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Autor Tópico: Python3: From Beginner to Pro  (Lida 145 vezes)

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Python3: From Beginner to Pro
« em: 03 de Agosto de 2021, 05:16 »

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 178 lectures (30h 16m) | Size: 3.96 GB
A Comprehensive Study of the Basic (and many advanced) skills required by any Python developer: Web, Data Analysis

What you'll learn:
Python 3 Language and Applications
Software Programming Skills
Learn the basic concepts of Python
Learn how to write robust and error free code
Establish a strong foundation in Object Oriented Programming
Learn how to write decorators like a Pro
Learn advanced python concepts like inheritance, super and the MRO
Built-in Modules: os, sys, math, random, datetime, logging
Learn how to work with Text, CSV and JSON files
Learn how to write and analyze Regular Expressions (Regex)
Setup a Flask web server using HTTP, HTML, SQL, Jinja2, Bootstrap4
Learn about Data Analysis using Python: Numpy, Pandas, Seaborn

Requirements
Basic Computer Skills
Basic Logic Skills

Description
Welcome to the brand new course in Python 3: Beginner to Pro.

When I started creating this course, I had one objective in mind:

"Teach like I wish I had been taught".

I remember the questions/doubts/hesitations I had when I was learning Python and I have tried very hard to address them in this course. This is why there are many many quizzes and code assignments/problems to solve in this course. No one learns to swim or ride a bicycle by attending lectures on swimming or biking and so it is with coding. You have to write the code, make mistakes, solve those mistakes and repeat. That is the only way to learn.

A strong foundation is necessary for any new endeavor and if it seems that the course is a bit slow in the beginning, it is a deliberate choice to ensure that students have the requisite knowledge to proceed to the more challenging portions.

Student feedback is a very important to me. It allows me to change portions of the course if necessary. Please don't hesitate to ask pertinent questions and I will answer them ASAP.

Some of the topics:

Data types, variables, operators.

Conversions between Data types

Operators: Arithmetic, Assignment, Comparison

Operators: Logical, Identity, Membership, Bitwise

for loops, while loops and if-else branching

Functions: Parameters, arguments, return values

Functions: Positional and Keyword Argument

Functions: Default Values for parameters

Functions: Variable positional and Keyword arguments

Functions: Local and Global Scope of variables

Functions: Enumerate, Map, Filter, Reduce, Zip, Lambda

Functions: Closures and Decorators

Functions: List and Dictionary comprehensions

Modules and Packages

Built-in modules: os, sys, random, datetime, logging, math

try-catch error handling

Unit tests

File handling: Text, CSV and JSON

Regular Expressions (regex)

Object Oriented Programming: Classes, Instances

OOP: Class and Instance attributes, class and instance methods

OOP: Instance creation step-by-step and the concept of self

OOP: Instance Properties and attribute validation

OOP: Class Inheritance and inherited attributes and methods

OOP: The concept of super

OOP: Method Resolution Order(MRO) for multi-level and multiple inheritance

Web: Using simple HTTP methods via the requests module

Web: Sending and receiving SMS messages using Twilio

Web: Setting up a web server using Flask micro-framework

Web: Dynamic HTML websites using Jinja2 templates

Web: Connecting to a SQL database

Web: Using Bootstrap4 in the website

Web: Putting it all together to create a frontend and a backend.

Data Analysis: Basics and Numpy

Data Analysis: Numpy nD arrays and characteristics

Data Analysis: Pandas dataframes

Data Analysis: Dataframe manipulations, groupby and conditional extraction

Data Analysis: Visualization of data using matDescriptionlib and pandas

Data Analysis: Visualization of data using Seaborn.

Who this course is for
Beginner Python students and developers


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