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Full Stack Machine Learning | Django REST Framework, React (Udemy.com)

Learn to Build full-fledged Stock Prediction Portal using Python, Django REST Framework, React.js and Machine Learning

Created by: Rathan Kumar

Last updated September 2026

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What you will learn

  • REST API Development
  • Backend Development with Django and Frontend with React JS
  • Machine Learning with Neural Networks
  • Deep Learning with LSTM Models
  • Data Analysis, Data Manipulation and Data Visualization
  • How to decide which type of machine learning to use for specific problems.
  • Where deep learning comes in and how neural networks work.
  • Why a neural network is the best choice for this specific stock prediction use case.
  • Integration of Machine Learning Models with Web Applications

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Quality Score

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Overall Score : 88 / 100

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Course Description

Not just another course, this is a hands-on program where you’ll build a complete, stock prediction portal using Django REST Framework, React.js, and Machine Learning.


Course Flow:

  • First, you'll learn the fundamentals of Django REST Framework, including what REST APIs are and how to create them. If you're already familiar with Django REST Framework, you can skip this section.

  • Next, we'll dive into the fundamentals of React.js to build the front-end of our application.

  • After that, we'll connect Django REST Framework with React.js to build the portal. This will include implementing a user authentication system and other essential features needed for a functional application.

  • Once the portal structure is ready, it's time to dive into machine learning. This course is not a Machine Learning Bootcamp, so it won’t cover every ML concept in detail. Instead, it takes a practical approach focused on building a stock prediction portal as a real-world use case.

Machine Learning Section:

  • The basics of machine learning and its different types.

  • How to choose the right ML approach for a specific problem.

  • When and why to use deep learning and how neural networks work.

  • Why a neural network is the best choice for this stock prediction use case.

You'll build an LSTM model in Jupyter Notebook to analyze stock price data and make predictions. Once the model is ready, you’ll create an API to integrate it with the portal and display the results.

This course gives you the full experience of building a real-world stock prediction portal—a full-stack project combining Django REST Framework, React.js, and machine learning.

Additional Skills You'll Learn:

  • Data manipulation using Pandas and NumPy.

  • Data visualization using Matplotlib.

By the end of this course, you'll have built a complete project while gaining hands-on experience in both web development and machine learning.


Important Disclaimer: This prediction model should NOT be implemented in real stock market trading. It is developed purely for educational purposes to help you understand the principles of machine learning and stock market data. Relying on this model for actual investments can lead to significant financial risks.

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Instructor Details

Rathan Kumar

I've spent over 10 years as a software developer, primarily working with Python and Django, the framework I genuinely enjoy working with the most.

I've created a series of Python and Django courses on Udemy, covering everything from beginner fundamentals to advanced topics like REST APIs, machine learning integration, multi-vendor ecommerce systems, and production deployment with Docker and CI/CD.

Across these courses, I've taught thousands of students, with a focus on building complete, real-world projects rather than isolated examples. My students don't just learn syntax; they walk away having built something they can actually showcase.

Right now, my focus is on Agentic AI, specifically, how backend developers can build multi-agent AI systems using the frameworks they already know, like Django. This isn't a new direction for me, it's the next step. I believe it's one of the most important shifts in software development, and I want Django developers to be at the forefront of it, not left behind.

If you're looking to build real, production-style skills, whether in Django, machine learning, or AI-powered backend systems, you're in the right place.

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Reviews

4.4

248 ratings on Udemy

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By Gerber Reyes Requena on 7/11/2026

I think great content to understand the workflow from backend, frontend and machine learning - I think it was easier to follow if you have already experience with machine learning, react and django - while I would have like to send the data and use a react library to plot the data rather than sending a png would have been interested but more stuff keep looking for.

By Galang Piliang on 11/20/2025

Need to add an explanation about how the business side works for this project, so that I can easily present this to the future employer/client, also it will be huge thanks if you can also add the series where we can deploy this to the production environtment

By Kinshuk . on 9/10/2025

Django is explained very well, as is React. I think the ML section could be improved.

By Muhammad Nurul Alam on 8/15/2025

The course content lacks depth, and the integration between the frontend and backend in the project could be significantly improved for better functionality and cohesion. The course content taken more time in React basic then Machine Learning.

By Tyler Rubino on 6/23/2025

This course is extremely impactful. If you already have fundamentals in programming, you will find him easy to understand. His videos are well structured, build on each other, and are not too long, not too fast, and not too hard to follow. Furthermore, if you're ever confused about a topic, just ask ChatGPT to clarify it in a way you'd understand and you're set. Would absolutely recommend this course if you are interested in the stack. In the future I would love to see a MLOps style course from this instructor OR expand on the current course to show how to use docker to containerize, hosting the frontend and backend in AWS, CI/CD pipeline, even how to create a microservice with FastAPI for the ML model.

By Ganesan Sethuraman on 6/11/2025

Hello Rathan, Thanks to the great course content and the concepts explained. It was a beautiful journey for me to learn new UI and Backend concepts practically, with ML concepts. At last, there were some rush in skipping few changes. But that might be good source for the learner to explore! :) Thank you!

By Md Mahamudun Alam Mahin on 6/5/2025

It is easy to follow up and very well structured course. That is the vibe I am getting so far. Also, I think definitely a good refresher to remember old stuffs and learn new as well for someone who had some prior knowledge on both react and drf.

By Daniel López on 5/16/2025

Me parece que el curso cumple con lo que dice y la explicación es bastante clara. Obviamente si uno desea entrar en profundidad en cualquiera de estos temas, puede utilizar los recursos oficiales y de esta forma terminar de entender ciertos detalles para aplicar en otro tipo de proyectos con estas tecnologías. Pero en general, me pareció muy completo.

By Niko Suave on 4/23/2025

I am taking this as a refresher as it has been some time since I have done full stack work or worked with react, and so far it is great for myself and i believe for people with more limited knowledge as well. great explanations and given at a great pace *This is my halfway update*: I cannot recommend this course enough it very well rounded and well executed and I am deeply enjoying it.

By Adrian Karlo D Siangco on 4/20/2025

Done doing the course Apr 21, 2025. Its a working full stack and machine learning in DRF, I learn a lot from this course. The instructor is not a bogus, I can feel his passion and professionalism. Bought 2-3 courses of the Author too. You can find my comments in the end if you want proof that i finish the course.

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