Udemy – In-Depth: Developing Generative AI Applications with Spring 2024-8
Udemy – In-Depth: Developing Generative AI Applications with Spring 2024-8 Downloadly IRSpace

In-Depth: Developing Generative AI Applications with Spring is a training course on using the power of generative artificial intelligence in the Spring framework, published by Udemy Online Academy. In-Depth: Developing Generative AI Applications with Spring is a specialized course designed for developers looking to harness the power of generative AI within the Spring framework. This course covers the fundamentals of generative artificial intelligence, including neural networks and deep learning techniques, while providing hands-on experience building applications that use these technologies.
People will learn how to integrate AI models into their Spring applications, manage data pipelines, and use tools like TensorFlow and PyTorch. This course explores the fundamentals of artificial intelligence and generative neural networks, with a focus on building applications with the Spring framework. Individuals gain hands-on experience integrating AI models, managing data pipelines, and using tools such as TensorFlow and PyTorch. By the end of the course, learners will be proficient in creating robust generative AI applications, equipped with the skills to implement advanced features such as natural language processing and image generation.
What you will learn in In-Depth: Developing Generative AI Applications with Spring:
- Understanding the principles of artificial intelligence
- Rapid Engineering and RAG
- Participation in extensive practical laboratories
- Managing practical programming challenges
- Automated testing methods
- and…
Course specifications
Publisher: Udemy
Instructors: Ken Krueger
Language: English
Level: Intermediate
Number of Lessons: 16
Duration: 8 hours and 39 minutes
Course topics
In-Depth: Developing Generative AI Applications with Spring Prerequisites
Students should have basic proficiency in Java, including experience with the Spring Framework and Spring Boot. To complete the hands-on labs (recommended), students must also have access to a computer capable of running Java and an integrated development environment (IDE) of their choice, such as IntelliJ IDEA, Eclipse, or Visual Studio Code.
Some hands-on labs require setting up accounts and credentials with AI model providers. These services may have associated charges, which are not covered by the course fee, though the overall cost is minimal.
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In-Depth: Developing Generative AI Applications with Spring introduction video
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