
Build a full stack stock prediction portal using Django REST framework, React, and machine learning with an LSTM architecture to predict stock price movements.
Install essential tools for api development—VS Code, git bash for Windows or Mac terminal, Postman, and Anaconda or Miniconda with Jupyter—and begin with Django Rest framework fundamentals.
Explore how an application programming interface enables two-way communication between the front end and back end through HTTP requests and REST API, with weather data examples.
Learn how rest api enables stateless client–server communication, using get, post, put, and delete to manage resources—such as students—identified by uris and returned as json or xml.
Create and activate a virtual environment for your project to keep Python packages organized, install Django, start a Django project with django-admin, and run the server to generate sqlite3 database.
Install Django Rest framework and configure it in your project, following the DRF tutorial, activate your virtual environment, run pip install, and add rest_framework to installed apps.
Distinguish web application endpoints from api endpoints, and follow a Django example showing a versioned rest api endpoint that returns student data for front-end integration.
Create a simple api endpoint at api/v1/students that returns a json response, illustrating public url patterns, json formatting, and the browsable api for development.
Create a django model for students, run migrations and create a superuser, register the model in admin, and populate data to enable dynamic data retrieval via a rest api.
Learn to fetch dynamic data from the database by querying the student model and serializing the results for JSON responses, including options for manual serialization and Django REST framework serializers.
Learn serialization and deserialization concepts and use model serializers to automatically convert Django models to JSON or XML, then deserialize client data back into model instances for seamless server-client communication.
Create a student serializer in serializers.py and a function-based view to get all students using the serializer with many=True, via a DRF API view and the browsable interface.
Post data with a Django rest framework endpoint using request.data, is_valid, and serializer.save. Note 201 created or 400 bad request, and test with Postman.
Create an api endpoint to fetch a single student by primary key. Use a function-based view and serializer to return 200 with the student data or 404 if not found.
Update operation on student using django rest framework: process put request, validate incoming data with serializer, update existing student, return updated data with 200 status, and handle bad request errors.
Perform primary key based delete operations using Django REST framework function-based views by handling get, put, and delete in a single method, returning HTTP 204 no content after deletion.
Explore class based views to handle requests with object oriented principles, mapping get, post, put, and delete to crud operations, boosting code reusability and introducing mixins, generics, and view sets.
Create an app named employees, define an employee model with id, name, and designation, and register it in admin. Serialize the model and explore class-based views to perform CRUD operations.
Import the employee model, extend serializers.ModelSerializer, and configure Meta with the employee model and all fields to create the serializer. Next, set up a URL and a class-based view.
Define a class-based api view to fetch all employees using the employee model and serializer, expose it via a url pattern, and return a 200 response.
Create a new employee with a post method inside a class-based view, validate data with the employee serializer, and return 201 created or 400 bad request.
Learn to fetch a single employee by primary key, handle not found errors, and update records with Django REST framework by defining the detail URL, get_object, and serialized get/put responses.
Update and delete an employee by primary key using put and delete operations, validating with the serializer and returning updated data or 204 no content.
Learn how Django Rest framework uses mixins to add common CRUD functionalities to views, including list, create, retrieve, update, and destroy, via class based views and generics.
Implement list and create mixins in the employee project using rest framework ListModelMixin and CreateModelMixin with a generic API view, wiring get and post to list and create.
Implement retrieve, update, and destroy mixins for primary key based operations in Django REST Framework, configuring queryset and serializer, and handling get, put, and delete requests.
Explore how generics provide prebuilt API views and mixins to perform CRUD in Django REST Framework, including list, create, retrieve, update, and destroy.
Learn to implement Django REST framework generics for employees by using list, create, and retrieve views with an employee serializer and queryset to list, create, and detail employee data.
Implement primary key based operations with Django REST Framework generics retrieve update destroy view for employee detail. Test by ID and see combined CRUD in one view, reducing code.
Explore viewsets in django rest framework to simplify standard crud operations by using viewsets or model viewsets, and automate url routing with routers.
Learn to implement Django REST framework view sets with a default router, register an employee view set with a base name, and enable list and create operations via a serializer.
Retrieve a single object by its primary key with the viewset's retrieve method using get_object_or_404 and a serializer. The router auto-generates URLs for listing, creating, retrieving, updating, and deleting.
Explore how Django REST Framework model viewsets handle update and delete with a single class, while enabling non-primary key and primary key operations via a serializer.
Explore nested serializers in Django REST framework by fetching a blog with its related comments via a foreign key relationship, returning a blog with its comments array.
Create a Django app named blocks with blog and comment models. Establish a one-to-many relationship via a foreign key with cascade delete and a related name comments.
Create comment and blog serializers using ModelSerializer in the API or blogs app, with fields set to all, and note that nested serializers will be covered in a lesson.
Implement nested serializers in Django REST Framework by wiring blog and comment endpoints with generics list-create views and embedding comments inside blogs via the related name.
Configure primary key based operations for blog and comment models using Django REST Framework, enabling retrieve, update, and destroy via class-based views and pk lookup.
Explore how to paginate data in Django Rest Framework using page number and limit offset strategies, with offset and limit controls and page navigation demonstrated on a blocks example.
Configure global pagination in the Rest framework by setting the default pagination class and page size in settings.py, enabling automatic page number pagination or limit offset pagination across views.
Create a custom pagination by extending page number pagination, override page size and page query params, and apply it to the employees view to expose next, previous, count, and results.
Learn how filtering works in Django Rest Framework with the django-filter library, filtering by designation like software engineer, combining lookups, and configuring a global filter backend for an employee dataset.
Implement a custom designation filter in Django REST Framework to enable case-insensitive, exact lookups for employees via a dedicated filters.py and view set integration.
Master custom employee filters in a Django REST Framework app by name contains queries and id range filters, including handling integer primary keys versus character employee IDs.
Implement a custom id range filter for employees using Django filters, enabling id min and id max with a custom filter method and label adjustments.
Enable search on the blog API with DRF's inbuilt search filter, targeting blog title and body. Override the query param to q and use the carrot for starts-with filtering.
Implement the ordering filter in Django REST framework by adding an ordering filter to blog views, defining ordering fields like ID ascending or descending, and optionally overriding the ordering_param.
Wraps up the basics of the Django REST framework while introducing advanced topics through a stock prediction portal using DRF, machine learning, and a ReactJS frontend.
Discover React.js introduction to build the stock prediction portal and become a full stack developer by using a JavaScript library for building user interfaces, single page applications, and reusable components.
Explore how React uses modular components and the virtual dom to update only affected parts of the page, delivering fast, reusable interface blocks and smooth DRF-powered full-stack apps.
Build a solid web development foundation by mastering HTML, CSS, and JavaScript before diving into React, and install Node.js to begin with the setup in the next video.
Install the Node.js LTS installer for your OS, verify with node -v and npm -v, and learn npm as the node package manager before creating a React project.
Create a React project with npx, learn that npx runs packages temporarily without installation, and compare it to npm while introducing wheat as a faster build tool.
Learn to create a React project with Vite using npm. Delete old files, install dependencies, and run the local dev server for the stock prediction portal.
Examine the React project directory structure, from root, node_modules, public, to src. Review essential files like eslint, gitignore, and package.json, plus the dev and build scripts.
Learn to edit a default React project by updating index.html, switching the title to React plus Django, and modifying app.js in the src folder, with automatic reload on save.
Delete default react app files by removing public v.svg, src/assets/react.svg, and app.css contents, drop unused imports, and update index.html title to learn React.
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.