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Python | Python Projects & Quizzes For Python Data Science

Posted By: ELK1nG
Python | Python Projects & Quizzes For Python Data Science

Python | Python Projects & Quizzes For Python Data Science
Published 5/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.52 GB | Duration: 14h 36m

Python | Python Programming Language with hands-on Python projects & quizzes, Python for Data Science & Machine Learning

What you'll learn

Python is a computer programming language often used to build websites and software, automate tasks, and conduct data analysis.

Python is a general-purpose language, meaning it can be used to create a variety of different programs and isn't specialized for any specific problems.

Whether you work in artificial intelligence or finance or are pursuing a career in web development or data science, Python is one of the most important skills

Its simple syntax and readability makes Python perfect for Flask, Django, data science, and machine learning.

Installing Anaconda Distribution for Windows

Installing Anaconda Distribution for MacOs

Installing Anaconda Distribution for Linux

Reviewing The Jupyter Notebook

Reviewing The Jupyter Lab

Python Introduction

First Step to Coding

Using Quotation Marks in Python Coding

How Should the Coding Form and Style Be (Pep8)

Introduction to Basic Data Structures in Python

Performing Assignment to Variables

Performing Complex Assignment to Variables

Type Conversion

Arithmetic Operations in Python

Examining the Print Function in Depth

Escape Sequence Operations

Boolean Logic Expressions

Order Of Operations In Boolean Operators

Practice with Python

Examining Strings Specifically

Accessing Length Information (Len Method)

Search Method In Strings Startswith(), Endswith()

Character Change Method In Strings Replace()

Spelling Substitution Methods in String

Character Clipping Methods in String

Indexing and Slicing Character String

Complex Indexing and Slicing Operations

String Formatting with Arithmetic Operations

String Formatting With % Operator

String Formatting With String Format Method

String Formatting With f-string Method

Creation of List

Reaching List Elements – Indexing and Slicing

Adding & Modifying & Deleting Elements of List

Adding and Deleting by Methods

Adding and Deleting by Index

Other List Methods

Creation of Tuple

Reaching Tuple Elements Indexing And Slicing

Creation of Dictionary

Reaching Dictionary Elements

Adding & Changing & Deleting Elements in Dictionary

Dictionary Methods

Creation of Set

Adding & Removing Elements Methods in Sets

Difference Operation Methods In Sets

Asking Questions to Sets with Methods

Comparison OperatorsIntersection & Union Methods In Sets

Structure of “if” Statements

Structure of “if-else” Statements

Structure of “if-elif-else” Statements

Structure of Nested “if-elif-else” Statements

Coordinated Programming with “IF” and “INPUT”

Ternary Condition

For Loop in Python

For Loop in Python(Reinforcing the Topic)

Using Conditional Expressions and For Loop Together

Continue Command

Break Command

List Comprehension

While Loop in Python

While Loops in Python Reinforcing the Topic

Getting know to the Functions

How to Write Function

Return Expression in Functions

Writing Functions with Multiple Argument

Writing Docstring in Functions

Using Functions and Conditional Expressions Together

Arguments and Parameters

High Level Operations with Arguments

all(), any() Functions

map() Function

filter() Function

zip() Function

enumerate() Function

sum() Function

max(), min() Functions

round() Function

Lambda Function

Local and Global Variables

Features of Class

Instantiation of Class

Attribute of Instantiation

Write Function in the Class

Inheritance Structure

If you are new to Python, data science or have no idea about what data scientist does no problem, you will learn anything you need to start to Python data scien

If you are a software developer or familiar to other programming language and you want to start a new world, you are also in the right place.

You will encounter many businesses that use Python and its libraries for data science.

In this course you need no previous Knowledge about Python, data science.

What does it mean that Python is object-oriented? Python is a multi-paradigm language, which means that it supports many programming approaches.

That’s why Udemy features a host of top-rated OOP courses tailored for specific languages, like Java, C#, and Python.

Most programmers will choose to learn the object oriented programming paradigm in a specific language.

Requirements

A working computer (Windows, Mac, or Linux)

No prior knowledge of Python for beginners is required

Motivation to learn the the second largest number of job postings relative program language among all others

Desire to learn machine learning python

Curiosity for python programming

Desire to learn python programming, pycharm, python pycharm

Nothing else! It’s just you, your computer and your ambition to get started today

Description

Welcome to my " Python | Python Projects & Quizzes for Python Data Science " course.Python | Python Programming Language with hands-on Python projects & quizzes, Python for Data Science & Machine Learning Python is a computer programming language often used to build websites and software, automate tasks, and conduct data analysis. Python is a general-purpose language, meaning it can be used to create a variety of different programs and isn't specialized for any specific problems.Python instructors at OAK Academy specialize in everything from software development to data analysis and are known for their effective, friendly instruction for students of all levels.Whether you work in machine learning or finance or are pursuing a career in web development or data science, Python is one of the most important skills you can learn.Python's simple syntax is especially suited for desktop, web, and business applications. Python's design philosophy emphasizes readability and usability. Python was developed upon the premise that there should be only one way (and preferably one obvious way) to do things, a philosophy that has resulted in a strict level of code standardization. The core programming language is quite small and the standard library is also large. In fact, Python's large library is one of its greatest benefits, providing a variety of different tools for programmers suited for many different tasks.Do you want to learn one of the employer’s most requested skills? If you think so, you are at the right place. Python, Python for data siene, machine learning, python data science, Django, python programming, machine learning python, python programming language, coding, data science, data analysis, programming languages.We've designed for you "Python | Python Projects & Quizzes for Python Data Science” a straightforward course for the Python programming language.In the course, you will have down-to-earth way explanations of hands-on projects. With my course, you will learn Python Programming step-by-step. I made Python 3 programming simple and easy with exercises, challenges, and lots of real-life examples.This Python course is for everyone!My "Python: Learn Python with Real Python Hands-On Examples" is for everyone! If you don’t have any previous experience, not a problem! This course is expertly designed to teach everyone from complete beginners, right through to professionals ( as a refresher).Why Python?Python is a general-purpose, high-level, and multi-purpose programming language. The best thing about Python is, that it supports a lot of today’s technology including vast libraries for Twitter, data mining, scientific calculations, designing, back-end server for websites, engineering simulations, artificial learning, augmented reality and what not! Also, it supports all kinds of App development.No prior knowledge is needed!Python doesn't need any prior knowledge to learn it and the Ptyhon code is easy to understand for beginners.What you will learn?In this course, we will start from the very beginning and go all the way to programming with hands-on examples . We will first learn how to set up a lab and install needed software on your machine. Then during the course, you will learn the fundamentals of Python development likeInstalling Anaconda Distribution for WindowsInstalling Anaconda Distribution for MacOsInstalling Anaconda Distribution for LinuxReviewing The Jupyter NotebookReviewing The Jupyter LabPython IntroductionFirst Step to CodingUsing Quotation Marks in Python CodingHow Should the Coding Form and Style Be (Pep8)Introduction to Basic Data Structures in PythonPerforming Assignment to VariablesPerforming Complex Assignment to VariablesType ConversionArithmetic Operations in PythonExamining the Print Function in DepthEscape Sequence OperationsBoolean Logic ExpressionsOrder Of Operations In Boolean OperatorsPractice with PythonExamining Strings SpecificallyAccessing Length Information (Len Method)Search Method In Strings Startswith(), Endswith()Character Change Method In Strings Replace()Spelling Substitution Methods in StringCharacter Clipping Methods in StringIndexing and Slicing Character StringComplex Indexing and Slicing OperationsString Formatting with Arithmetic OperationsString Formatting With % OperatorString Formatting With String.Format MethodString Formatting With f-string MethodCreation of ListReaching List Elements – Indexing and SlicingAdding & Modifying & Deleting Elements of ListAdding and Deleting by MethodsAdding and Deleting by IndexOther List MethodsCreation of TupleReaching Tuple Elements Indexing And SlicingCreation of DictionaryReaching Dictionary ElementsAdding & Changing & Deleting Elements in DictionaryDictionary MethodsCreation of SetAdding & Removing Elements Methods in SetsDifference Operation Methods In SetsIntersection & Union Methods In SetsAsking Questions to Sets with MethodsComparison OperatorsStructure of “if” StatementsStructure of “if-else” StatementsStructure of “if-elif-else” StatementsStructure of Nested “if-elif-else” StatementsCoordinated Programming with “IF” and “INPUT”Ternary ConditionFor Loop in PythonFor Loop in Python(Reinforcing the Topic)Using Conditional Expressions and For Loop TogetherContinue CommandBreak CommandList ComprehensionWhile Loop in PythonWhile Loops in Python Reinforcing the TopicGetting know to the FunctionsHow to Write FunctionReturn Expression in FunctionsWriting Functions with Multiple ArgumentWriting Docstring in FunctionsUsing Functions and Conditional Expressions TogetherArguments and ParametersHigh Level Operations with Argumentsall(), any() Functionsmap() Functionfilter() Functionzip() Functionenumerate() Functionmax(), min() Functionssum() Functionround() FunctionLambda FunctionLocal and Global VariablesFeatures of ClassInstantiation of ClassAttribute of InstantiationWrite Function in the ClassInheritance StructureHands-on Real Python Projects With my up-to-date course, you will have a chance to keep yourself up-to-date and equip yourself with a range of Python programming skills. I am also happy to tell you that I will be constantly available to support your learning and answer questions.Do not forget ! Python for beginners has the second largest number of job postings relative to all other languages. So it will earn you a lot of money and will bring a great change in your resume.What is python?Machine learning python is a general-purpose, object-oriented, high-level programming language. Whether you work in artificial intelligence or finance or are pursuing a career in web development or data science, Python bootcamp is one of the most important skills you can learn. Python's simple syntax is especially suited for desktop, web, and business applications. Python's design philosophy emphasizes readability and usability. Python was developed on the premise that there should be only one way (and preferably, one obvious way) to do things, a philosophy that resulted in a strict level of code standardization. The core programming language is quite small and the standard library is also large. In fact, Python's large library is one of its greatest benefits, providing different tools for programmers suited for a variety of tasks.Python vs. R: What is the Difference?Python and R are two of today's most popular programming tools. When deciding between Python and R in data science , you need to think about your specific needs. On one hand, Python is relatively easy for beginners to learn, is applicable across many disciplines, has a strict syntax that will help you become a better coder, and is fast to process large datasets. On the other hand, R has over 10,000 packages for data manipulation, is capable of easily making publication-quality graphics, boasts superior capability for statistical modeling, and is more widely used in academia, healthcare, and finance.What does it mean that Python is object-oriented?Python is a multi-paradigm language, which means that it supports many data analysis programming approaches. Along with procedural and functional programming styles, Python also supports the object-oriented style of programming. In object-oriented programming, a developer completes a programming project by creating Python objects in code that represent objects in the actual world. These objects can contain both the data and functionality of the real-world object. To generate an object in Python you need a class. You can think of a class as a template. You create the template once, and then use the template to create as many objects as you need. Python classes have attributes to represent data and methods that add functionality. A class representing a car may have attributes like color, speed, and seats and methods like driving, steering, and stopping.What are the limitations of Python?Python is a widely used, general-purpose programming language, but it has some limitations. Because Python in machine learning is an interpreted, dynamically typed language, it is slow compared to a compiled, statically typed language like C. Therefore, Python is useful when speed is not that important. Python's dynamic type system also makes it use more memory than some other programming languages, so it is not suited to memory-intensive applications. The Python virtual engine that runs Python code runs single-threaded, making concurrency another limitation of the programming language. Though Python is popular for some types of game development, its higher memory and CPU usage limits its usage for high-quality 3D game development. That being said, computer hardware is getting better and better, and the speed and memory limitations of Python are getting less and less relevant.How is Python used?Python is a general programming language used widely across many industries and platforms. One common use of Python is scripting, which means automating tasks in the background. Many of the scripts that ship with Linux operating systems are Python scripts. Python is also a popular language for machine learning, data analytics, data visualization, and data science because its simple syntax makes it easy to quickly build real applications. You can use Python to create desktop applications. Many developers use it to write Linux desktop applications, and it is also an excellent choice for web and game development. Python web frameworks like Flask and Django are a popular choice for developing web applications. Recently, Python is also being used as a language for mobile development via the Kivy third-party library.What jobs use Python?Python is a popular language that is used across many industries and in many programming disciplines. DevOps engineers use Python to script website and server deployments. Web developers use Python to build web applications, usually with one of Python's popular web frameworks like Flask or Django. Data scientists and data analysts use Python to build machine learning models, generate data visualizations, and analyze big data. Financial advisors and quants (quantitative analysts) use Python to predict the market and manage money. Data journalists use Python to sort through information and create stories. Machine learning engineers use Python to develop neural networks and artificial intelligent systems.How do I learn Python on my own?Python has a simple syntax that makes it an excellent programming language for a beginner to learn. To learn Python on your own, you first must become familiar with the syntax. But you only need to know a little bit about Python syntax to get started writing real code; you will pick up the rest as you go. Depending on the purpose of using it, you can then find a good Python tutorial, book, or course that will teach you the programming language by building a complete application that fits your goals. If you want to develop games, then learn Python game development. If you're going to build web applications, you can find many courses that can teach you that, too. Udemy’s online courses are a great place to start if you want to learn Python on your own.Why would you want to take this course?Our answer is simple: The quality of teaching.OAK Academy based in London is an online education company. OAK Academy gives education in the field of IT, Software, Design, development in English, Portuguese, Spanish, Turkish, and a lot of different languages on the Udemy platform where it has over 2000 hours of video education lessons. OAK Academy both increases its education series number by publishing new courses, and it makes students aware of all the innovations of already published courses by upgrading.When you enroll, you will feel the OAK Academy`s seasoned developers' expertise. Questions sent by students to our instructors are answered by our instructors within 48 hours at the latest.Video and Audio Production QualityAll our videos are created/produced as high-quality video and audio to provide you the best learning experience.You will be,Seeing clearlyHearing clearlyMoving through the course without distractionsYou'll also get:Lifetime Access to The CourseFast & Friendly Support in the Q&A sectionUdemy Certificate of Completion Ready for DownloadDive in now!We offer full support, answering any questions.See you in the " Python | Python Projects & Quizzes for Python Data Science " course.Python | Python Programming Language with hands-on Python projects & quizzes, Python for Data Science & Machine Learning

Overview

Section 1: Installations

Lecture 1 Installing Anaconda Distribution for Windows

Lecture 2 Installing Anaconda Distribution for MacOs

Lecture 3 Installing Anaconda Distribution for Linux

Lecture 4 Reviewing The Jupyter Notebook

Lecture 5 Reviewing The Jupyter Lab

Lecture 6 Installing PyCharm IDE for Windows

Lecture 7 "Installing PyCharm IDE for Mac "

Section 2: First Step to Coding

Lecture 8 Python Introduction

Lecture 9 Project Files

Lecture 10 FAQ regarding Python

Lecture 11 First Step to Coding

Lecture 12 Using Quotation Marks in Python Coding

Lecture 13 How Should the Coding Form and Style Be (Pep8)

Section 3: Basic Operations with Python

Lecture 14 Introduction to Basic Data Structures in Python

Lecture 15 Performing Assignment to Variables

Lecture 16 Performing Complex Assignment to Variables

Lecture 17 Type Conversion

Lecture 18 Arithmetic Operations in Python

Lecture 19 Examining the Print Function in Depth

Lecture 20 Escape Sequence Operations

Section 4: Boolean Data Type in Python Programming Language

Lecture 21 Boolean Logic Expressions

Lecture 22 Order Of Operations In Boolean Operators

Lecture 23 Practice with Python

Section 5: String Data Type in Python Programming Language

Lecture 24 Examining Strings Specifically

Lecture 25 Accessing Length Information (Len Method)

Lecture 26 Search Method In Strings Startswith(), Endswith()

Lecture 27 Character Change Method In Strings Replace()

Lecture 28 Spelling Substitution Methods in String

Lecture 29 Character Clipping Methods in String

Lecture 30 Indexing and Slicing Character String

Lecture 31 Complex Indexing and Slicing Operations

Lecture 32 String Formatting with Arithmetic Operations

Lecture 33 String Formatting With % Operator

Lecture 34 String Formatting With String.Format Method

Lecture 35 String Formatting With f-string Method

Section 6: List Data Structure in Python Programming Language

Lecture 36 Creation of List

Lecture 37 Reaching List Elements – Indexing and Slicing

Lecture 38 Adding & Modifying & Deleting Elements of List

Lecture 39 Adding and Deleting by Methods

Lecture 40 Adding and Deleting by Index

Lecture 41 Other List Methods

Section 7: Tuple Data Structure in Python Programming Language

Lecture 42 Creation of Tuple

Lecture 43 Reaching Tuple Elements Indexing And Slicing

Section 8: Dictionary Data Structure in Python Programming Language

Lecture 44 Creation of Dictionary

Lecture 45 Reaching Dictionary Elements

Lecture 46 Adding & Changing & Deleting Elements in Dictionary

Lecture 47 Dictionary Methods

Section 9: Set Data Structure in Python Programming Language

Lecture 48 Creation of Set

Lecture 49 Adding & Removing Elements Methods in Sets

Lecture 50 Difference Operation Methods In Sets

Lecture 51 Intersection & Union Methods In Sets

Lecture 52 Asking Questions to Sets with Methods

Section 10: Conditional Expressions in Python Programming Language

Lecture 53 Comparison Operators

Lecture 54 Structure of “if” Statements

Lecture 55 Structure of “if-else” Statements

Lecture 56 Structure of “if-elif-else” Statements

Lecture 57 Structure of Nested “if-elif-else” Statements

Lecture 58 Coordinated Programming with “IF” and “INPUT”

Lecture 59 Ternary Condition

Section 11: For Loop in Python Programming Language

Lecture 60 For Loop in Python

Lecture 61 For Loop in Python(Reinforcing the Topic)

Lecture 62 Using Conditional Expressions and For Loop Together

Lecture 63 Continue Command

Lecture 64 Break Command

Lecture 65 List Comprehension

Section 12: While Loop in Python Programming Language

Lecture 66 While Loop in Python

Lecture 67 While Loops in Python Reinforcing the Topic

Section 13: Functions in Python Programming Language

Lecture 68 Getting know to the Functions

Lecture 69 How to Write Function

Lecture 70 Return Expression in Functions

Lecture 71 Writing Functions with Multiple Argument

Lecture 72 Writing Docstring in Functions

Lecture 73 Using Functions and Conditional Expressions Together

Section 14: Arguments And Parameters in Python Programming Language

Lecture 74 Arguments and Parameters

Lecture 75 High Level Operations with Arguments

Section 15: Most Used Functions in Python Programming Language

Lecture 76 all(), any() Functions

Lecture 77 map() Function

Lecture 78 filter() Function

Lecture 79 zip() Function

Lecture 80 enumerate() Function

Lecture 81 max(), min() Functions

Lecture 82 sum() Function

Lecture 83 round() Function

Lecture 84 Lambda Function

Section 16: Class Structure in Python Programming Language

Lecture 85 Local and Global Variables

Lecture 86 Features of Class

Lecture 87 Instantiation of Class

Lecture 88 Attribute of Instantiation

Lecture 89 Write Function in the Class

Lecture 90 Inheritance Structure

Section 17: OOP

Lecture 91 OOP: Logic of OOP

Lecture 92 OOP: Constructor

Lecture 93 OOP: Methods

Lecture 94 OOP: Inheritance

Lecture 95 OOP: Overriding and Overloading

Section 18: Python Marathon Projects

Lecture 96 Example : E-mail Generator

Lecture 97 Example : BMI Calculator

Lecture 98 Example : Tip Calculator

Lecture 99 Example : Bottle Deposits

Lecture 100 Example : Name The Shape

Lecture 101 Example : Admission Price

Lecture 102 Example : Note to Frequency

Lecture 103 Example : Frequency to Note

Lecture 104 Example : Parity Bits

Lecture 105 Example : Reduce a Fraction to Lowest Terms

Lecture 106 Example : Two Dice Simulation

Lecture 107 Example : String Edit Distance

Lecture 108 Example : Run-Length Encoding

Lecture 109 Example : Caesar Cipher

Lecture 110 Example : Number Guessing Game

Lecture 111 Example : Login Controller

Lecture 112 Example : Password Generator

Lecture 113 Example : Sorted Order

Lecture 114 Example : Fibonacci

Lecture 115 Example : Team Builder

Lecture 116 Example : Finding Prime Number

Lecture 117 Example : Word Counter

Lecture 118 Example : Overlap

Lecture 119 Example : Perfect Number Finder

Lecture 120 Example : Playing Card

Lecture 121 Example : The Sieve of Eratosthenes

Lecture 122 Example : Anagrams

Lecture 123 Example : Roulette Game

Lecture 124 Example : Bingo Card

Lecture 125 Example : Rock Paper Scissors

Lecture 126 Example : Remote Controller

Section 19: Extra

Lecture 127 Python | Python Projects & Quizzes for Python Data Science

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