What you would learn in Projects In Python For Intermediate course?
In this course, you will be taught how to create Python projects with the existing Python abilities.
In this class, we'll develop four significant applications that will cover the latest technologies such as Django, OpenCV, Implementing Machine Learning Models, Rake NLTK Tkinter, and many more.
Here's a short overview of the topics you will be learning in each segment of the class:
Section 1:Building A Data Analysis & Visualisation Web App.
Python: Programming Language
Django is a web-based application.
Pandas: For data analysis.
ChartJS: For data visualisation.
In this section, we'll build a data analysis and visualization web application. The application will take data from the raw CSV file in the pre-defined format and create visually appealing charts. It will begin by studying and comprehending the specification document for software and then determining what must be constructed. The SRS document will be a copy of the actual document provided by software clients to their developers. Then we install the development environment on the machine required to build the app. Because this is a Web application, we employ Django as the platform for building the entire application. We know how to install and download Django on our system and learn the basic understanding of Django to begin. Then, we will learn how to build our Django application take the CSV file provided by the user. Then, it will take the data it contains. We will also learn how to transform data from the CSV data into the panda's data frame so that the data can be analyzed and manipulated. Then, we render the data as an HTML page and display it in tabular format. We also analyze the data with pandas and afterward feed the analyzed data into the Django template to display the data in terms of charts to aid in data visualization. We use a library called ChartJS to display information on our website. This project will discover how various technologies such as Django, Pandas, and ChartJS are integrated to make an actual web application.
Section 2. Monitoring Performance of Computers using Tkinter.
Python: A programming language
Tkinter: To build an interface for users using graphics
Psutil: For accessing hardware stats
Speedtest: To determine the speed of internet download, upload speed, and Ping.
In this section, we'll develop a desktop application that tracks CPU and RAM utilization in real-time. The project will be developed using tools like Python, Tkinter, psutil, and the speediest. This application will be able to determine the internet download, ping, and upload speed, as well. We will discover that the library psutil permits us to access OS APIs on a level and, in turn, give us access to the performance of computers data in real-time. We'll first determine the CPU utilization, then RAM usage, and finally the internet speed. Then we will learn to display this information on an application for desktops using Tkinter. We create the complete user interface using Tkinter and show all the information on a single screen. We also learned to create customized fonts, colors, and images to improve our app's design and feel.
Third Section: The Contextual Adverting Platform.
Python: A programming language.
Django: For web app.
Requests: To make HTTP requests for blog posts.
BeautifulSoup: To parse webpages
RakeNLTK: To locate relevant keywords
Contextual ads are a technique that identifies relevant advertisements from blog posts to maximize a blog's or website's earnings. Contextual advertising is when you will see an advertisement for Nike sneakers in a fitness-related article. In this section, we'll build a contextual advertisement platform that will read information from any blog whose URL is entered, search for relevant keywords on the blog, and then find ads that match the keywords and it is automatically. The first step is to create a basic Django application that can accept a blog's URL, read all the blog's information using the requests library, and parse it with BeautifulSoup. The parsed data into the rake library. It then determines those most pertinent and well-known keywords within the blog post and saves them for later use. These keywords match the ads in our database. It then provides us with the most relevant ads to the blog post. We also employ Tailwind to customize the website app.
Section 4: Gesture Volume Control Software For Mac & Windows.
Python is a programming language.
OpenCV: To record webcam input.
Mediapipe: To detect and track hands.
Osascript: To control the system of the volume of Mac.
Pycaw: To manage the volume of the system on Windows.
This is the most intriguing one. We will create software for volume control using gestures that allow you to regulate your computer's volume level simply using your fingers. The software records the webcam's input, determines the focal points of your hands, such as the joints and fingers, and lets us determine how far two locations are. To develop this application, we use OpenCV's Python module that allows us to capture video with our webcam frame-by-frame. After the video has been recorded, it is then used MediaPipe, which provides us with an already-trained set of machine learning models that enable us to identify hands when a live video is played. We then look for the central locations on our hands to recognize gestures and then determine the distance between the tips of two fingers to ensure we can control the system's volume. Then, we use Osacript to control volume on Mac and pycaw for Windows to control system volume, and then connect both of them to allow the volume to be controlled with two fingers.
- Create a data analysis application that reads data in CSV files CSV file and then creates charts to show data in a visual.
- Develop a computer performance monitoring software that shows data such as CPU and RAM usage in real-time
- Create a contextual ad platform that looks for relevant ads to your blog writing.
- Create a volume control that works on Mac & Windows, which controls the volume of your computer using hand gestures