Projects In Python for Intermediate is a course to help beginners and intermediate Python programmers develop quality projects. It starts with the basics of programming, such as variables, expressions, and functions, and then moves on to more complex topics such as objects, databases, web programming, and graphics. This course is packed with tips and examples that will help you quickly learn new concepts.
In this course, we will build 4 Major apps covering technologies like Django, OpenCV, Implementing Machine Learning Models, Rake NLTK, Tkinter, and a lot more. We will use Python for this course and explore different libraries and frameworks to create our projects. This is a great way to learn the basics of these technologies as well as how they work together.
Projects In Python For Intermediate
Python is a versatile programming language that can be used to build real-world software. Python is widely used in many industries, such as scientific computing, web development, and data science. Python has a rich standard library that makes it easy to integrate multiple technologies with Python to build real-world apps. In this course, you will learn how to use the Python Standard Library to build real-world software using different technologies such as web services, databases, and machine learning. This course will teach you how to build robust and scalable applications using Python.
You will learn
- Build a data analysis app that reads data from a CSV file and creates charts out of it for data visualization.
- Build a computer performance monitor software that displays data like RAM & CPU usage in real-time
- Build a contextual ad platform that searches for Ads relevant to any blog article you post
- Build a gesture-based volume controller for Mac & Windows which controls your computer’s volume via hand gestures
Projects In Python For Intermediate
Here Is What You Get By Enrolling In This Course:
Word-By-Word Explanation: In the entire course, I explain each line of code, without skipping a single line of code.
Awesome Quality Content: Over 10+ hours of HD Videos.
Well Structured & Easy To Learn: Course has been specially designed to make it easy for the students to learn Django starting from a basic level and gradually moving up to advance concepts.
24 X 7 Support: I will always be there to guide you in your journey to become a Django expert.
Here Is Everything You Will Learn In This Complete Course:
In this hands-on course, you will learn how to build Python projects using your existing Python skills.
In this course we will build 4 Major apps covering technologies like Django, OpenCV, Implementing Machine Learning Models, Rake NLTK, Tkinter and a lot more.
Here is a brief description of what you will learn in each section of the course:
Section 1: Building A Data Analysis & Visualisation Web App.
Python : Programming Language
Django : For web based app.
Pandas: For data analysis.
ChartJS: For data visualisation.
In this section, we will be building a data analytics and visualization web app. This app will read data from a raw CSV file in a pre-defined format and will generate visualization charts for us. We will start off by reading and understanding the software requirements specification document and figuring out what exactly needs to be built. This SRS document will mimic the real document which is given by clients to software developers. We then set up the required development environment on our machine required to build the project. As this is a web app, we use Django as a platform to build our entire app, we learn how to download and install Django on our machine and also learn a few basics about Django to get started.
We will then learn how to make our Django app read a CSV file submitted by the user and then read data from it. We will learn how to convert the CSV data into a pandas data frame so that the data could be manipulated and analyzed. We then render this data to an HTML page and display it in a tabular format. We also analyze the data using pandas and then feed the analyzed data to a Django template and display it in terms of charts for data visualization. We make use of a library called ChartJS to display data on our webpage. Hence in this project, we learn how multiple technologies like Django, Pandas, and ChartJS integrate together to form a working web app.
Section 2: Computer Performance Monitor Using Tkinter.
Python: Programming language
Tkinter: For building a graphical user interface
Psutil: For accessing hardware stats
Speedtest: Forgetting the internet download, upload speed, and ping.
In this section, we will build a desktop app that monitors CPU & RAM usage in real-time. This project would be built using technologies like Python, Tkinter, psutil and speediest. This app will also be able to calculate the ping, internet download, and upload speed as well. We will learn how the psutil library allows us to access the OS level APIs and in turn give us access to the computer performance stats in real-time.
We will first calculate the CPU usage, then RAM usage, and finally the internet speed. We then learn how to represent this information in a desktop app using Tkinter. We build the entire interface for our app using Tkinter and then display all the statistics on a window. We also learn how to use custom fonts, colors, and images to give our app a better look and feel.
Section 3: Contextual Advertising Platform.
Python: Programming language.
Django: For web app.
Requests: For making HTTP requests to blog pages.
BeautifulSoup: To parse webpages
RakeNLTK: To find relevant keywords
Contextual advertising is a technology that finds relevant ads from a given blog article to maximize a blog or website’s revenue. Contextual advertising is the reason why you see an ad for Nike shoes in a fitness-related article. In this section, we will be building a contextual advertising platform that reads data from any blog whose URL you pass in, find relevant keywords on that blog, and find ads that are relevant to them and all of this is done automatically.
First, we create a basic Django app that could accept a blog URL, then read all the data on that blog page using the requests library and parse the data using BeautifulSoup. We then feed the parsed data to the rake library which then finds the most relevant and prominent keywords in that blog article and saves them. These relevant keywords are then matched with the ads present in our database and give us back the ads which are most relevant to the blog post. We will also use Tailwind to style up the web app.
Section 4: Gesture Volume Control Software For Mac & Windows.
Python: Programming language.
OpenCV: To capture webcam input.
Mediapipe: To detect, track hands.
osascript: To control system volume on Mac.
Pycaw: To control system volume on Windows.
This project would be the most interesting one, we will build a gesture volume control software that will allow you to control the volume of your computer by just using two fingers. This software captures your webcam input, detects focal points on your hand like the fingertips and joints, and allows us to find the distance between two points. To build this app we use OpenCV’s python module which allows us to capture video from our webcam, frame-by-frame.
Once the video is captured we then use MediaPipe which provides us a set of already trained machine learning models which allows us to detect hands in a live video. We then detect the key points on our hands to detect a gesture and find the distance between the tips of two fingers so that we could control the system volume. We then make use of script on Mac and pycaw on Windows to control the system volume and integrate the two things together so that volume could be controlled by two fingers.
So let’s begin the journey of developing projects with Python
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