Python Tutorial for Beginners - Learn Python in 5 Hours [FULL COURSE]

Python Tutorial for Beginners | Full Python Course | Learn Python in 2021

In this complete Python course you will learn everything you need to get started with Python. 🚀 🤩
By the end of this course, you will have a good understanding of the concepts and hands-on experience with several demo projects you can follow along.

Python is the most popular programming language out there and it is used for so many different industries, like: Web Development, Data Science, Machine Learning and DevOps Automation. So learning Python is definitely a good idea! 💪

▬▬▬▬▬▬ U S E F U L L I N K S 🔗 ▬▬▬▬▬▬
► GitLab Source Code: https://gitlab.com/nanuchi/python-programming
► PyCharm Download: https://www.jetbrains.com/pycharm/download
► Python Installation Steps for Windows - Important click “Add to PATH” https://docs.python.org/3/using/windows.html#installation-steps

▬▬▬▬▬▬ T I M E S T A M P S ⏰ ▬▬▬▬▬▬

  • 0:00 - Course Intro & Course Overview
  • 2:53 - Introduction to Python
  • 07:01 - Installation and Local Setup with PyCharm
  • 14:10 - Write our first Python program
  • 15:33 - Python IDE vs simple File Editor
  • 19:04 - Strings and Number Data Types
  • 30:11 - Variables in Python
  • 39:33 - Encapsulate Logic with Functions
  • 54:00 - Scope
  • 59:50 - Accepting User Input
  • 1:15:28 - Conditionals (if / else) and Boolean Data Type
  • 1:44:18 - Error Handling with Try / Except
  • 1:50:11 - While Loops
  • 2:02:43 - Lists and For Loops
  • 2:21:51 - Thanks Jetbrains!
  • 2:23:17 - Comments in Python
  • 2:27:23 - Sets
  • 2:38:31 - Built-In Functions
  • 2:44:25 - Dictionary Data Type
  • 3:01:32 - Modularize your project with Modules
  • 3:20:09 - Project: Countdown App
  • 3:40:27 - Packages, PyPI and pip
  • 3:54:06 - Project: Automation with Python (Working with Spreadsheets)
  • 4:44:02 - Object Oriented Programming: Classes and Objects
  • 5:14:35 - Project: API Request to GitLab
  • 5:30:23 - Wrap Up

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Python Tutorial for Beginners - Learn Python in 5 Hours [FULL COURSE]
Sival Alethea

Sival Alethea

1624291780

Learn Python - Full Course for Beginners [Tutorial]

This course will give you a full introduction into all of the core concepts in python. Follow along with the videos and you’ll be a python programmer in no time!
⭐️ Contents ⭐
⌨️ (0:00) Introduction
⌨️ (1:45) Installing Python & PyCharm
⌨️ (6:40) Setup & Hello World
⌨️ (10:23) Drawing a Shape
⌨️ (15:06) Variables & Data Types
⌨️ (27:03) Working With Strings
⌨️ (38:18) Working With Numbers
⌨️ (48:26) Getting Input From Users
⌨️ (52:37) Building a Basic Calculator
⌨️ (58:27) Mad Libs Game
⌨️ (1:03:10) Lists
⌨️ (1:10:44) List Functions
⌨️ (1:18:57) Tuples
⌨️ (1:24:15) Functions
⌨️ (1:34:11) Return Statement
⌨️ (1:40:06) If Statements
⌨️ (1:54:07) If Statements & Comparisons
⌨️ (2:00:37) Building a better Calculator
⌨️ (2:07:17) Dictionaries
⌨️ (2:14:13) While Loop
⌨️ (2:20:21) Building a Guessing Game
⌨️ (2:32:44) For Loops
⌨️ (2:41:20) Exponent Function
⌨️ (2:47:13) 2D Lists & Nested Loops
⌨️ (2:52:41) Building a Translator
⌨️ (3:00:18) Comments
⌨️ (3:04:17) Try / Except
⌨️ (3:12:41) Reading Files
⌨️ (3:21:26) Writing to Files
⌨️ (3:28:13) Modules & Pip
⌨️ (3:43:56) Classes & Objects
⌨️ (3:57:37) Building a Multiple Choice Quiz
⌨️ (4:08:28) Object Functions
⌨️ (4:12:37) Inheritance
⌨️ (4:20:43) Python Interpreter
📺 The video in this post was made by freeCodeCamp.org
The origin of the article: https://www.youtube.com/watch?v=rfscVS0vtbw&list=PLWKjhJtqVAblfum5WiQblKPwIbqYXkDoC&index=3

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Sival Alethea

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1624395600

MongoDB with Python Crash Course - Tutorial for Beginners. DO NOT MISS!!!

Learn the most popular NoSQL / document database: MongoDB. In this quickstart tutorial, you’ll be up and running with MongoDB and Python.
⭐️Course Contents⭐️
⌨️ (0:00:00) Welcome
⌨️ (0:04:33) Intro to MongoDB
⌨️ (0:07:49) How do document DBs work?
⌨️ (0:10:34) Who uses MongoDB
⌨️ (0:13:02) Data modeling
⌨️ (0:16:30) Modeling guidelines
⌨️ (0:22:11) Integration database
⌨️ (0:24:23) Getting demo code
⌨️ (0:30:07) How ODMs work?
⌨️ (0:32:55) Introduction to mongoengine
⌨️ (0:34:01) Demo: Registering connections with MongoEngine
⌨️ (0:37:20) Concept: Registering connections
⌨️ (0:39:14) Demo: Defining mongoengine entities (classes)
⌨️ (0:45:22) Concept: mongoengine entities
⌨️ (0:49:03) Demo: Create a new account
⌨️ (0:56:55) Demo: Robo 3T for viewing and managing data
⌨️ (0:58:18) Demo: Login
⌨️ (1:00:07) Demo: Register a cage
⌨️ (1:10:28) Demo: Add a bookable time as a host
⌨️ (1:16:13) Demo: Managing your snakes as a guest
⌨️ (1:19:18) Demo: Book a cage as a guest
⌨️ (1:33:41) Demo: View your bookings as guest
⌨️ (1:41:29) Demo: View bookings as host
⌨️ (1:46:18) Concept: Inserting documents
⌨️ (1:47:28) Concept: Queries
⌨️ (1:48:09) Concept: Querying subdocuments with mongoengine
⌨️ (1:49:37) Concept: Query using operators
⌨️ (1:50:24) Concept: Updating via whole documents
⌨️ (1:51:46) Concept: Updating via in-place operators
⌨️ (1:54:01) Conclusion

📺 The video in this post was made by freeCodeCamp.org
The origin of the article: https://www.youtube.com/watch?v=E-1xI85Zog8&list=PLWKjhJtqVAbnqBxcdjVGgT3uVR10bzTEB&index=10
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Python tutorial Full Course from scratch

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Sival Alethea

Sival Alethea

1624378020

Python Django Web Framework - Full Course for Beginners. DO NOT MISS!!!

Learn the Python Django framework with this free full course. Django is an extremely popular and fully featured server-side web framework, written in Python. Django allows you to quickly create web apps.
⭐️Course Contents ⭐️
⌨️ (0:00:00) 1 - Welcome
⌨️ (0:01:14) 2 - Installing to Get Started
⌨️ (0:05:02) 3 - Setup your Virtual Environment for Django
⌨️ (0:14:39) 4 - Create a Blank Django Project
⌨️ (0:18:54) 5 - Setup Your Code Text Editor
⌨️ (0:22:27) 6 - Settings
⌨️ (0:29:58) 7 - Built-In Components
⌨️ (0:33:57) 8 - Your First App Component
⌨️ (0:42:34) 9 - Create Product Objects in the Python Shell
⌨️ (0:46:18) 10 - New Model Fields
⌨️ (0:52:52) 11 - Change a Model
⌨️ (0:59:27) 12 - Default Homepage to Custom Homepage
⌨️ (1:04:48) 13 - URL Routing and Requests
⌨️ (1:10:23) 14 - Django Templates
⌨️ (1:16:50) 15 - Django Templating Engine Basics
⌨️ (1:24:00) 16 - Include Template Tag
⌨️ (1:26:49) 17 - Rendering Context in a Template
⌨️ (1:33:21) 18 - For Loop in a Template
⌨️ (1:37:01) 19 - Using Conditions in a Template
⌨️ (1:42:17) 20 - Template Tags and Filters
⌨️ (1:48:59) 21 - Render Data from the Database with a Model
⌨️ (1:59:55) 22 - How Django Templates Load with Apps
⌨️ (2:06:50) 23 - Django Model Forms
⌨️ (2:14:16) 24 - Raw HTML Form
⌨️ (2:25:33) 25 - Pure Django Form
⌨️ (2:35:30) 26 - Form Widgets
⌨️ (2:41:29) 27 - Form Validation Methods
⌨️ (2:48:59) 28 - Initial Values for Forms
⌨️ (2:51:42) 29 - Dynamic URL Routing
⌨️ (2:54:26) 30 - Handle DoesNotExist
⌨️ (2:56:24) 31 - Delete and Confirm
⌨️ (2:58:24) 32 - View of a List of Database Objects
⌨️ (3:00:00) 33 - Dynamic Linking of URLs
⌨️ (3:01:17) 34 - Django URLs Reverse
⌨️ (3:03:10) 35 - In App URLs and Namespacing
⌨️ (3:07:35) 36 - Class Based Views - ListView
⌨️ (3:10:45) 37 - Class Based Views - DetailView
⌨️ (3:15:38) 38 - Class Based Views - CreateView and UpdateView
⌨️ (3:21:23) 39 - Class Based Views - DeleteView
⌨️ (3:24:02) 40 - Function Based View to Class Based View
⌨️ (3:27:15) 41 - Raw Detail Class Based View
⌨️ (3:30:31) 42 - Raw List Class Based View
⌨️ (3:33:32) 43 - Raw Create Class Based View
⌨️ (3:26:03) 44 - Form Validation on a Post Method
⌨️ (3:37:58) 45 - Raw Update Class Based View
⌨️ (3:41:13) 46 - Raw Delete Class Based View
⌨️ (3:42:17) 47 - Custom Mixin for Class Based Views

📺 The video in this post was made by freeCodeCamp.org
The origin of the article: https://www.youtube.com/watch?v=F5mRW0jo-U4&list=PLWKjhJtqVAbnqBxcdjVGgT3uVR10bzTEB&index=6
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Sival Alethea

Sival Alethea

1624305600

Learn Data Science Tutorial - Full Course for Beginners. DO NOT MISS!!!

Learn Data Science is this full tutorial course for absolute beginners. Data science is considered the “sexiest job of the 21st century.” You’ll learn the important elements of data science. You’ll be introduced to the principles, practices, and tools that make data science the powerful medium for critical insight in business and research. You’ll have a solid foundation for future learning and applications in your work. With data science, you can do what you want to do, and do it better. This course covers the foundations of data science, data sourcing, coding, mathematics, and statistics.
⭐️ Course Contents ⭐️
⌨️ Part 1: Data Science: An Introduction: Foundations of Data Science

  • Welcome (1.1)
  • Demand for Data Science (2.1)
  • The Data Science Venn Diagram (2.2)
  • The Data Science Pathway (2.3)
  • Roles in Data Science (2.4)
  • Teams in Data Science (2.5)
  • Big Data (3.1)
  • Coding (3.2)
  • Statistics (3.3)
  • Business Intelligence (3.4)
  • Do No Harm (4.1)
  • Methods Overview (5.1)
  • Sourcing Overview (5.2)
  • Coding Overview (5.3)
  • Math Overview (5.4)
  • Statistics Overview (5.5)
  • Machine Learning Overview (5.6)
  • Interpretability (6.1)
  • Actionable Insights (6.2)
  • Presentation Graphics (6.3)
  • Reproducible Research (6.4)
  • Next Steps (7.1)

⌨️ Part 2: Data Sourcing: Foundations of Data Science (1:39:46)

  • Welcome (1.1)
  • Metrics (2.1)
  • Accuracy (2.2)
  • Social Context of Measurement (2.3)
  • Existing Data (3.1)
  • APIs (3.2)
  • Scraping (3.3)
  • New Data (4.1)
  • Interviews (4.2)
  • Surveys (4.3)
  • Card Sorting (4.4)
  • Lab Experiments (4.5)
  • A/B Testing (4.6)
  • Next Steps (5.1)

⌨️ Part 3: Coding (2:32:42)

  • Welcome (1.1)
  • Spreadsheets (2.1)
  • Tableau Public (2.2)
  • SPSS (2.3)
  • JASP (2.4)
  • Other Software (2.5)
  • HTML (3.1)
  • XML (3.2)
  • JSON (3.3)
  • R (4.1)
  • Python (4.2)
  • SQL (4.3)
  • C, C++, & Java (4.4)
  • Bash (4.5)
  • Regex (5.1)
  • Next Steps (6.1)

⌨️ Part 4: Mathematics (4:01:09)

  • Welcome (1.1)
  • Elementary Algebra (2.1)
  • Linear Algebra (2.2)
  • Systems of Linear Equations (2.3)
  • Calculus (2.4)
  • Calculus & Optimization (2.5)
  • Big O (3.1)
  • Probability (3.2)

⌨️ Part 5: Statistics (4:44:03)

  • Welcome (1.1)
  • Exploration Overview (2.1)
  • Exploratory Graphics (2.2)
  • Exploratory Statistics (2.3)
  • Descriptive Statistics (2.4)
  • Inferential Statistics (3.1)
  • Hypothesis Testing (3.2)
  • Estimation (3.3)
  • Estimators (4.1)
  • Measures of Fit (4.2)
  • Feature Selection (4.3)
  • Problems in Modeling (4.4)
  • Model Validation (4.5)
  • DIY (4.6)
  • Next Step (5.1)

📺 The video in this post was made by freeCodeCamp.org
The origin of the article: https://www.youtube.com/watch?v=ua-CiDNNj30&list=PLWKjhJtqVAblfum5WiQblKPwIbqYXkDoC&index=7
🔺 DISCLAIMER: The article is for information sharing. The content of this video is solely the opinions of the speaker who is not a licensed financial advisor or registered investment advisor. Not investment advice or legal advice.
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