The Python Mega Course: Build 10 Real World Applications

The Python Mega Course: Build 10 Real World Applications
The Python Mega Course: Build 10 Real World Applications

English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 23.5 Hours | 5.25 GB
eLearning | Skill level: All Levels

Start Python from the basics and learn how to create 10 amazing and professional Python programs used in the real world!

The Python Mega Course is the most practical course you will find on the web nowadays. Over 130 thousand students so far have used the course to learn Python programming and to build real-world applications in Python 3. You will learn how to build Python apps in this course even if you know nothing about programming. You will start from scratch and progressively build up your skills by creating some awesome Python programs ranging from webcam object detection apps to data collector web apps that query data from SQL databases to data visualization dashboards on the browser. The course has it all to make you an all-around Python programmer that not only knows Python but also the technologies you need to know to create professional applications.

The course follows a modern-teaching approach where students learn by doing. You will start Python from scratch by creating simple programs first. Once you learn the basics, you will then start with the fun part which is building not less but 10 real-world applications. You will code the apps guided step-by-step by easy video explanations and continuous support by the course instructor. The applications you will build in the course consist of database apps, web apps, desktop apps, web scraping scripts, webcam object detectors, web maps, data visualization dashboards, and more. These programs are not only great examples to master Python, but you can also use them for your portfolio.

If you don’t know anything about Python, do not worry! In the first 12 sections, you will learn Python basics such as functions, loops, and conditionals and learn how to apply the basics by doing some examples. If you already know the basics, then the first 12 sections can serve as a refresher. The other 20 sections focus entirely on building real-world applications. The applications you will build cover a wide range of interesting topics:

  • Web applications
  • Desktop applications
  • Database applications
  • Web scraping
  • Web mapping
  • Data analysis
  • Data visualization
  • Computer vision
  • Object-Oriented Programming

Specifically, the 10 Python applications you will build are:

  • A program that returns English-word definitions
  • A program that blocks access to distracting websites
  • A web map visualizing volcanoes and population data
  • A portfolio website
  • A desktop-graphical program with a database backend
  • A webcam motion detector
  • A web scraper of real estate data
  • An interactive web graph
  • A database web application
  • A web service that converts addresses to geographic coordinates

To consider yourself a professional programmer you need to know how to make professional programs and there’s no other course that teaches you that, so join thousands of other students who have successfully applied their Python skills in the real world. Sign up and start learning the amazing Python programming language today!

What you’ll learn

  • Go from a total beginner to a confident Python programmer
  • Create 10 real-world Python programs (no toy programs)
  • Solidify your skills with bonus practice activities throughout the course
  • Create an app that translates English words
  • Create a web-mapping app on the browser
  • Create a portfolio website and publish it on a real server
  • Create a desktop app for storing data for books
  • Create a webcam video app that detects moving objects
  • Create a web scraper
  • Create a data visualization app
  • Create a database app
  • Create a geocoding web app
  • Create a website blocker
  • Send automated emails
  • Analyze and visualize data
  • Use Python to schedule programs based on computer events.
  • Learn OOP (Object-Oriented Programming)
  • Learn GUIs (Graphical-User Interfaces)
+ Table of Contents

Data Analysis with Pandas
102 What is Pandas?
103 Installing Pandas
104 Getting Started with Pandas
105 Getting Started with Jupyter Notebooks
106 Loading CSV Files
107 Exercise: Loading JSON Files
108 Solution
109 Note on Loading Excel Files
110 Loading Excel Files
111 Loading TXT Files
112 Set Header Row
113 Set Column Names
114 Set Index Column
115 Indexing and Slicing
116 Deleting Columns and Rows
117 Updating and Adding new Columns and Rows
118 Note on Nominatim
119 Example: Geocoding Addresses with Pandas and Geopy

120 What is Numpy?
121 Installing OpenCV
122 Convert Images to Numpy Arrays
123 Indexing, Slicing, and Iterating Numpy Arrays
124 Stacking and Splitting Numpy Arrays

Application 2: Create Webmaps with Python and Folium
125 Web Map – How The Output Will Look Like
126 The Basemap
127 Note
128 Adding Points
129 Adding Multiple Points
130 Adding Points from Files
131 Popup Windows on Map
132 HTML on Popups
133 Color Points
134 Add and Style Points (Practice)
135 Tip: Add and Style Points
136 Solution
137 GeoJson Data
138 Adding a GeoJson Polygon Layer
139 Choropleth Map
140 Layer Control Panel

Fixing Programming Errors
141 Syntax Errors
142 Runtime Errors
143 How to Fix Difficult Errors
144 Good Programming Questions
145 Error Handling

Application 3: Build a Website Blocker
146 Website Blocker – How The Output Will Look Like
147 Application Architecture
148 Setting up the Script
149 Setting up the Infinite Loop
150 Implementing the First Part
151 Implementing the Second Part
152 The any() function
153 Scheduling the Python Program on Windows
154 Scheduling the Python Program on Mac and Linux
155 Scheduling a Python Program on a Server

Application 4: Build a Personal Website with Python and Flask
156 Personal Website – How The Output Will Look Like
157 Your First Website
158 HTML Templates
159 Navigation Menu
160 Note on Browser Caching
161 CSS Styling
162 Creating a Python Virtual Environment
163 How to Install Git
164 Deploying the Website to a Live Server
165 Maintaining the Live Website
166 Troubleshooting
167 Congratulations!

Graphical User Interfaces with Tkinter
168 Introduction to Tkinter
169 Setting up a GUI with Widgets
170 Connecting GUI Widgets with Callback Functions
171 Create a Multi-widget GUI (Practice)
172 Solution

Interacting with Databases
173 Introduction to “Python with Databases”
174 Connecting and Inserting Data to SQLite via Python
175 Selecting, Inserting, Deleting, and Updating SQLite Records
176 Introduction to PostgreSQL Psycopg2
177 Selecting, Inserting, Deleting, and Updating PostgreSQL Records
178 Querying data from a MySQL database

Application 5: Build a Desktop Database Application
179 Desktop Database App – How The Output Will Look Like
180 User Interface Design
181 Frontend Interface
182 Backend
183 Connecting the Frontend to the Backend, Part 1
184 Connecting the Frontend to the Backend, Part 2
185 Fixing the Bug (Practice)
186 Solution
187 Creating a Standalone Executable Version of the Program

Object Oriented Programming
188 Object Oriented Programming Explained
189 Turning this Application into OOP Style, Part 1
190 Turning this Application into OOP Style, Part 2
191 Creating a Bank Account Object
192 Inheritance
193 OOP Glossary
194 GUI in OOP Design (Practice)
195 Solution

Python for Image and Video Processing with OpenCV
196 Introduction
197 Installing the Library
198 Loading, Displaying, Resizing, and Writing Images
199 Batch Image Resizing (Practice)
200 Solution
201 Solution with Explanations
202 Face Detection
203 Capturing Video

Application 6: Build a Webcam Motion Detector
204 Webcam Motion Detector – How The Output Will Look Like
205 Detecting Webcam Objects
206 Capturing Motion Time

Interactive Data Visualization with Bokeh
207 Introduction to Bokeh
208 Installing Bokeh
209 Your First Bokeh Plot
210 Plotting Triangles and Circle Glyphs (Practice)
211 Solution
212 Using Bokeh with Pandas
213 Plotting Education Data (Practice)
214 Solution
215 Note on Loading Excel Files
216 Plot Properties
217 Plotting Weather Data (Practice)
218 Solution
219 Visual Attributes
220 Time-series Plots
221 More Visualization Examples with Bokeh
222 Plotting Time Intervals of the Motion Detector
223 Hover Tool Implementation

Webscraping with Python Beautiful Soup
224 Section Introduction
225 The Concept Behind Webscraping
226 Request Headers
227 Webscraping Example

Application 7: Scrape Real Estate Property Data from the Web
228 Scraped Website Data – How The Output Will Look Like
229 Request Headers
230 Loading the Webpage in Python
231 Extracting “div” Tags
232 Extracting Addresses and Property Details
233 Extracting Elements without Unique Identifiers
234 Saving the Extracted Data in CSV Files
235 Crawling Through Webpages
236 List Methods

Application 8: Build a Web-based Financial Graph
237 Web-based Financial Graph – How The Output Will Look Like
238 Downloading Datasets with Python
239 Stock Market Data
240 Stock Market Data Candlestick Charts
241 Candlestick Charts with Bokeh Quadrants
242 Candlestick Charts with Bokeh Rectangles
243 Candlestick Segments
244 Stylizing the Chart
245 The Concept Behind Embedding Bokeh Charts in a Flask Webpage
246 Note
247 Embedding the Bokeh Chart in a Webpage
248 Deploying the Chart Website to a Live Server

Application 9: Build a Data Collector Web App with PostGreSQL and Flask
249 Data Collector Web App – How The Output Will Look Like
250 PostGreSQL Database Web App with Flask: Steps
251 Frontend: HTML Part
252 Frontend: CSS Part
253 Backend: Getting User Input
254 Backend: The PostGreSQL Database Model
255 Backend: Storing User Data to the Database
256 Backend: Emailing Database Values Back to the User
257 Backend: Sending Statistics to Users
258 Deploying the Web Application to a Live Server
259 Bonus Lecture: Implementing Download and Upload in your Web App

Application 10: Project Exercise on Building a Geocoder Web Service
260 Student Project – How The Output Should Look Like
261 Solution, Part 1
262 Solution, Part 2
263 End of the Course

Offers for my Other Python Courses
264 Bonus Lecture