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Generative AI For Software Development Training and Certification

Generative AI For Software Development Training, Learn Generative AI For Software Development with Online Practices, in-class Seminars, and Certifications from the list of world-class Generative AI For Software Development trainers. Below listed Generative AI For Software Development education partners provide Course Material, Classes Curriculum, Tutorial Videos, Interview Questions, Books, and Tricks. Get experts lectures and tailored practical lessons on Generative AI For Software Development to improve your skills and Students will benefit with Job Placements and Visa.

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  • Live or virtual instructor-led classes
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Upcoming Instructor-Led Generative AI For Software Development Class Date & Time as on June 07, 2025

Jun 9 2025
Jul 9 2025
Generative AI For Software Development
Generative AI For Software Developme...
Online Training,
$0.0000
IT Tutor PRO
Jun 10 2025
Jul 10 2025
Generative AI For Software Development
Generative AI For Software Developme...
Online Training,
$0.0000
IT Tutor PRO
Jun 11 2025
Jul 11 2025
Generative AI For Software Development
Generative AI For Software Developme...
Online Training,
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IT Tutor PRO
Jun 12 2025
Jul 12 2025
Generative AI For Software Development
Generative AI For Software Developme...
Online Training,
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IT Tutor PRO
Jun 13 2025
Jul 13 2025
Generative AI For Software Development
Generative AI For Software Developme...
Online Training,
$0.0000
IT Tutor PRO
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Generative AI For Software Development

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About Generative AI For Software Development training

  • About Our Generative AI for Software Development

    Our Generative AI for Software Development course is designed to equip software engineers with cutting-edge skills in AI-driven programming. The course focuses on integrating Large Language Models (LLMs) with traditional Software Development practices, providing insights into how AI can revolutionize the coding process. By combining Machine Learning and Generative AI, this course enables developers to streamline coding tasks, from writing and debugging to automating repetitive processes. Learners will explore advanced tools such as pair-coding with an LLM and analyzing code with AI, preparing them for the next wave of innovation in software engineering.
  • Objective of Generative AI for Software Development

    The primary objective of this course is to enable developers to harness Generative AI to automate, enhance, and optimize the Software Development lifecycle. Participants will learn to leverage Large Language Models for generating code, troubleshooting, and streamlining complex development tasks. The course aims to provide learners with the skills necessary to integrate AI into traditional programming workflows, focusing on improving productivity, reducing errors, and advancing innovation in Software Engineering. Upon completion, participants can use Machine Learning models effectively to assist in pair-coding and analyzing code.
  • What You Will Learn in This Course

    • Understand how Large Language Models integrate with Software Engineering.

    • Apply Generative AI techniques to software development tasks.

    • Analyze and debug code with an LLM.

    • Perform pair-coding with AI-driven tools.

    • Automate repetitive coding processes using Machine Learning.

    • Earn a Generative AI for Software Development Professional Certificate.

  • Career opportunities

    • AI Software Engineer

    • Machine Learning Engineer

    • AI-Powered Software Developer

    • Data Scientist in Software Development

    • AI Solution Architect

    • Technical Consultant for AI Development

Generative AI For Software Development syllabus

  • Module 1: Introduction to Generative AI

    • Define generative AI and its significance.

    • Distinguish between generative and discriminative models.

    • Explore foundational concepts of large language models (LLMs).

  • Module 2: Prompt Engineering

    • Objectives: Learn principles of prompt engineering.

    • Develop impactful prompts for coding tasks.

    • Practice refining prompts for better code quality.

  • Module 3: Code Generation and Pair Programming

    • Utilize tools like GitHub Copilot for code generation.

    • Implement pair programming techniques with LLMs.

    • Analyze AI's role in automating coding tasks.

  • Module 4: Database Design and Management

    • Collaborate with LLMs to design database schemas.

    • Implement CRUD operations using generative AI.

    • Debug database issues with AI assistance.

  • Module 5: Software Design Patterns

    • Explore common software design patterns.

    • Use generative AI to implement design patterns.

    • Discuss the advantages of applying design patterns.

  • Module 6: Testing and Quality Assurance

    • Apply generative AI for automated testing.

    • Generate test cases based on requirements.

    • Discuss best practices for integrating AI into testing.

  • Module 7: Ethical Considerations in Generative AI

    • Identify ethical concerns in programming with AI.

    • Explore strategies for mitigating bias and misuse.

    • Discuss the implications of automation on employment.

  • Module 8: Capstone Project

    • Develop a software application using generative AI tools.

    • Implement features like code generation and testing.

    • Present the project showcasing AI's impact on development.

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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