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Generative AI For Software Development Classroom Training and Certification Classes

Generative AI For Software Development classroom training, Learn with Real Time Practice, in-class Seminars and Certification from the list of educating experts. Below listed Generative AI For Software Development Tutorial Institutes provide Course Materials, Training Syllabus, Demo Videos, Sample Questions and Answers & Curriculum. Get lectures and practical lessons on development and programming to enhance technical skills and Students will benefit with Job Placements

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      FAQ's on Generative AI For Software Development training & certification

      • How can generative AI be used in software development?

        Generative AI can be leveraged in various stages of software development. It assists in code generation, debugging, testing, and even automating documentation. Developers use tools like GitHub, Copilot to generate code snippets or complete functions, reducing development time.

      • Will generative AI replace software developers?

        Generative AI will not replace software developers but will act as an assistive tool. While AI can automate repetitive tasks and offer code suggestions, it needs more creativity and problem-solving skills for complex programming. Developers are still essential for quality control, understanding context, and handling intricate tasks.

      • Which generative AI is best for programming?

        Tools like GitHub Copilot and OpenAI Codex are considered top-tier generative AI programming tools. These tools assist with code completion and bug detection and even suggest improvements for efficiency and functionality.

      • Can generative AI create code?

        Yes, generative AI can create code using machine learning models to generate code snippets or entire blocks based on developer input. It helps generate repetitive code sections and can adapt to different programming languages.

      • Can GenAI be used in SDLC?

        Generative AI can enhance various phases of the Software Development Life Cycle (SDLC), including requirements gathering, coding, testing, deployment, and maintenance. It aids in automating test case creation, streamlining code review, and ensuring compliance in the deployment phase.

      • Which industry is likely to benefit the most from generative AI?

        The tech industry, particularly software development and cybersecurity, is set to benefit the most from generative AI. Other sectors, like healthcare and finance, also stand to gain by automating complex data analysis, code development, and cybersecurity measures.

      • What is one primary ethical concern in the use of generative AI?

        A significant ethical concern with generative AI is bias in the output. Since generative AI learns from historical data, it can perpetuate biases in the training data, potentially leading to unfair or misleadingness.

      • What are the three limitations of generative AI?

        The three main limitations of generative AI include:

        • Accuracy: AI-generated code can have errors or security vulnerabilities, requiring human oversight.

        • Contextual understanding: AI often needs more project-specific context for complex programming tasks.

        • Computational cost: Generative AI models require substantial computational resources for training and execution. 

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