Advanced Django: Introduction to Django Rest Framework (Coursera)

Offered by Codio,
Advanced Django: Introduction to Django Rest Framework (Coursera)

Code and run Django websites without installing anything! This course is designed for learners who are familiar with Python and basic Django skills (similar to those covered in the Django for Everybody specialization). The modules in this course cover an introduction to the the Django REST framework and handling JSON within the context of APIs, fundamentals such as serialization ViewSheets, and authentication/permissions.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

To allow for a truly hands-on, self-paced learning experience, this course is video-free. Assignments contain short explanations with images and runnable code examples with suggested edits to explore code examples further, building a deeper understanding by doing. You’ll benefit from instant feedback from a variety of assessment items along the way, gently progressing from quick understanding checks (multiple choice, fill in the blank, and un-scrambling code blocks) to slowly building features, resulting in large coding projects at the end of the course.
Course Learning Objectives:

  • Describe how the Django REST framework allows Django websites to leverage APIs
  • Apply the Django REST framework
  • Leverage ViewSets to map views to logic
  • Setup authentication and configure permissions

Course 2 of 4 in the Advanced Django: Mastering Django and Django Rest Framework Specialization.

What You Will Learn

  • Build an API with Django Rest Framework
  • Use Postman to explore the API
  • Add functionality with serializers, viewsets, routers, authentication, and permissions

Syllabus

WEEK 1: Introduction to REST APIs
WEEK 2: Django Rest Framework Serializers and Views
WEEK 3: Django Rest Framework Relationships
WEEK 4: Django Rest Framework APIs

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Computational Thinking for Problem Solving (Coursera) Coursera
University of Pennsylvania

Computational Thinking for Problem Solving (Coursera)

Computational thinking is the process of approaching a problem in a systematic manner and creating and expressing a solution such that it can be carried out by a computer. But you don't need to be a computer scientist to think like a computer scientist! In fact, we encourage students from any field of study to take this course. Many quantitative and data-centric problems can be solved using computational thinking and an understanding of computational thinking will give you a foundation for solving problems that have real-world, social impact.

Jun 22nd 2026
4 Weeks
Machine Learning: Regression (Coursera) Coursera
University of Washington

Machine Learning: Regression (Coursera)

Case Study - Predicting Housing Prices. In our first case study, predicting house prices, you will create models that predict a continuous value (price) from input features (square footage, number of bedrooms and bathrooms,...). This is just one of the many places where regression can be applied. Other applications range from predicting health outcomes in medicine, stock prices in finance, and power usage in high-performance computing, to analyzing which regulators are important for gene expression.

Jun 22nd 2026
5-12 Weeks
Using Python to Interact with the Operating System (Coursera) Coursera
Google

Using Python to Interact with the Operating System (Coursera)

By the end of this course, you’ll be able to manipulate files and processes on your computer’s operating system. You’ll also have learned about regular expressions -- a very powerful tool for processing text files -- and you’ll get practice using the Linux command line on a virtual machine. And, this might feel like a stretch right now, but you’ll also write a program that processes a bunch of errors in an actual log file and then generates a summary file. That’s a super useful skill for IT Specialists to know.

Jun 23rd 2026
5-12 Weeks
Fitting Statistical Models to Data with Python (Coursera) Coursera
University of Michigan

Fitting Statistical Models to Data with Python (Coursera)

In this course, we will expand our exploration of statistical inference techniques by focusing on the science and art of fitting statistical models to data. We will build on the concepts presented in the Statistical Inference course (Course 2) to emphasize the importance of connecting research questions to our data analysis methods. We will also focus on various modeling objectives, including making inference about relationships between variables and generating predictions for future observations.

Jun 22nd 2026
4 Weeks
Hypothesis Testing with Python and Excel (Coursera) Coursera
Tufts University

Hypothesis Testing with Python and Excel (Coursera)

In today's job market, leaders need to understand the fundamentals of data to be competitive. An essential procedure to understand business and analytics is hypothesis testing. This short course, designed by Tufts University expert faculty, will teach the fundamentals of hypothesis testing of a population mean and a population proportion, using Excel and Python for calculations. You'll also discover the central limit theorem, which is essential for hypothesis testing. To conclude the course, you will apply your newfound skills by creating a plan for an experiment in your own workplace that uses hypothesis testing.

Jun 23rd 2026
1 Week
Interfacing with the Raspberry Pi (Coursera) Coursera
University of California, Irvine

Interfacing with the Raspberry Pi (Coursera)

The Raspberry Pi uses a variety of input/output devices based on protocols such as HDMI, USB, and Ethernet to communicate with the outside world. In this class you will learn how to use these protocols with other external devices (sensors, motors, GPS, orientation, LCD screens etc.) to get your IoT device to interact with the real world.

Jun 22nd 2026
4 Weeks
Introduction to Data Science in Python (Coursera) Coursera
University of Michigan

Introduction to Data Science in Python (Coursera)

This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively. By the end of this course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses.

Jun 22nd 2026
4 Weeks
Accounting Data Analytics with Python (Coursera) Coursera
University of Illinois at Urbana-Champaign

Accounting Data Analytics with Python (Coursera)

This course focuses on developing Python skills for assembling business data. It will cover some of the same material from Introduction to Accounting Data Analytics and Visualization, but in a more general purpose programming environment (Jupyter Notebook for Python), rather than in Excel and the Visual Basic Editor. These concepts are taught within the context of one or more accounting data domains (e.g., financial statement data from EDGAR, stock data, loan data, point-of-sale data).

Jun 22nd 2026
5-12 Weeks
Cloud Networking (Coursera) Coursera
University of Illinois at Urbana-Champaign

Cloud Networking (Coursera)

In the cloud networking course, we will see what the network needs to do to enable cloud computing. We will explore current practice by talking to leading industry experts, as well as looking into interesting new research that might shape the cloud network’s future. This course will allow us to explore in-depth the challenges for cloud networking—how do we build a network infrastructure that provides the agility to deploy virtual networks on a shared infrastructure, that enables both efficient transfer of big data and low latency communication, and that enables applications to be federated across countries and continents? Examining how these objectives are met will set the stage for the rest of the course.

Jun 22nd 2026
5-12 Weeks
AI Workflow: Business Priorities and Data Ingestion (Coursera) Coursera
IBM

AI Workflow: Business Priorities and Data Ingestion (Coursera)

This is the first course of a six part specialization. You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones. This first course in the IBM AI Enterprise Workflow Certification specialization introduces you to the scope of the specialization and prerequisites.

Jun 22nd 2026
2 Weeks