The 2023 Ultimate AI ChatGPT & Python Programming Bundle

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Content
3.0 hours
Lessons
15

Create a ChatGPT A.I. Bot with Tkinter & Python

Learn How to Connect Text-to-Speech Apps to an Artificial Intelligence API

By John Elder | in Online Courses

In this course, you will learn how to make graphical user interfaces for Python using Tkinter, and how to connect those apps to the OpenAI Text Completion Artificial Intelligence API. You'll be surprised just how quickly you can create some pretty cool-looking apps! If you've seen ChatGPT recently and want to learn how to use these types of tools programmatically, then this is the course for you!

4.5/5 average rating: ★ ★ ★ ★

  • Access 15 lectures & 3 hours of content 24/7
  • Learn how to use a wide variety of widgets
  • Create multiple Tkinter projects
  • Gain in-depth knowledge of how themes and styles work in Tkinter
  • Create your own styles and use them in your applications
John Elder | Founder of Codemy
4.4/5 Instructor Rating: ★ ★ ★ ★

John Elder is a pioneer in Web Development who created one of the first Internet advertising networks back in 1997. He sold it to a publicly traded company at the height of the dot com boom and then went on to create the best-selling Submission-Spider search engine submission software that's been used by over 3 million individuals and small businesses in over 45 countries. Today he teaches Web Development courses at Codemy the online code school he founded.

Important Details

  • Length of time users can access this course: lifetime
  • Access options: desktop & mobile
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: beginner
  • Updates included
  • Have questions on how digital purchases work? Learn more here

Requirements

  • A basic understanding of Python and Tkinter is helpful

Course Outline

  • Your First Program

  • Introduction and Setup

    • Introduction - 2:13
    • Install Python - 1:55
    • Install Sublime Text and Git Bash Terminal - 2:48
    • Set Up OpenAI API Key - 1:57
    • Create a Virtual Environment - 3:06
    • Pip Install The Necessary Libraries - 1:54
    • Create the App! - 4:12
  • Build Tkinter GUI

    • Create a Text Widget - 4:44
    • Add A Scrollbar To The Text Widget - 2:37
    • Create an Entry Widget - 2:11
    • Add Some Buttons - 5:19
    • API Key Section - 4:23
    • Show and Hide the API Key - 3:10
    • API Key - 5:03
    • Save the API Key - 3:57
    • Add Error Handling - 2:46
    • Clear The Screen - 2:34
  • Using The ChatGPT API

    • Check For API Key - 4:58
    • Query ChatGPT - 5:12
    • Parse Results From ChatGPT - 4:45
  • Upload Your Code To Github

    • Create An SSH Key - 2:40
    • Upload Your SSH Key To Github.com - 1:44
    • Push Your Code To Github.com - 6:33

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14.0 hours
Lessons
91

Create a ChatGPT A.I. Bot with Django & Python

Learn to Connect Your Django Python Apps to OpenAI The Fast & Easy Way!

By John Elder | in Online Courses

In this course you will learn how to make web apps for Django and Python, and how to connect those apps to the OpenAI (makers of ChatGPT) Text Completion Artificial Intelligence API and have it fix code that you submit as well as write code that you ask it to write. You will use Python, Django, and the Bootstrap Framework to build a cool Coding website that connects to OpenAI. You will also use a database to save all of the code answers that you've received from the OpenAI API, a query that database, and output the answers on the web page. Finally, you will learn how to connect to OpenAI with an API Key, query the engine, parse the responses in the correct way and output the answers to the homepage of your Django app.

  • Access 91 lectures & 14 hours of content 24/7
  • Submit your Code & have the A.I. suggest fixes
  • Ask The A.I. to write code for you
  • Choose from over a dozen programming languages
  • Save your code responses to the Database
  • View past code responses from the Database
John Elder | Founder of Codemy
4.4/5 Instructor Rating: ★ ★ ★ ★

John Elder is a pioneer in Web Development who created one of the first Internet advertising networks back in 1997. He sold it to a publicly traded company at the height of the dot com boom and then went on to create the best-selling Submission-Spider search engine submission software that's been used by over 3 million individuals and small businesses in over 45 countries. Today he teaches Web Development courses at Codemy the online code school he founded.

Important Details

  • Length of time users can access this course: lifetime
  • Access options: desktop & mobile
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: beginner
  • Updates included
  • Have questions on how digital purchases work? Learn more here

Requirements

  • A basic understanding of Python and Django is helpful

Course Outline

  • Introduction and Setup
    • Introduction - 2:30
    • Install Python - 2:51
    • Sublime Text And Gitbash Terminal - 3:21
    • OpenAI API Key - 3:01
    • Virtual Environment
    • Pip Install Libraries
    • Create Our App!
  • Create a Django App
    • Starting to Proofread a Blog Post with ChatGPT - 3:32
    • Deep Proofreading for an Emotional Writing vs. Sterile Writing - 3:40
    • Doing Sales Copywriting with Artificial Intelligence - AI
    • Better editing and making any business writing more sophisticated - 4:34
    • Create the ChatGPT Response Area - 2:11
    • Create a WebForm with Bootstrap - 4:38
    • Add Form Processing - 6:18
  • OpenAI API
    • Setup an OpenAI Account - 2:12
    • Create the OpenAI Request - 5:32
    • Parse OpenAI Response - 5:19
    • Handle Multiline Responses - 8:03
  • Using The Database
    • Create the Database Model - 5:06
    • Save Data To The Database - 2:27
    • Create a Database Webpage - 2:40
    • Query The Database on the Web Page - 2:33
    • Delete Items form the Database - 8:24
    • Set up Error Handling - 2:45
  • Create Pagination
    • Set Up Pagination - 3:40
    • Understanding Pagination Variables - 3:23
    • Next - Last Pagination - 3:53
    • Pagination Webpage Numbers - 7:16START
    • Finishing Up - 0:43

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Lifetime
Content
7 hours
Lessons
15

Python PDF Handling from Beginner to Winner

Create Professional-Looking PDF Documents in Python

By Hugo Ferro | in Online Courses

This course is a very practical one that will teach you how to use the different types of PDF files. You will learn how to create them step by step in detail, as well as how to protect them with passwords and prevent people from printing your files. You will learn how to rotate images, insert radio buttons, checkboxes, and drop-down lists amongst others.

5.0/5 average rating: ★ ★ ★ ★ ★

  • Access 15 lectures & 7 hours of content 24/7
  • Discover how to get the total number of pages of a PDF document
  • Discover how to get its metadata, author, title, table of content
  • Extract text from a PDF file & write it into a txt file
  • Extract images from a PDF file & save it into a png file
  • Read hyperlinks from a PDF document
  • Take snapshots from pages & save them as png files
  • Learn how to change pages paper size from A4 portrait, A4 landscape & others
  • Learn how to rotate the pages from a PDF file
  • Practice splitting odd from even pages so it would be easier to print them
  • Learn how to join together pages from several PDF files into a new PDF document
  • Discover how to change the page's visible area, crop the pages
  • Discover how to add watermarks to PDF pages
Hugo Ferro | Software Engineer | Solutions Architect
4.6/5 Instructor Rating: ★ ★ ★ ★

Hugo Ferro is a Software Engineer/Hardware Engineer from Portugal and he teaches online via his YouTube Channel with more than 11,000 subscribers. His courses are focused on Python, C#, Java, JavaScript, Kotlin, Groovy, and more.

Important Details

  • Length of time users can access this course: lifetime
  • Access options: desktop & mobile
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: beginner
  • Have questions on how digital purchases work? Learn more here

Requirements

  • Basic Knowledge about Python
  • Python 3.8.x or later
  • Visual Studio Code (Recommended)
  • Visual Studio Code "Python from Microsoft" & "Pylance from Microsoft" extensions

Course Outline

  • Section 1: Basic PDF Operations with PyMuPDF
    • Introduction [Part 0 of 14] - 8:25
    • Visual Studio Code Extensions [Part 1 of 14] - 1:48
    • Install PyMuPDF [Part 2 of 14] - 2:43
    • Get Number of Pages [Part 3 of 14] - 7:26
    • Get Document Info [Part 4 of 14] - 14:54
    • Get Text from Pages [Part 5 of 14] - 28:13
    • Get Images from Pages [Part 6 of 14] - 22:28
    • Get URLs from Pages [Part 7 of 14] - 14:08
    • Make Images from Pages [Part 8 of 14] - 16:22
    • Scale Pages [Part 9 of 14] - 19:36
    • Rotate Pages [Part 10 of 14] - 10:12
    • Split Pages [Part 11 of 14] - 16:03
    • Merge Pages [Part 12 of 14] - 8:10
    • Crop Pages [Part 13 of 14] - 15:23
    • Add Watermark [Part 14 of 14] - 24:07

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1 hours
Lessons
23

Python TkInter from Beginner to Winner

Build Amazing Desktop Applications Using Python Tkinter with Useful Widgets — Buttons, Labels & More

By Hugo Ferro | in Online Courses

In this course, you will learn how to use Python's Tkinter library to create desktop applications. Tkinter is a thin client interface for creating graphical user interfaces for both text and GUI (graphical user interface) applications. You will learn about event-driven programming and interact with databases and web services in order to create amazing tools for your personal or professional use.

  • Access 23 lectures & 1 hour of content 24/7
  • Learn how to use a variety of widgets
  • Discover effective tips & tricks to take advantage of different tools
  • Learn how to generate Docx from TkInter App
  • Explore best practices for coding
  • Understand computer science concepts
Hugo Ferro | Software Engineer | Solutions Architect
4.6/5 Instructor Rating: ★ ★ ★ ★

Hugo Ferro is a Software Engineer/Hardware Engineer from Portugal and he teaches online via his YouTube Channel with more than 11,000 subscribers. His courses are focused on Python, C#, Java, JavaScript, Kotlin, Groovy, and more.

Important Details

  • Length of time users can access this course: lifetime
  • Access options: desktop & mobile
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: beginner
  • Have questions on how digital purchases work? Learn more here

Requirements

  • Any device with basic specifications
  • Basic understanding of Python or other programming languages
  • Understanding of Variables, Conditional Statements, Loop Statements & Object Oriented Programming
  • Windows 10 or later
  • Python 3.8.x or later
  • Visual Studio Code (Recommended)

Course Outline

  • My Calculator
    • Introduction [Part 0 of 10] - 3:44
    • Main Structure [Part 1 of 10] - 31:49
    • Build Display [Part 2 of 10] - 10:54
    • Build Clear and Equals Buttons [Part 3 of 10] - 9:06
    • Build Numbers and Operators Buttons [Part 4 of 10] - 27:23
    • Define Numbers and Operators Actions [Part 5 of 10] - 12:56
    • How to Evaluate an Expression?! [Part 6 of 10] - 3:56
    • Define classes Node and ExpressionTree [Part 7 of 10] - 6:25
    • Build Binary Tree [Part 8 of 10] - 40:24
    • Evaluate Expression [Part 9 of 10] - 13:26
    • Division by Zero [Part 10 of 10] - 6:26
    • Make an Exe File [Bonus 1] - 7:38
  • My Products Stock Manager
    • Build the Main Window [Part 1 of 39] - 13:32
    • Define Main Areas with Frames [Part 2 of 39] - 16:13
    • Create Add/Delete Buttons [Part 3 of 39] - 9:19
    • Create Search Inputs [Part 4 of 39] - 14:02
    • Create Search Buttons [Part 5 of 39] - 12:50
    • Define Global Vars Section [Part 6 of 39] - 6:32
    • Add Font Styles [Part 7 of 39] - 9:55
    • Using TTF Fonts [Part 8 of 39] - 5:13
    • Define Product List Area [Part 9 of 39] - 9:25
    • Build Page Navigation Area [Part 10 of 39] - 4:20
    • Build Product List Area (Rows) [Part 11 of 39] - 17:47
    • Build Product List Area (Columns) [Part 12 of 39] - 15:05
    • Define Product and DataManager Classes [Part 13 of 39] - 11:46
    • Load Product Lines [Part 14 of 39] - 9:14
    • Load Name/Description Column [Part 15 of 39] - 5:30
    • Load Stock Quantity Column [Part 16 of 39] - 9:34
    • Load Delete Check Button Column [Part 17 of 39] - 7:12
    • Load Image Column [Part 18 of 39] - 13:43
    • Load Pages Navigation [Part 19 of 39] - 12:09
    • Load Total Page Number [Part 20 of 39] - 7:40
    • Action Move Prev/Next Page [Part 21 of 39] - 10:06
    • Search Action Engine [Part 22 of 39] - 7:26
    • Filtering in Search Action [Part 23 of 39] - 5:50
    • Action Clear Search [Part 24 of 39] - 4:03
    • Action Mark for Delete [Part 25 of 39] - 8:23
    • Reset Products to Delete [Part 26 of 39] - 8:35
    • Action Delete Products [Part 27 of 39] - 12:20
    • Action Add/Edit Products [Part 28 of 39] - 9:23
    • Product Editor [Part 29 of 39] - 13:10
    • Define Product Editor Areas [Part 30 of 39] - 3:22
    • Stock Editor + Add/Update Button [Part 31 of 39] - 13:58
    • Name/Description Frames [Part 32 of 39] - 4:17
    • Name/Description Inputs [Part 33 of 39] - 11:27
    • Product Image Editor [Part 34 of 39] - 9:13
    • Select Image File [Part 35 of 39] - 7:00
    • Update Product Image [Part 36 of 39] - 5:09
    • Process of Saving the Product [Part 37 of 39] - 12:37
    • Functions to Update and Insert a Product [Part 38 of 39] - 4:34
    • Callback Method to Save the Product [Part 39 of 39] - 11:13
    • Generate Stand Alone File [Extra] - 13:33
  • My Products Stock Manager - Bonus 1 (Generate PDF)
    • Introduction [Part 0 of 8] - 1:29
    • Create "Export PDF" Button (Single Product) [Part 1 of 8] - 7:16
    • Define Function to Generate PDF (Single Product) [Part 2 of 8] - 10:16
    • Insert Product's Name into PDF [Part 3 of 8] - 9:37
    • Insert Product's Image into PDF [Part 4 of 8] - 18:25
    • Insert Product's Description into PDF [Part 5 of 8] - 5:26
    • Create "Export PDF" Button (All Products) [Part 6 of 8] - 5:20
    • Define Function to Generate PDF (All Products) [Part 7 of 8] - 6:12
    • Insert Multiple Product Pages into PDF [Part 8 of 8] - 10:12
    • Generate Stand Alone File [Extra] - 7:38
  • My Products Stock Manager - Bonus 2 (Extract Text from Image)
    • Introduction [Part 0 of 7] - 1:59
    • Add a Menu to our App [Part 1 of 7] - 14:54
    • Add actions to the Menu [Part 2 of 7] - 9:46
    • How lambda functions work? [Part 3 of 7] - 7:41
    • Extract text from images with easyOCR [Part 4 of 7] - 17:49
    • Why our app freezes? [Part 5 of 7] - 7:33
    • Using Threads (Solution 1) [Part 6 of 7] - 6:58
    • Using Threads (Solution 2) [Part 7 of 7] - 20:46
  • My Products Stock Manager - Bonus 3 (Generate Docx - Part I)
    • Introduction [Part 0 of 8] - 0:37
    • Generate a Docx File [Part 1 of 8] - 5:09
    • Add Title, Image and Description to Docx [Part 2 of 8] - 7:06
    • Center the Title [Part 3 of 8] - 11:48
    • Increase Font Size of Title [Part 4 of 8] - 6:53
    • Center the Image [Part 5 of 8] - 5:23
    • Format the Description Text [Part 6 of 8] - 5:49
    • Add Option to Generate Docx to the Menu [Part 7 of 8] - 5:59
    • Generate Docx from TkInter App [Part 8 of 8] - 6:01
  • My Products Stock Manager - Bonus 4 (Generate Docx - Part II)
    • Introduction [Part 0 of 11] - 1:56
    • Create Button Export Docx [Part 1 of 11] - 3:02
    • Create Export Docx Options Window [Part 2 of 11] - 7:03
    • Separate Options Window into Top and Bottom Frames [Part 3 of 11] - 4:01
    • Separate the Top Frame into Two more Frames [Part 4 of 11] - 4:20
    • Frame Options Title Size [Part 5 of 11] - 12:29
    • Frame Options Title Color [Part 6 of 11] - 8:02
    • Build Frame Button Content [Part 7 of 11] - 4:52
    • Refactor docxGeneration.py [Part 8 of 11] - 11:55
    • Refactor docxGeneration.py [Part 9 of 11] - 11:19
    • Refactor docxGeneration.py [Part 10 of 11] - 12:58
    • Using a CallBack to Get Products [Part 11 of 11] - 5:25

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1 hours
Lessons
29

Python ReportLab from Beginner to Winner

Generate Dynamically PDF Files Using Python & ReportLab

By Hugo Ferro | in Online Courses

This hands-on course is very practical and easy to learn. You will not only learn about ReportLab, but you will also learn how to create beautiful, professional PDFs with ReportLab in this hands-on course. You'll explore the different features of this powerful tool, including outlining and designing, content management, and exporting your work Also you will learn how to think, how to structure your code, how to make your code pretty and easy for everyone to understand your work because at the end of the day, these skills are the ones that make companies want you!

4.8/5 average rating: ★ ★ ★ ★

  • Access 29 lectures & 1 hour of content 24/7
  • Learn how to generate dynamically PDF files with Python
  • Study the practical use cases with a hands-on approach
  • Learn how to add javascript to your PDF documents
  • Practice loading images, creating paragraphs, inserting buttons, & more
Hugo Ferro | Software Engineer | Solutions Architect
4.6/5 Instructor Rating: ★ ★ ★ ★

Hugo Ferro is a Software Engineer/Hardware Engineer from Portugal and he teaches online via his YouTube Channel with more than 11,000 subscribers. His courses are focused on Python, C#, Java, JavaScript, Kotlin, Groovy, and more.

Important Details

  • Length of time users can access this course: lifetime
  • Access options: desktop & mobile
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: beginner
  • Have questions on how digital purchases work? Learn more here

Requirements

  • Knowledge about the basics of Python 3

Course Outline

  • Palms Hotel PDF
    • 01.Python Reportlab Palms Hotel PDF - Part 1 - Build the main structure - 37:34
    • 02.Python Reportlab Palms Hotel PDF - Part 2 - Make the footer - 15:21
    • 03.Python Reportlab Palms Hotel PDF - Part 3 - Make the header - 24:00
    • 04.Python Reportlab Palms Hotel PDF - Part 4 - Build body structure - 24:42
    • 05.Python Reportlab Palms Hotel PDF - Part 5 - Make about section - 18:31
    • 06.Python Reportlab Palms Hotel PDF - Part 6 - Make description section - 10:26
    • 07.Python Reportlab Palms Hotel PDF - Part 7 - Make contacts section - 29:43
    • 08.Python Reportlab Palms Hotel PDF - Part 8 - Make prices list section - 28:33
    • 09.Python Reportlab Palms Hotel PDF - Exercise 1 - Add shadow effect to text - * 10:57
    • 10.Python Reportlab Palms Hotel PDF - Exercise 2 - Add Arabic text - 8:43
    • 11.Python Reportlab Palms Hotel PDF - Exercise 3 - Register a Font Family - 15:17
    • 12.Python Reportlab Palms Hotel PDF - Exercise 4 - Add Five Stars! - 37:24
    • 13.Python Reportlab Palms Hotel PDF - Exercise 5 - FAQs - 38:45
    • 14.Python Reportlab Palms Hotel PDF - Exercise 6 - Debug ReportLab Code - 54:37
    • 15.Python Reportlab Palms Hotel PDF - Exercise 7 - Django App - 83:50

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5 hours
Lessons
25

Python MTA 98-381: Complete Preparation Course

Master Python Essentials & Pass the MTA 98-381 Exam

By Chris Mall | in Online Courses

Learn the basics of computer programming, variables, if-statements and decision-making, loops, functions, and files input-output, XML Processing, and Database Handling. After this course, you will be able to code your fancy app for your work or your personal portfolio. Learning Python will give you more opportunities for jobs and career advancement because Python is one of the most requested skills in 2021! This course requires no previous programming or Python experience. If you’ve never programmed a computer before or know another programming language and want to learn Python, this course will teach you everything you need.

4.4/5 average rating: ★ ★ ★ ★

  • Access 25 lectures & 5 hours of content 24/7
  • Be able to sit for & pass the MTA 98-381 Python Certificate exams
  • Develop impressive Python applications in a few minutes/hours
  • Add Python 3 to your resumé by understanding Object-Oriented Programming (OOP)
  • Create programs using your logic & data structures
  • Automate coding tasks by building custom Python functions
Dr. Chris Mall | Scratch | C# | GDPR | Java | Python | C++ | Flutter | CySA+
4.4/5 Instructor Rating: ★ ★ ★ ★

Dr. Chris Mall holds a Ph.D. in Computer Science, Software Development, and multiple information technology professional certifications, including CySA+, PRINCE2 Practitioner, and Information Technology Infrastructure Library ITIL v3.

He also holds a Master of Science degree in Information Technology with a specialization in Information Assurance, GDPR compliance, and the development of mobile applications in novel technologies like Google Flutter and Dart.

Important Details

  • Length of time users can access this course: lifetime
  • Access options: desktop & mobile
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: intermediate
  • Have questions on how digital purchases work? Learn more here

Requirements

  • Any device with basic specifications

Course Outline

  • Introduction to MTA 98-381 Exam and Python Programming Language
    • Visual Studio Code - 10:04
    • 3 Tips to Get More Value Out of this Course
    • Installing Visual Studio Code - 10:29
    • Introduction to Python - 3:09
  • Variables and Data Types
    • Variables - 15:56
    • Python Variables - 19:14
    • Data Types - 11:18
    • Python Data Types - 21:21
    • Python Data Type Conversion - 6:11
    • Variable Operators - 8:54
  • If-Statements and Conditional Logic
    • If-Statements and Conditional Logic - 15:13
    • If-Statements and Conditional Logic in Python - 4:20
  • Loops and Iterations
    • Loops and Iteration - 10:29
    • Loops and Iteration in Python - Part 1 - 6:39
    • Loops and Iteration in Python - Part 2 - 11:06
  • Arrays, Functions and Files
    • Arrays - 10:51
    • 2D Arrays - 15:10
    • Multidimensional Arrays & Examples - 13:56
    • Functions - 21:44
    • Functions in Python - 14:41
    • File Input/ Output - 25:47
    • Input/ Output and Files in Python - 11:27
  • Advanced Concepts in Python
    • Sending Emails to multiple receivers with Python - 10:41
    • XML parsing - 16:26
    • Multithreading in Python - 8:24

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1 hours
Lessons
14

Robotics and Artificial Intelligence with Tools & Templates

Build a Solid Foundation in Building AI Systems with a Focus on Robotics, Unity 3D, GIT & More

By Chris Mall | in Online Courses

Robotics is one of the emerging technologies that researchers and industry leaders around the world have identified. Controlling robots can be done manually, semi-autonomously, or fully autonomously. Having an autonomous robotic system necessitates the system making decisions, which are usually based on artificial intelligence algorithms.

This course attempts to introduce students to the fundamentals of artificial intelligence as they apply it to robotic systems. The course begins with an introduction to machine learning for robotics before moving on to present developmental-based algorithms, robot learning, motion, and sensing. The course then covers robot perception and collaborative robotic systems before concluding with a discussion of robot ethics.

  • Access 14 lectures & 1 hour of content 24/7
  • Understand the theory behind Artificial Intelligence
  • Learn how to identify AI startup opportunities
  • Build your first robot
  • Learn how to use the AI algorithm in creating 3D projects
  • Familiarize the various tools used in Artificial Intelligence
Dr. Chris Mall | Scratch | C# | GDPR | Java | Python | C++ | Flutter | CySA+
4.4/5 Instructor Rating: ★ ★ ★ ★

Dr. Chris Mall holds a Ph.D. in Computer Science, Software Development, and multiple information technology professional certifications, including CySA+, PRINCE2 Practitioner, and Information Technology Infrastructure Library ITIL v3.

He also holds a Master of Science degree in Information Technology with a specialization in Information Assurance, GDPR compliance, and the development of mobile applications in novel technologies like Google Flutter and Dart.

Important Details

  • Length of time users can access this course: lifetime
  • Access options: desktop & mobile
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: intermediate
  • Have questions on how digital purchases work? Learn more here

Requirements

  • Any device with basic specifications

Course Outline

  • Installing GIT, Unity3D and Docker to Build our Pick-and-Place Robot
    • Introducing and Installing GIT - 5:03
    • Docker and Unity3D Installation - 5:14
  • Building the Docker Project and Integrating into Unity3D
    • Building the Docker Project - 5:13
    • Integrating the Project into Unity3D - 3:55
  • Building our Unity3D Project and ROS Communication with Serialized Messages
    • Building our Unity3D Project - 8:22
    • Robotic Operating System (ROS) Communication with Serialized Messages - 1:04
  • Finalizing the Integration and the Pick-and-Place Robot
    • Finalizing the Integration Process from the Unity 3D Side - 4:56
    • Finalizing the Pick-and-Place Robot - 6:44
  • Introduction to Pose Estimation in Robots with a UR3 Robotic Arm
    • Introduction to Pose Estimation in Robots with a UR3 Robotic Arm. What you will learn. - 1:35
  • Setting Up Unity 3D, Installing Packages and Instantiating Objects
    • Setting Up Unity 3D and Installing Packages - 6:20
    • Instatiate Game Objects with Prefabs and How to Import a Robot from a URDF file in Unity3D - 12:00
  • Collecting, Training and Validating Data for our Robot
    • Preparing the Scene for data collection with the Perception Package - 9:56
    • Collecting, Training and Validating Data - 9:56
  • Finalizing the Pose Estimation UR3 Robot
    • Finalizing the Pose Estimation UR3 Robot - 14:47

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Lifetime
Content
9 hours
Lessons
51

Python for Data Analysis: Step-by-Step with Projects

Have a Solid Foundation on Data Analysis with Python Programming

By Packt Publishing | in Online Courses

Data analysis is a critical skill and is getting more popular. Nowadays, every organization has some data. Data could be extremely useful, but not without appropriate analysis. Data analysis enables us to transform data into insights for businesses to make informative decisions.

The course follows the approach of rather than dumping all the available Python libraries or functions to you, we picked only the most useful ones based on our industry experience to cover in the course. This allows you to focus and master the foundations. Besides Python programming, you will also get exposed to the basic statistical knowledge necessary for data analysis. Combined with detailed video lectures, you will be given a few projects to work on to reinforce your knowledge. By the end of the course, you will have a solid foundation in data analysis, and be able to use Python for the complete process.

4.6/5 average rating: ★ ★ ★ ★

  • Access 51 lectures & 9 hours of content 24/7
  • Learn how to use Python for data analysis
  • Experience analyzing real-world datasets in lectures & guided projects
  • Use Python data analysis libraries (Pandas, Scikit-learn, Seaborn)
  • Import, examine, and export data in Python
  • Learn how to manipulate, clean, & transform data
  • Calculate summary statistics
  • Create data visualizations in Python
  • Use JupyterLab/Jupyter Notebook
Packt Publishing | Tech Knowledge in Motion
4.0/5 Instructor Rating: ★ ★ ★ ★

Packt’s mission is to help the world put software to work in new ways, through the delivery of effective learning and information services to IT professionals. Working towards that vision, it has published over 4,000 books and videos so far, providing IT professionals with the actionable knowledge they need to get the job done–whether that’s specific learning on an emerging technology or optimizing key skills in more established tools.

Important Details

  • Length of time users can access this course: lifetime
  • Access options: desktop & mobile
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: intermediate
  • Have questions on how digital purchases work? Learn more here

Requirements

  • Any device with basic specifications

Course Outline

  • Introduction
    • Introduction - 4:02
    • Course Overview - 5:31
  • Python Crash Course
    • Setting Up Python environment - 7:19
    • Overview of Data Types, Numeric, Define Variables - 8:19
    • Strings, Common Functions, and Methods - 14:31
    • Lists, Tuples, Sets, Dictionaries, Booleans - 13:56
    • If Statements, Loops - 19:11
    • Define Functions, Use Packages - 15:11
    • Lambda Functions, Conditional Expressions - 15:04
  • Importing Data
    • Pandas Data Structures Overview - 14:32
    • Loading Data - 8:00
    • Previewing Data - 6:30
    • Pandas Data Types Overview - 17:43
    • Exporting Data - 6:32
  • Exploring Data
    • Combining Datasets - 13:49
    • Renaming Columns - 7:42
    • Selecting Columns - 4:19
    • Selecting Rows and Setting the Index (1) - 14:36
    • Selecting Rows and Setting the Index (2) - 13:38
    • Subsetting Both Rows and Columns - 10:24
    • Modifying Values - 14:11
    • Making a Copy - 5:54
    • Sorting Data - 10:14
  • Capstone Practice Project I
    • NBA Games Project Overview - 2:45
  • Cleaning Data
    • Data Cleaning Overview - 2:15
    • Removing Unnecessary Columns/Rows - 10:58
    • Missing Data Overview - 17:02
    • Tackling Missing Data (Dropping) - 8:14
    • Tackling Missing Data (Imputing with Constant) - 18:03
    • Tackling Missing Data (Imputing with Statistics) and Missing Indicators - 20:05
    • Tackling Missing Data (Imputing with Model) - 7:38
    • Handling Outliers (1) - 15:23
    • Handling Outliers (2) - 15:57
    • Cleaning Text - 15:39
  • Transforming Columns/Features
    • Extracting Date and Time - 20:19
    • Binning - 17:55
    • Mapping New Values - 11:42
    • Applying Functions - 16:11
  • Capstone Practice Project II
    • Czech Bank Project Overview - 3:31
  • Exploratory Data Analysis
    • EDA Overview - 2:44
    • Aggregating Statistics - 23:09
    • Group By - 21:48
    • Pivoting Tables - 17:17
    • Distribution of One Feature - 17:20
    • Seaborn Library Overview - 14:03
    • Relationship of Two Features (1) - 11:38
    • Relationship of Two Features (2) - 16:28
    • Relationship of Multiple Features - 11:40
    • Seaborn Library Recap - 3:15
  • Capstone Practice Project III
    • Olympic Games Project Overview - 2:57
  • Thank You
    • Course Wrap Up - 0:36

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1

Python Data Analysis (Third Edition)

Perform Data Collection, Data Processing, Wrangling, Visualization & Model Building Using Python

By Packt Publishing | in Online Courses

Get up and running using Python for data analysis by exploring the different phases and methodologies used in data analysis and learning how to use modern libraries from the Python ecosystem to create efficient data pipelines.

Starting with the essential statistical and data analysis fundamentals using Python, you will perform complex data analysis and modeling, data manipulation, data cleaning, and data visualization using easy-to-follow examples. You will then understand how to conduct time series analysis and signal processing using ARMA models. As you advance, you will get to grips with smart processing and data analytics using machine learning algorithms such as regression, classification, Principal Component Analysis (PCA), and clustering. In the concluding chapters, you will work on real-world examples to analyze textual and image data using natural language processing (NLP) and image analytics techniques, respectively. Finally, the book will demonstrate parallel computing using Dask.

By the end of this data analysis book, you’ll be equipped with the skills you need to prepare data for analysis and create meaningful data visualizations for forecasting values from data.

  • Access 1 lecture & 1 hour of content 24/7
  • Resolve common issues in broken or incomplete data sets
  • Possess a strong understanding of manipulating data sets
  • Create meaningful data visualizations
  • Analyze dozens of real-world data sets
Packt Publishing | Tech Knowledge in Motion
4.0/5 Instructor Rating: ★ ★ ★ ★

Packt’s mission is to help the world put software to work in new ways, through the delivery of effective learning and information services to IT professionals. Working towards that vision, it has published over 4,000 books and videos so far, providing IT professionals with the actionable knowledge they need to get the job done–whether that’s specific learning on an emerging technology or optimizing key skills in more established tools.

Important Details

  • Length of time users can access this course: lifetime
  • Access options: desktop & mobile
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: intermediate
  • Have questions on how digital purchases work? Learn more here

Requirements

  • Any device with basic specifications

Course Outline

  • Python Data Analysis - Third Edition
    • Python Data Analysis - Third Edition

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2 hours
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23

Create an Escape Room with Python

Apply Object-Oriented Programming Principles to Games while Building an Escape Room in Python

By ZENVA | in Online Courses

Games have a huge impact on the entire world – from being able to help spread awareness to providing individuals with unique career paths. Object-oriented programming (OOP) is one of the most in-demand paradigms when it comes to games, as it offers developers efficient and intuitive ways to organize their code.

In this course, you’ll use the Python language to create a text-based escape room while exploring core techniques for working with game “objects”. You’ll also master a variety of relevant game development fundamentals such as creating puzzles, implementing interactive elements, managing a project, and evaluating potential bugs and societal implications for such a game. Regardless of what kind of coding projects interest you, these game and OOP foundations will prepare you to pursue any number of interactive projects with responsible habits.

4.9/5 average rating: ★ ★ ★ ★

  • Access 23 lectures & 2 hours of content 24/7
  • Learn how to manage game projects
  • Implement different interaction types
  • Learn how to structure, store, & display item data
  • Evaluate inputs for specific answers
  • Test your games for errors
Zenva Academy
4.5/5 Instructor Rating: ★ ★ ★ ★

Trusted by over 1 million learners and developers, Zenva provides world-class training on in-demand programming skills covering game development, machine learning, virtual reality, and full-stack web development. Their e-learning platform is the leading place to upskill, learn and gain key tech skills for the innovation economy. Their curriculum is organized about Mini-Degrees™ which cover a wide range of technical subjects and include videos, project files, and mentor support.

Important Details

  • Length of time users can access this course: lifetime
  • Access options: desktop & mobile
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: beginner
  • Have questions on how digital purchases work? Learn more here

Requirements

  • Familiarity with object-oriented Python & a Python coding environment

Course Outline

  • Introduction
    • Introduction - 4:01
    • Source Files - Create an Escape Room with Python
    • Additional Resources
    • What is Object Oriented Programming - 3:17
  • Escape Room Project
    • Project Definition - 2:29
    • Project Design - 2:56
    • Text Input and Output - 8:45
    • Implementing GameObject Fields - 9:24
    • Implementing GameObject Methods - 10:06
    • Implementing Room - 8:23
    • Implementing Game Fields - 10:21
    • Implementing take_turn() - 9:23
    • Implementing select_object() - Part 1 - 9:38
    • Implementing select_object() - Part 2 - 9:48
    • Implementing guess_code() - 9:46
    • Testing - Part 1 - 6:45
    • Testing - Part 2 - 9:55
    • Project Evaluation - 3:03
  • Impacts
    • Social Impact - 7:05
    • Environmental Impact - 4:44
    • Economic Impact Part - 7:35
    • Data Considerations - 6:39
  • Conclusion
    • Conclusion - 3:38

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17 hours
Lessons
89

The Complete Python Hacking Course: Beginner to Advanced

Learn Ethical Hacking, Penetration Testing & More while Working on Python Coding Projects!

By Joseph Delgadillo | in Online Courses

This course is designed to teach you how to hack from the basics to advanced techniques. This course will cover the following topics in this course: port and vulnerability scanning, SSH, FTP attacks, and much more! It starts with basic network skills and then takes you through everything from port scanning, password cracking and detecting vulnerabilities, command, and control centers, website penetration testing, and much more.

4.4/5 average rating: ★ ★ ★ ★

  • Access 89 lectures & 17 hours of content 24/7
  • Learn how to code & configure IP address
  • Understand what is hacking & programming
  • Crack password hashes With Python
  • Discover vulnerabilities with Python
  • Write programs in Python
Joseph Delgadillo | Best-Selling Instructor
4.3/5 Instructor Rating: ★ ★ ★ ★

Joseph Delgadillo is the founder of JTDigital Courses, an education technology company. He has been active in the online learning industry since 2015 and has worked with several prominent companies. As of 2022, over 1 million students across the globe have enrolled in his courses covering network security, Python programming, web development, and more. He teaches skills ranging from computers and technology to entrepreneurship and digital marketing.

Important Details

  • Length of time users can access this course: lifetime
  • Access options: desktop & mobile
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: intermediate
  • Have questions on how digital purchases work? Learn more here

Requirements

  • A basic understanding of ethical hacking-related concepts

Course Outline

  • Introduction and Setup
    • Introduction to Python for ethical hacking - 5:16
    • VirtualBox installation - 11:39
    • Kali Linux installation - 17:05
    • Guest Additions installation - 15:06
    • Python in Kali terminal - 13:31
  • Port and Vulnerability Scanning
    • Building a simple portscanner - 15:30
    • Adding raw_input to our port scanner - 9:21
    • Scanning the first 1000 ports - 4:46
    • Coding an advanced port scanner part 1
    • Coding an advanced port scanner part 2 - 8:48
    • Finishing and testing our scanner - 8:55
    • Configuring IP address and installing Metasploitable - 8:13
    • Returning banner from open port - 14:45
    • Coding a vulnerability scanner part 1 - 11:55
    • Coding a vulnerability scanner part 2 - 7:19
  • SSH and FTP Attacks
    • Automating SSH login part 1 - 9:54
    • Automating SSH login part 2 - 9:20
    • Testing our SSH login program - 8:34
    • Coding SSH brute-forcer - 10:37
    • Executing commands on target after brute-forcing SSH - 10:09
    • Anonymous FTP login attack - 9:53
    • Username and password list attack on FTP - 17:32
  • Password Cracking
    • SHA256, SHA512, MD5 - 8:37
    • Cracking SHA1 hash with online dictionary - 16:40
    • Getting password from MD5 hash - 13:22
    • Cracking crypt passwords with Salt - 24:02
  • Sniffers, Flooders and Spoofers
    • Changing MAC address manually - 8:34
    • Coding MAC address changer - 16:56
    • Theory behind ARP spoofing - 4:42
    • Crafting malicious ARP packet - 19:26
    • Coding ARP spoofer - 13:31
    • Forwarding packets and restoring ARP tables - 8:04
    • Spoofing our IP address and sending message with TCP payload - 12:01
    • Running SynFlooder with changed source IP address - 11:20
    • Getting source and destination MAC address from received packets - 24:45
    • Sniffing FTP username and password part 1 - 8:09
    • Sniffing FTP username and password part 2 - 12:09
    • Getting passwords from HTTP websites - 14:01
  • Coding DNS Spoofer
    • Cloning any webpage - 10:36
    • Printing DNS queries - 9:57
    • Redirecting response to cloned page - 16:44
    • Setting IP table rules and running DNS spoofer - 10:35
  • Network Analysis
    • Analyzing ethernet header - 16:07
    • Analyzing IP header part 1 - 10:24
    • Analyzing IP header part 2 - 25:34
    • Analyzing TCP header - 15:13
    • Analyzing UDP header - 13:20
  • Multi-functioning Reverse Shell
    • Theory behind socket programming - 7:20
    • Wine and Pyinstaller installation - 7:41
    • Setting up listener - 8:17
    • Establishing connection between target and server - 6:31
    • Implementing send and receive functions - 11:28
    • Executing commands on target system - 11:43
    • Importing JSON library to parse data - 8:19
    • Converting Python backdoor to .exe - 8:14
    • Using OS library to change directory - 9:58
    • Downloading and uploading files to target PC - 19:07
    • Hiding our backdoor and creating persistence - 13:49
    • Trying to connect to server every 20 seconds - 7:52
    • Downloading files to target PC - 11:49
    • Capturing screenshot on target PC - 23:04
    • Administrator privilege check - 8:14
    • Starting other programs with our shell - 10:44
    • Running our shell as an image, audio, PDF - 20:05
  • Coding a Keylogger
    • Installing Pynput - 6:19
    • Printing space character - 8:48
    • Calling timer on our keylogger - 9:56
    • Adding keylogger to our backdoor - 12:58
  • Command and Control Center
    • What is a threaded server? - 5:05
    • Accepting connections with a thread - 13:11
    • Managing multiple sessions - 8:39
    • Testing threaded server with Windows 10 target - 9:04
    • Fixing Q command - 11:11
    • Coding exit function - 13:51
    • Attacking multiple targets and gathering botnet - 16:26
  • Website Penetration Testing
    • Stealing saved wireless passwords - 21:55
    • Saving passwords to a file - 3:02
    • Bruteforcing Gmail - 10:13
    • Bruteforcing any login page part 1 - 12:59
    • Bruteforcing any login page part 2 - 10:07
    • Finding hidden directories part 1 - 5:10
    • Finding hidden directories part 2 - 6:36
    • Discovering subdomains - 11:32
    • Changing HTTP headers - 13:56
    • Starting basic and digest authentication bruteforcer - 10:23
    • Controlling threads - 8:35
    • Coding run function - 10:06
    • Printing usage and testing our program - 12:33
    • Taking a look at ransomware - 8:20

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4 hours
Lessons
42

Artificial Intelligence (AI) in Python: An H2O Approach

Master Powerful Python Package for Machine Learning, Artificial Neural Networks (ANN) & Deep Learning

By Minerva Singh | in Online Courses

This course covers the main aspects of the H2O package for data science in Python. If you take this course, you can do away with taking other courses or buying books on Python-based data science as you will have the keys to a mighty Python-supported data science framework. In this age of big data, companies worldwide use Python to sift through the avalanche of information at their disposal. By becoming proficient in machine learning, neural networks, and deep learning via a powerful framework, H2O in Python, you can give your company a competitive edge and boost your career to the next level!

4.4/5 average rating: ★ ★ ★ ★

  • Access 42 lectures & 4 hours of content 24/7
  • Use the Python/Anaconda environment for practical data science
  • Learn the important concepts associated with supervised & unsupervised learning
  • Implement supervised & unsupervised learning on real-life data
  • Implement Artificial Neural Networks (ANN) & Deep
  • Neural Networks (DNN) on real-life data
Minerva Singh | Bestselling Instructor & Data Scientist
4.3/5 Instructor Rating: ★ ★ ★ ★

Minerva Singh is a Ph.D. graduate from Cambridge University where she specialized in Tropical Ecology. She is also a Data Scientist on the side. As a part of her research, she has to carry out extensive data analysis, including spatial data analysis using tools like R, QGIS, and Python. Minerva also holds an MPhil degree in Geography and Environment from Oxford University.

Important Details

  • Length of time users can access this course: lifetime
  • Access options: desktop & mobile
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: intermediate
  • Have questions on how digital purchases work? Learn more here

Requirements

  • Any device with basic specifications

Course Outline

  • Welcome To The World of Python AI
    • What is this course about? - 3:29
    • Data and code
    • What is AI? - 9:51
    • Introduction to the Python Data Science Environment - 10:57
    • Upgraded Python3 Installation - 5:44
    • The IPython Ecosystem - 19:13
  • Read in and Preprocess Data From External Data Sources
    • Introduction to Pandas - 12:06
    • Read CSV - 5:42
    • Read Excel - 5:31
    • Read HTML - 5:58
    • Introduction to Pandas For Basic EDA - 4:30
  • Introduction to H2O
    • What is H2O?
    • More H2O Installation - 2:11
    • Getting Used To the H2O Framework - 2:12
    • Read in Data as H2O Frame - 4:23
    • Convert To H2O Frame - 2:43
  • What is Machine Learning (ML)?
    • Theory Behind ML - 5:32
  • Supervised Learning With H2O
    • What Is Supervised Classification? - 10:10
    • Supervised Classification Accuracy - 4:19
    • Theory of GLM - 5:25
    • Set up GLMs - 11:35
    • Test GLM Performance - 9:48
    • Select Optimum GLM Parameters: Grid search - 10:03
    • Random Forest For Binary Classification - 17:50
    • Implement a Random Forest Model - 7:49
    • Gradient Boosting Machine (GBM) For Regression - 11:11
    • Search or GBM Parameters - 7:02
    • XGB Theory - 2:02
    • XGBoost for Binary Classification - 5:15
    • XGBoost For Multiclass Classification - 5:12
    • Search For the Best H2O Model:Select the Best Machine Learning Model - 5:20
  • Unsupervised Learning
    • What Is Unsupervised Classification? - 1:38
    • Principal Component Analysis (PCA) Theory - 2:37
    • PCA - 6:14
    • k-means theory - 1:57
    • k-means - 11:08
  • Neural Networks With H2O
    • Theoretical Introduction - 9:17
    • What are Activation Functions? - 5:50
    • Implement Deep Learning for Binary Classification - 8:01
    • Theory Behind Autoencoders - 1:46
    • Set up Autoencoder - 4:06
    • Implement the Autoencoder - 3:11

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12 hours
Lessons
81

Computer Vision & Deep Learning with OpenCV and Python: Build 15 Projects

Refresh Your Python Knowledge & Build Real-Time Computer Vision Applications

By Mammoth | in Online Courses

This course focuses on hands-on Computer Vision with OpenCV from scratch to real-time project development. Computer Vision is the hottest field in the era of Artificial Intelligence. It is making enormous advances in Self-driving cars, Robotics, Medical as well as in various image correction apps. And OpenCV-Python is an appropriate tool for fast prototyping of Computer Vision problems. This course is perfect for anyone who wants to upgrade in Computer Vision and Deep Learning and be able to develop real-time computer vision applications.

4.5/5 average rating: ★ ★ ★ ★

  • Access 81 lectures & 12 hours of content 24/7
  • Refresh your knowledge on Python
  • Analyze images with OpenCV
  • Restore images with computation photography
  • Detect objects in images
  • Understand machine learning & neural networks
  • Read text in an image with OCR & Tesseract
  • Build your first neural network with OpenCV
Mammoth Interactive
4.2/5 Instructor Rating: ★ ★ ★ ★

Mammoth Interactive produces XBOX 360, iPhone, iPad, Android, HTML 5, ad-games, and more. It's owned by top-rated instructor John Bura. Mammoth Interactive recently sold a game to Nickelodeon! John has been contracted by many different companies to provide game design, audio, programming, level design, and project management. To this day John has 40 commercial games that he has contributed to. Several of the games he has produced have risen to number 1 in Apple's app store. In his spare time, John likes to play ultimate Frisbee, cycle, and work out.

Important Details

  • Length of time users can access this course: lifetime
  • Access options: desktop & mobile
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: beginner
  • Have questions on how digital purchases work? Learn more here

Requirements

  • Any device with basic specifications

Course Outline

  • Course Overview - Rendered
    • 01 Course Overview - Opencv - 4:51PREVIEW
    • 02 What You'll Need - 2:38
    • Course Overview - Source File
  • Introduction to Python (Prerequisite)
    • 00. Intro To Course And Python - 9:57
    • 01. Variables - 19:19
    • 02. Type Conversion Examples - 10:06
    • 03. Operators - 28:54
    • 04. Collections - 8:25
    • 05. List Examples - 19:41
    • 06. Tuples Examples
    • 07. Dictionaries Examples - 14:26
    • 08. Ranges Examples - 8:32
    • 09. Conditionals - 6:43
    • 10. If Statement Examples - 21:32
    • 11. Loops - 29:42
    • 12. Functions - 17:01
    • 13. Parameters And Return Values Examples - 13:54
    • 14. Classes And Objects - 34:11
    • 15. Inheritance Examples - 17:29
    • 16. Static Members Examples - 11:05
    • 17. Summary And Outro - 4:08
    • Source Code
  • Analyze Images with OpenCV
    • 01 Detect Edges In An Image - 8:19
    • 02 Detect Contours In An Image - 11:23
    • 03 Detect Corners In An Image - 9:37
    • Analyze Images
  • Restore Images with Computational Photography
    • 01 Restore A Damaged Image - 18:57
    • Computational Photography
  • Detect objects in images
    • 01 Detect Objects In An Image With Masking - 15:39
    • 04 Find Object In Image With Template Matching - 12:27
    • 03 Extract Foreground In An Image - 18:30
    • 02 Detect Faces In Images - 11:31
  • Machine learning and neural networks introduction
    • 01 What Is Machine Learning - 5:26
    • 02 What Is Deep Learning - 7:42
    • 03 What Is A Neural Network - 8:47
    • 04 What Is Ml-Agents - 5:16
    • Source Files
  • Read text in an image with OCR and Tesseract
    • 01 Extract Text From An Image With Tesseract - 13:31
    • 02 Improve Accuracy With Thresholding - 8:10
    • 03 Change Perspective Of An Image With Foreign Text - 15:30
    • 04 Extract Foreign Language Text From An Image - 8:03
  • Build your first neural network with OpenCV
    • 01 Generate Data - 7:09
    • 02 Build An Artificial Neural Network - 9:16
    • 03 Visualize Model Results - 14:30
    • SourceFiles
  • Object detection with OpenCV Deep Learning
    • 01 Load Yolo Dnn Model - 3:18
    • 02 Build A Neural Network With Opencv - 7:44
    • 03 Print Out Detected Objects - 6:44
    • 04 Outline Objects In The Original Image - 21:57
    • Source Files
  • Outline objects in a video
    • 01 Outline Objects In A Video - 10:55
    • 03 Save New Frames As A Video - 5:04
    • Outline objects in a video
    • 02 Draw Contours On Video - 16:30
  • Detect faces in video
    • 01 Load A Video From Drive - 7:39
    • 02 Detect Faces In Video - 10:32
    • 03 Detect Eyes In Video - 6:40
    • 04 Save New Frames As A Video - 7:40
    • Detect faces in video
  • Track a color in videos
    • 01 Track Color In A Video - 20:06
    • 02 Save New Frames As A Video - 7:14
    • Track a color in videos
  • Detect lanes for autonomous vehicle computer vision
    • 01 Load A Driving Dash Cam Video - 4:05
    • 02 Process Each Video Frame - 14:54
    • 03 Outline Lanes Detected - 12:21
    • 04 Save New Frames As A Video - 13:52
    • Source Files
  • Build a motion alert video monitoring system
    • 01 Load A Video From Drive - 5:28
    • 02 Detect Objects In A Video With Contours - 10:05
    • 03 Detect When Motion Begins And Ends - 15:17
    • 04 Record Each Time Motion Begins - 16:36
    • Source Files
  • Detect emotion in a video
    • Detect Emotion In A Video - 12:11
    • Source Files
  • Swap faces with machine learning
    • 01 Load Images From The Web Into Colab - 3:00
    • 02 Get Facial Landmarks From Image - 11:55
    • 03 Build A Matrix From Landmark Points - 10:08
    • 04 Draw A Mask Over Facial Landmarks - 7:07
    • 05 Build A Warped Mask - 4:09
    • 06 Combine Face Masks - 8:15
    • Source Files

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9 hours
Lessons
85

Python 3: From ZERO to GUI Programming

Expand Your Python Horizon to Other Features Such as Pygame, PyTorch & Qiskit

By LearningWhilePracticing | in Online Courses

Python 3 is one of the strongest programming languages and has a high demand on the market. Whether it is for scientific programming, gaming, or web development, Python has the tools and libraries that will make your project come to life. This course will help you set afoot in the world of Python without any prior knowledge. Each chapter is filled with practical examples, allowing you to code right away from the very beginning. Once this course is finished, you will be able to expand your Python horizon to other features such as Pygame, which is for gaming development under Python, PyTorch for machine learning, and even Qiskit for Quantum Computing.

4.5/5 average rating: ★ ★ ★ ★

  • Access 85 lecture & 9 hours of content 24/7
  • Get an overview of Python 3
  • Learn about elementary programming
  • Work with mathematical functions, strings, & objects
  • Explore conditional statements, loops, & functions
  • Learn GUI programming with Tkinter
  • Learn about Inheritance & Polymorphism, FIles & Exception Handling, and more
LearningWhilePracticing | Joe Rahl
4.6/5 Instructor Rating: ★ ★ ★ ★

LearningWhilePracticing has one of the most practical approaches when it comes to learning. Our goal is to let you be operational as quickly as possible while at the same grasping all the concepts required. Being able to work on your projects through software while learning it at the same time, is a source of motivation that will make you go further.

Important Details

  • Length of time users can access this course: lifetime
  • Access options: desktop & mobile
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: beginner
  • Have questions on how digital purchases work? Learn more here

Requirements

  • Any device with basic specifications

Course Outline

  • Section 1 - Introduction to Python 3
    • Introduction - 6:48
    • C1Ex1 - Olympic Circles - 10:10
  • Section 2 - Elementary Programming
    • Elementary Programming - 11:05
    • C2Ex1 - Area with input - 5:55
    • C2Ex2 - Show current time - 9:18
    • C2Ex3 - Compute distance with graphical representation - 6:12
  • Section 3 - Mathematical Functions, Strings, Objects
    • Mathematical Functions, Strings, Objects - 12:40
    • C3Ex1 - Math functions - 4:02
    • C3Ex2 - Compute change - 4:01
    • C3Ex3 - Simple shapes - 2:37
    • C3Ex4 - Color shapes - 3:24
  • Section 4 - Conditional Statements
    • Conditional Statements - 13:02
    • C4Ex1 - Guess the birthday date - 6:16
    • C4Ex2 - Subtraction quiz - 2:51
    • C4Ex3 - Chinese Zodiac - 2:12
    • C4Ex4 - Lottery - 4:04
    • C4Ex5 - Point in a circle - 3:59
  • Section 5 - Loops
    • Loops - 12:04
    • C5Ex1 - Guess the number - 4:28
    • C5Ex2 - Subtraction quiz loop - 7:14
    • C5Ex3 - Multiplication table - 4:59
    • C5Ex4 - Prime number - 5:00
    • C5Ex5 - Random walk - 5:46
  • Section 6 - Functions
    • Functions - 9:59
    • C6Ex1 - Test Max - 5:26
    • C6Ex2Ex3 - GCD function - 6:05
    • C6Ex4 - Random character - 10:38
    • C6Ex5 - Print Calendar - 9:27
    • C6Ex6Ex7 - Useful Turtle functions - 4:00
  • Section 7 - Objects and Classes
    • Objects and Classes - 14:34
    • C7Ex1Ex2 - TV - 4:59
    • C7Ex3 - Immutable vs Mutable Object - 3:07
  • Section 8 - GUI Programming with Tkinter
    • GUI Programming with Tkinter - 3:22
    • C8Ex1 - Simple GUI - 3:00
    • C8Ex2 - Process Button Event - 2:41
    • C8Ex3 - Widget Demo - 6:10
    • C8Ex4 - Change Label Demo - 5:24
    • C8Ex5 - Canvas Demo - 7:45
    • C8Ex6 - Place Manager Demo - 2:02
    • C8Ex7 - Loan Calculator - 5:52
    • C8Ex8 - Image Demo - 3:26
    • C8Ex9 - Menu Demo - 7:15
    • C8Ex10 - Popup Menus - 3:29
    • C8Ex11 - Mouse Key Event Demo - 5:41
    • C8Ex12 - Enlarge Shrink Circle - 5:00
    • C8Ex13 - Animation Demo - 5:16
    • C8Ex14 - Control Animation - 4:59
    • C8Ex15 - Scroll Text - 2:21
    • C8Ex16 - Dialog Demo - 2:45
  • Section 9 - Lists
    • Lists - 30:21
    • C9Ex1 - Data Analysis - 2:20
    • C9Ex2 - Lotto Numbers - 4:31
    • C9Ex3 - Deck Of Cards GUI - 2:49
    • C9Ex4 - Bounce Balls - 5:59
  • Section 10 - Inheritance and Polymorphism
    • Inheritance and Polymorphism - 18:51
    • C10Ex1E2Ex3Ex4 - Geometric Objects - 7:33
    • C10Ex5 - Polymorphism Demo - 4:01
    • C10Ex6Ex7 - Clock - 5:14
  • Section 11 - Files and Exception Handling
    • Files - 24:42
    • C11Ex1 - Write Demo - 2:19
    • C11Ex2 - Read Demo - 2:20
    • C11Ex3 - Copy File - 1:37
    • C11Ex4 - Append Demo - 1:57
    • C11Ex5 - Write Read Numbers - 2:25
    • C11Ex6 - File Editor - 2:41
    • C11Ex7 - Test Exception - 3:32
    • C11Ex8Ex9 - Circle With Exception - 2:42
    • C11Ex10 - Processing Exception Object - 1:46
  • Section 12 - Tuples, Sets, and Dictionaries
    • Tuples, Sets, and Dictionaries - 33:27
    • C12Ex1 - Tuple Demo - 5:17
    • C12Ex2 - Set Demo - 5:09
    • C12Ex3 - Set List Performance Test - 4:09
    • C12Ex4 - Count Keywords - 4:59
    • C12Ex5 - Count Occurrence Of Words - 3:09
  • Section 13 - Recursion
    • Recursion - 13:34
    • C13Ex1 - Compute Factorial - 4:12
    • C13Ex2 - Compute Fibonacci - 4:03
    • C13Ex3 - Recursive Palindrome Using Substring - 2:49
    • C13Ex4 - Recursive Selection Sort - 4:36
    • C13Ex5 - Recursive Binary Search - 7:11
    • C13Ex6 - Directory Size - 4:54
    • C13Ex7 - Sierpinski Triangle - 6:27
    • C13Ex8 - Eight Queens - 5:53
  • Bonus - Additional Modules
    • 14-osdatetimerandom - 28:03
  • Resource Files
    • GitHub repository to access files

View Full Curriculum



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