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This site is protected by reCAPTCHA and the Google, Learn A New Language This Year With Highly Rated, Babbel - 55% Off, Access 242 lectures & 23 hours of content 24/7, Build a name generator, a website URL timed blocker, a web map generator, a portfolio website w/ Flask, a GUI-based desktop application, & more apps, Use Python to build applications w/ Flask, Tkinter, Numpy, Folium & more, Explore scraping data, computer vision, sending automated emails & more using Python, Schedule Python programs based on computer events, Length of time users can access this course: lifetime, Redemption deadline: redeem your code within 30 days of purchase, Simple Types: Integers, Strings, and Floats - 3:21, How are datatypes used in the real world - 1:07, Summary: Integers, Floats, Lists, Dictionaries, and Tuples, Exercise: Create Integers, Strings, and Floats, Solution: Create Integers, Strings, and Floats, Accessing items and slices with negative indexes - 2:02, Accessing characters and slices in strings - 1:30, Summary: Positive/Negative Indexes, Slicing, Bonus Code: Using "and" and "or" in a Conditional, Conditional explained line by line - 3:09, String formatting with multiple variables - 1:35, Bonus code: Dictionary loop and string formatting, While loop example with user input - 3:12, While loop with break and continue - 3:22, Putting the Pieces Together: Building a Program, List comprehension with If conditional - 1:22, List comprehension with if-else conditional - 1:37, Keyword and non-keyword arguments, default and non-default parameters - 3:00, Functions with an arbitrary number of non-keyword arguments - 3:32, Functions with an arbitrary number of keyword arguments - 1:34, The concept of processing files with Python - 1:12, Appending text to an existing File - 3:30, Application 1: Build an Interactive Dictionary, Returning the definition of a word - 3:25, Similarity ratio between two words - 4:39, Creating Numpy Arrays from Images and Vice-Versa - 12:30, Getting Started with Jupyter Notebooks - 9:18, Updating and Adding New Columns and Rows - 7:31, Example: Geocoding Addresses with Pandas and Geopy - 15:11, Application 2: Create Webmaps with Python and Folium, Demonstration of the Web Mapping Application - 1:24, Creating an Open Street Map with Python - 6:34, Adding Markers to the Map from CSV Data - 9:12, Calculating the Map Center from the Input Data - 7:56, Adjusting the Code for the Latest Version of Folium - 8:12, Adding a Choropleth Map from GeoJson - 20:59, The structure of a good programming question - 5:59, Demonstration of the Website Blocker Application - 3:48, Scheduling the Python Program on Windows - 12:39, Scheduling the Python Program on Mac and Linux - 6:15, Application 4: Build a Website with Python and Flask, Creating a Python Virtual Environment - 6:22, Deploying the Website to a Live Server - 21:52, Connecting GUI Widgets with Callback Functions - 9:33, Introduction to Working with Databases - 3:04, Connecting and Inserting Data to SQLite via Python - 13:11, Selecting, Inserting, Deleting, and Updating SQLite Records - 6:58, Introduction to PostgreSQL Psycopg2 - 8:46, Selecting, Inserting, Deleting, and Updating PostgreSQL Records - 12:53, Application 5: Build a Desktop Database Application, Demonstration of the Database Application - 2:25, Connecting the Front-end to the Back-end, Part 1 - 17:31, Connecting the Front-end to the Back-end, Part 2 - 21:59, Creating a Standalone Executable Version of the Program - 5:00, Object Oriented Programming Explained - 4:59, Turning this Application into OOP Style, Part 1 - 13:01, Turning this Application into OOP Style, Part 2 - 14:06, Python for Image and Video Processing with OpenCV, Loading, Displaying, Resizing, and Writing Images with Python - 14:00, Application 6: Build a Webcam Motion Detector, Demonstration of the Motion Detector Application - 1:59, Detecting Objects from the Webcam - 30:20, Interactive Data Visualization with Python, Plotting Triangles and Circle Glyphs (Practice), More Visualization Examples with Bokeh - 4:21, Plotting Time Intervals of the Motion Detector - 14:05, Scraping a Webpage with Requests and BeautifulSoup - 16:22, Application 7: Scrape Real Estate Property Data, Demonstration of the Webscraping Application - 2:28, Understanding the Problem and Loading the Webpage in Python - 7:15, Extracting Divisions of All Properties - 11:34, Extracting Addresses and Property Details - 14:39, Extracting Elements with no Unique Identifiers - 12:07, Saving the Extracted Data in CSV Files - 8:27, Application 8: Build a Web-based Financial Graph, Demonstration of the Financial Analysis Application - 1:59, Downloading Various Datasets with Python - 11:31, Understanding Stock Market Data Candlestick Charts - 5:39, Building Chart Candlesticks with Bokeh Quadrants - 10:13, Building Chart Candlesticks with Bokeh Rectangles - 22:28, The Concept Behind Embedding a Bokeh Chart in a Webpage - 11:04, Embedding the Bokeh Chart in a Webpage - 15:33, Deploying the Chart Website to a Live Server - 8:22, Application 9: Build a Data Collector Web App, Demonstration of the Web Application - 2:59, Steps for Building a PostgreSQL Database-enabled Web Application - 6:08, Building the Front-end: HTML Part - 14:52, Building the Back-end: Getting User Input - 17:31, Building the Back End: Creating the PostGreSQL Database Model - 18:17, Building the Back End: Storing User Data to the Database - 19:14, Building the Back End: Emailing Database Values Back to the User - 11:14, Building the Back End: Sending Statistics to Users - 16:00, Deploying the Web Application to a Live Server - 29:31, Bonus Lecture: User Downloads and Uploads - 20:51, Application 10: Student Project on Building a Geocoder Web Service, Demonstration of the Geocoding Web Service Application and Project Requirements - 7:31, Access 141 lectures & 3 hours of content 24/7, Understand how Python works & what it's good for, Perform math operations & work w/ Python sequences, Access 40 lectures & 10 hours of content 24/7, Write, test & share quick Python programs using Jupyter Notebook, Use NumPy to work w/ arrays & matrices of numbers, Learn some simple data visualization techniques w/ matplotlib, Access 33 lectures & 2 hours of content 24/7, Use Pandas DataFrames to work w/ tabular data, Use conditional filtering to select relevant information from datasets, Create graphical plots such as bar, line, area, scatter, & more, Access 35 lectures & 5 hours of content 24/7, Implement different clustering algorithms in python, Handle issues of varying cluster sizes, densities, shapes & noise, Access 35 lectures & 3 hours of content 24/7, Get started w/ Jupyter notebooks for implementing data science techniques in Python, Create artificial neural networks & deep learning structures w/ Keras, Prior exposure to Python-based data science will be beneficial, Prior exposure to basic statistical concepts & implementation will be useful, Prior exposure to common machine learning terms such as cross-validation, Access 61 lectures & 5 hours of content 24/7, Carry out basic image pre-processing & computer vision tasks w/ Python, Implement common machine learning algorithm on image classification, Read in image data into the Jupiter/iPython environment, Access 52 lectures & 6 hours of content 24/7, Learn implement deep learning models w/ PyTorch, Implement PyTorch based deep learning algorithms on imagery data, Configure the Anaconda Environment for getting started w/ PyTorch, Implement common machine learning algorithms for Image Classification, Access 40 lectures & 6 hours of content 24/7, Learn to create, evaluate & use data models to make predictions, Dive into setting up & starting new projects, Practice w/ pop quizzes embedded in lectures for you to test yourself, Access 206 lectures & 2 hours of content 24/7, Access 77 lectures & 6 hours of content 24/7, Build advanced data visualization web apps using the Python Bokeh library, Create widgets that let users interact w/ your plots, Integrate & visualize data from Pandas DataFrames, Create interactive modern web plots that represent your data impressively, Access 99 lectures & 1 hour of content 24/7, Practice w/ databases, CSV files, JSON, & XML. June 12, 2019 November 30, -0001 Editor. Webucator is a global training company founded in 2003 that has trained over 60,000 students. With 77 lectures, this course will guide you step-by-step, starting from plotting simple datasets to building rich and beautiful data visualization web apps that plot data in real-time and allow web users to interact and change the behavior of your plots via the internet from their browsers.

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