Python – Complete Python, Django, Data Science and ML Guide

Python – Complete Python, Django, Data Science and ML Guide, available at $84.99, has an average rating of 4.58, with 470 lectures, based on 157 reviews, and has 1605 subscribers.

You will learn about You will learn the basic principles of Python and learn all the main functions that are used most often in real projects and are in demand the most You will practice all the examples that I will show throughout the course using the Python interpreter, Visual Studio Code with Code Runner You will master all the necessary packages for Data Science and Machine Learning such as NumPy, Pandas, Matplotlib and Scikit-learn using Jupyter Notebook You will learn the basic functionality of Python, ranging from variables, lists, dictionaries, to classes, loops, modules, and creating virtual environments In addition, you will learn how to use functional and object-oriented approaches in Python programming. This course is ideal for individuals who are Beginning Python programmers who want to learn how to program or Those who are planning to work in the direction of Data Science and Machine Learning or Web developers who want to build web applications with Python or Those who want to perform tasks related to machine learning, data processing or Game developers who want to create games with Python Pygame It is particularly useful for Beginning Python programmers who want to learn how to program or Those who are planning to work in the direction of Data Science and Machine Learning or Web developers who want to build web applications with Python or Those who want to perform tasks related to machine learning, data processing or Game developers who want to create games with Python Pygame.

Enroll now: Python – Complete Python, Django, Data Science and ML Guide

Summary

Title: Python – Complete Python, Django, Data Science and ML Guide

Price: $84.99

Average Rating: 4.58

Number of Lectures: 470

Number of Published Lectures: 470

Number of Curriculum Items: 470

Number of Published Curriculum Objects: 470

Original Price: $119.99

Quality Status: approved

Status: Live

What You Will Learn

You will learn the basic principles of Python and learn all the main functions that are used most often in real projects and are in demand the most
You will practice all the examples that I will show throughout the course using the Python interpreter, Visual Studio Code with Code Runner
You will master all the necessary packages for Data Science and Machine Learning such as NumPy, Pandas, Matplotlib and Scikit-learn using Jupyter Notebook
You will learn the basic functionality of Python, ranging from variables, lists, dictionaries, to classes, loops, modules, and creating virtual environments
In addition, you will learn how to use functional and object-oriented approaches in Python programming.

Who Should Attend

Beginning Python programmers who want to learn how to program
Those who are planning to work in the direction of Data Science and Machine Learning
Web developers who want to build web applications with Python
Those who want to perform tasks related to machine learning, data processing
Game developers who want to create games with Python Pygame

Target Audiences

Beginning Python programmers who want to learn how to program
Those who are planning to work in the direction of Data Science and Machine Learning
Web developers who want to build web applications with Python
Those who want to perform tasks related to machine learning, data processing
Game developers who want to create games with Python Pygame

Python is the easiest programming language in the world. But at the same time, Python is a powerful tool with which you can solve a huge range of different tasks, from file processing to machine learning, data processing, game creation and web application development .

Thus, having learned Python, you can choose a profession from a wide range of vacancies, or you can use Python to create your own applications and solve your own problems.

This course includes many practical tasks, as well as tasks for self-fulfillment.

Python is an object oriented programming language.

Python is also a language with a huge amount of features, but in order to be able to code in Python, you need to UNDERSTAND the key concepts of Python. And that’s what I’m going to focus on with you in this course.

Before writing code and running examples, you will receive from me explanations and answers to questions WHY and WHY , and only after that HOW to write code.

I will not waste your time and therefore I have created the most effective course structure. All the examples that I will explain and run are written by me before the course, but you will write and run the code yourself.

All video lectures in this course are over 50 hours long , but expect to spend around 500 hours to master all the topics of the course, including self-completion of all practical tasks.

In this course you will learn following key topics:

Foundational Python Programming: Learn the fundamental concepts of Python programming, from data types, functions, and variables to control structures like loops and conditional statements.
Object-Oriented Programming (OOP): Dive into the principles of OOP, understanding classes, objects, inheritance, encapsulation, and polymorphism, and discover how to leverage them for efficient code organization.
File Handling and Modules: Explore file manipulation techniques, from working with directories and files using the os module to using external modules, enabling code reuse, and managing packages with PIP.
Web Development with Django: Get an introduction to web development using Django, covering MVC architecture, URL routing, model creation, and interacting with databases to build dynamic web applications.
API Development: Learn to create RESTful APIs using Django and handle API requests and responses, including authentication, authorization, and versioning.
Game Development with Pygame: Enter the world of game development with Pygame, creating interactive games by working with graphics, animations, and user input.
Data Manipulation with NumPy and Pandas: Discover data analysis and manipulation using NumPy and Pandas, covering array operations, dataframes, and handling real-world data sets.
Error Handling: Understand error handling mechanisms in Python ensuring robust and reliable code.
Package Management and Virtual Environments: Master package management using PIP, create virtual environments to isolate projects, and manage dependencies effectively.
Visualization and Machine Learning: Explore data visualization with Matplotlib, and dip your toes into machine learning concepts with Scikit-Learn, covering model creation, evaluation, and prediction.

Why it’s important: This course provides a comprehensive foundation in Python programming, from basic syntax to advanced topics like OOP, web and game development, data manipulation, and more. Understanding these concepts is crucial for building versatile applications, performing data analysis, and even stepping into machine learning, ensuring you’re equipped for a wide range of programming tasks and projects.

After completing this course, you can safely say that you KNOW Python and CAN use the most popular Python functions.

As any of my courses this course comes with 30-days money back guarantee. No questions asked!

Course Curriculum

Chapter 1: Introduction to Python

Lecture 1: Introduction to the Complete Python Guide

Lecture 2: Where to Write and Run Python Code

Lecture 3: Practice – Installing Python

Lecture 4: Practice – Using the Python Interactive Interpreter

Chapter 2: Installing and Using PyCharm IDE

Lecture 1: Installing PyCharm

Lecture 2: Getting Familiar with the PyCharm Interface

Chapter 3: Course and Project Files

Lecture 1: Download Project Files

Chapter 4: Basic Concepts in Python

Lecture 1: Key Concept in Python

Lecture 2: Main Data Types in Python

Lecture 3: Practice – Working with Main Data Types

Chapter 5: Introduction to Functions and Built-in Functions in Python

Lecture 1: Built-in Functions

Lecture 2: Practice – Defining and Using Functions

Lecture 3: Practice – Using the Return Statement in Functions

Lecture 4: Practice – Exploring Built-in Functions

Lecture 5: Practice – Using the built-in dir() Function

Lecture 6: Practice – Gathering User Input with the built-in input() Function

Chapter 6: Code Formatting and PEP8

Lecture 1: Code Indentations

Lecture 2: Practice – Working with Indentations

Lecture 3: Following PEP 8 Guidelines

Lecture 4: Enabling Auto-Formatting in PyCharm

Chapter 7: Comments

Lecture 1: Comments

Lecture 2: Practice – Adding Comments to Your Code

Chapter 8: Expressions and Instructions

Lecture 1: Understanding Expressions

Lecture 2: Understanding Statements

Lecture 3: Practice – Using Expressions

Lecture 4: Practice – Using Statements

Chapter 9: Variables

Lecture 1: Variables

Lecture 2: Practice – Defining and Using Variables

Chapter 10: Data Types and Structures

Lecture 1: Understanding Dynamic Typing

Lecture 2: Types and Data Structures Overview

Lecture 3: Variables and Objects

Lecture 4: Practice – Using the built-in id() Function

Lecture 5: Practice – Exploring Core Data Classes (str, int, bool, list, dict)

Lecture 6: Practice – Using the built-in isinstance() Function

Chapter 11: Strings

Lecture 1: Strings

Lecture 2: Practice – String Manipulation

Lecture 3: Practice – String Methods

Chapter 12: String Concatenation

Lecture 1: String Concatenation

Lecture 2: Practice – Concatenating Strings using the + Operator

Lecture 3: Practice – Using f-strings for String Formatting

Lecture 4: Practice – Alternative String Formatting Methods

Chapter 13: Numeric Types

Lecture 1: Integers

Lecture 2: Practice – Integers Manipulation

Lecture 3: Float Numbers

Lecture 4: Practice – Floating-Point Numbers Manipulation

Lecture 5: Working with Complex Numbers

Chapter 14: Boolean Type

Lecture 1: Boolean Values

Lecture 2: Practice – Working with Boolean Values

Lecture 3: Type Conversion

Chapter 15: Magic Methods

Lecture 1: Magic Methods

Lecture 2: Practice – Utilizing Magic Attributes and Methods

Chapter 16: Lists

Lecture 1: Lists

Lecture 2: List Methods

Lecture 3: Practice – Working with Lists

Lecture 4: Copying Lists

Lecture 5: Practice – Copying Lists

Lecture 6: TASK – Working with Lists

Chapter 17: Dictionaries

Lecture 1: Dictionaries

Lecture 2: Practice – Manipulating Dictionaries

Lecture 3: Practice – Dictionary Methods

Lecture 4: Other Operations with Dictionaries

Lecture 5: Practice – Using the get() Method for Dictionaries

Lecture 6: Practice – Converting Other Types to a Dictionary

Lecture 7: TASK – Working with Dictionaries

Chapter 18: Tuples

Lecture 1: Tuples

Lecture 2: Practice – Tuples Manipulation

Chapter 19: Sets

Lecture 1: Sets

Lecture 2: Practice – Working with Sets

Lecture 3: Understanding Set Theory

Lecture 4: Set Methods

Lecture 5: Practice – Usage of the Set Methods

Lecture 6: Practice – Calculating Symmetric Difference of Sets

Lecture 7: TASK – Working with Sets

Chapter 20: Ranges

Lecture 1: Ranges

Lecture 2: Practice – Range Manipulation

Lecture 3: Practice – Range Methods and Attributes

Chapter 21: Working with Sequences

Lecture 1: Built-in Functions for Sequences

Lecture 2: Built-in zip() Function

Lecture 3: Practice – Working with zip Objects

Instructors

Bogdan Stashchuk | Software Engineer, MBA, PhD
Just keep learning – stashchuk

Rating Distribution

1 stars: 1 votes
2 stars: 1 votes
3 stars: 7 votes
4 stars: 41 votes
5 stars: 107 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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