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Artificial Intelligence in - Software-Development

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Objectives

The course highlights AI-driven coding, automated testing, and code optimization to streamline the software development lifecycle. Emphasis is on using AI-powered IDEs, code generation, and testing tools to reduce errors, accelerate delivery, and improve overall software quality. Additionally, it showcases how intelligent automation can support collaboration, continuous integration, and faster iteration, making teams more productive while maintaining high standards of code quality.



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Course Outcome

Efficiently leverage AI-powered tools to accelerate coding, including code generation and refactoring.
Utilize AI-augmented IDEs to enhance developer productivity and produce higher quality code.
Automate comprehensive testing processes, including unit, regression, and UI testing with AI assistance.
Conduct intelligent code reviews highlighting quality issues and anti-patterns using AI analysers. use cases.
Integrate AI workflows into CI/CD pipelines for continuous and automated deployment.
Navigate the ethical and legal aspects of AI-generated code with confidence.
Build robust, smarter software faster through AI-driven development practices.

Why Mazenet?


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    Expert Faculty

    Our Faculty comprises of 300+ SMEs with many years of experience. All our trainers possess a minimum of 8+ years of experience.

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    Proven Track Record

    We have served over 200+ global corporate clients, consistently maintaining a 99% success rate in meeting training objectives for 300+ technologies with quick turnaround time.

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    Blended Learning

    We provide course content over any platform that our clients prefer. You can choose an exclusive platform or a combination of ILT, VILT, and DLP.

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    Learning Paths

    The learning paths are very defined with clear benchmarks. Quantitative assessments at regular intervals measure the success of the learning program.

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    Case Study

    We have amassed over 10,000 case studies to support training delivery. Candidates will be trained to work on any real-time business vertical immediately after the training.

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    24*7 Global Availability

    We are equipped to conduct training on any day, date or time. We have delivered training pan India, Singapore, North America, Hong Kong, Egypt and Australia.

Delivery Highlights

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    Customized Training Modules

    Training programs are highly flexible with module customizations to suit the requirements of the business units.

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    Certification

    The training can be supplemented with appropriate certifications that are recognized across the industry.

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    Multi-language Support

    Course content can be delivered in English, Spanish, Japanese, Korean or any other language upon request.

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    Personalized Training Reports

    Candidates are assessed individually at regular intervals and are provided unique learning suggestions to suit their learning calibre.

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    Industry-Oriented Training

    Industry-oriented training, completing which, candidates can be immediately deployed for billable projects.

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    Diverse Training Platforms

    Choose from Instructor-Led Training, Virtual Instructor-Led Training, Digital Learning Platform and Blended Training platforms

Contact Us
Ready to get started?
Let's chat.
info@mazenetsolution.com +91 9500929297
          +91 7397723052
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Get Started Today

Course Preview

  • Explore how AI is transforming the software development lifecycle.
  • Understand the benefits and limitations of AI-assisted coding.
  • Get introduced to key AI tools like GitHub Copilot, Tabnine, and Replit Ghostwriter.

  • Learn how AI models understand code context and syntax.
  • Practice writing functions, boilerplate code, and comments with AI support.
  • Recognize the limitations and best practices for reviewing AI-generated code.

  • Discover AI-enhanced code editors and features such as auto-suggestions and refactoring.
  • Utilize AI plugins in Visual Studio Code, IntelliJ, and Replit for real-time error detection.

  • Generate unit tests automatically using AI tools.
  • Use machine learning to predict bugs and improve test coverage.
  • Explore AI-assisted regression and UI testing platforms like Testim and Mabl.

  • Apply AI for static code analysis and linting.
  • Use AI-driven quality scoring and anti-pattern detection.
  • Integrate code review automation into CI/CD pipelines.

  • Versioning, Documentation, and DevOps Automation Auto-generate documentation and intelligent commit messages.
  • Create smart build and deployment scripts using natural language models.
  • Incorporate AI for log analysis, performance monitoring, and alert triage DevOps.

  • Focus on responsible AI use in coding processes.
  • Address licensing, intellectual property, and security concerns for AI-generated code.
  • Understand AI bias in code suggestions and its impact on software quality.

  • Develop a feature such as a login system using Copilot.
  • Automatically generate and run unit tests with PyTest or JUnit.
  • Conduct AI-assisted code reviews with insightful comments.
  • Enhance workflows by integrating AI plugins into existing IDEs.