Know how to create that with or without using Qt Designer. Present your data (either from SQL database, CSV, JSON, list, dictionary, set, tuple) using Matplotlib to your desktop app.

Use either SQLite or MySQL to store your data and manipulate them, either with simple Python, or with Django, or with PyQt5. (CRUD) Create, Read, Update, Delete.

In the course, very very less theoretical things are used. Learning with exemples and exercices is the most effective way!!!! However, during typing the codes, we explain everything from start to finish so you understand the theory while coding.

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Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: What you will learn

Lecture 3: Important

Chapter 2: Starting booster

Lecture 1: Installation

Lecture 2: Syntax

Lecture 3: Data types

Lecture 4: Variables

Lecture 5: Numbers & random

Lecture 6: Strings & some methods

Lecture 7: Input & Strings

Lecture 8: String format

Lecture 9: Operators & type conversion

Lecture 10: List & methods

Lecture 11: Tuple

Lecture 12: Dictionaries

Lecture 13: Emoji converter exemple with dictionaries

Lecture 14: Dictionaries & some methods

Lecture 15: Recap – Quick note

Lecture 16: If statement

Lecture 17: While loop

Lecture 18: While exemple with input as command

Lecture 19: For loop

Lecture 20: Nested loops

Lecture 21: Functions – *args & **kwargs

Lecture 22: Create BMI calculator with functions

Lecture 23: Classes & Objects

Lecture 24: The use of self

Lecture 25: Inheritance

Lecture 26: Modules

Lecture 27: External modules

Lecture 28: JSON with Python

Lecture 29: Regular Expressions (RegEx)

Lecture 30: Error handlign – tryexcept

Lecture 31: Packages

Lecture 32: External packages

Lecture 33: Pathlib

Lecture 34: File handling

Lecture 35: File handling 2

Lecture 36: File handling 3 – with statement

Chapter 3: NumPy

Lecture 1: Multi-dimensional

Lecture 2: Indexing

Lecture 3: Slicing

Lecture 4: Ownership – copy() vs view()

Lecture 5: Iteration

Lecture 6: Join & Split

Lecture 7: Search & Sort

Lecture 8: Creating functions

Lecture 9: Arithmetics

Chapter 4: Matplotlib

Lecture 1: Matplotlib

Lecture 2: Markers

Lecture 3: Labels

Lecture 4: Grid

Lecture 5: Grid with subplots

Lecture 6: Scatter

Lecture 7: Bar chart

Lecture 8: Pie chart

Chapter 5: Pandas

Lecture 1: Overview

Lecture 2: Series vs DataFrame

Lecture 3: Read JSON & CSV

Lecture 4: Clean data

Lecture 5: Clean data 2

Lecture 6: Plotting CSV or JSON data

Lecture 7: Histogram

Chapter 6: Machine Learning

Lecture 1: Info

Lecture 2: Overview

Lecture 3: KNN

Lecture 4: K-means

Lecture 5: K-means with images

Chapter 7: MySQL with Python

Lecture 1: Connection setup

Lecture 2: Use a database

Lecture 3: Insert data

Lecture 4: Select – displaying data

Lecture 5: Delete

Lecture 6: Update & highlights

Chapter 8: Django with SQLite & MySQL

Lecture 1: Django starting

Lecture 2: Creating/Adding new App

Lecture 3: Views & Urls

Lecture 4: Static files

Lecture 5: Migrations & Django admin

Lecture 6: Models & Admin App register

Lecture 7: Models & Foreign Key

Lecture 8: Accessing & displaying data from database to the frontend

Lecture 9: Views with slug

Lecture 10: New App & file upload preparation

Lecture 11: File upload

Lecture 12: Switch from SQLite to MySQL

Lecture 13: Sign up & sign in

Lecture 14: Add a form to template

Lecture 15: Sign up new user

Lecture 16: Get logged in username

Lecture 17: Page visibility / restriction

Lecture 18: Forms

Instructors

Nico @softcademy
IT | Web & Software developer | Teacher & Instructor

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5 stars: 7 votes

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