Representational State Transfer (REST) is a design that characterizes a lot of imperatives to be utilized for making web administrations.
Learning Style
Learning Style
Difficulty
Course Duration
Representational State Transfer (REST) is a design that characterizes a lot of imperatives to be utilized for making web administrations.
Representational State Transfer (REST) is a design that characterizes a lot of imperatives to be utilized for making web administrations. The services of the web that are compliant to the architecture of REST are known as the services of RESTful. The primary differentiation of RESTful services is that they give interoperability between PC frameworks on the web. This course covers the key ideas of the services of RESTful and empowers the understudies to comprehend the characteristics and utilization of REST architecture. This course includes the basics RESTful services concepts and permits the students to comprehend the characteristics and usage of the architecture of REST.
This course provides the understudies an outline of the Services of RESTful, including JAX-RS, install, and Jersey, developing an application, and the server. These basic ideas are necessary for any developer of web administration to make RESTful web services. The course can enable the understudies to launch their vocation in the field of the development of web services.
The normal compensation of an API Developer is $109,716 annually.
There are no formal pre-requirements for this course. But, understudies are advised to register for RESTful Services: Basics before opting for this course.
| Subjects | App Development |
|---|---|
| Lab Access | No |
| Learning Style | Self-Paced Learning |
| Learning Type | Course |
| Difficulty | Beginner |
| Course Duration | 3 Hours |
| Language | English |
Tom is an innovator first, and then a Data Scientist & Software Architect. He has integrated expertise in business, product, technology and management. Tom has been involved in creating category defining new products in AI and big data for different industries, which generated more than hundred million revenue cumulatively, and served more than 10 million users.
As a Data Scientist and Software Architect Tom has extensive experience in data science, engineering, architecture and software development. To date Tom has accumulated over a decade of experience in R, Python & Linux Shell programming.
Tom has expertise on Python, SQL, and Spark. He has worked on several libraries including but not limited to Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn, SciPy, NLTK, Keras, and Tensorflow.
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