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Granite / Automated Code Generators

  • Duration: 7 hours
  • Exam Voucher: Yes
  • Language: English
  • Course Delivery : E - Learning Access
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Course Overview

The Next-Gen Code Intelligence: AI-Assisted Software Development & Auto-Coding Tools course is designed to help developers and engineering teams operationalize AI code assistants (including automated code generators such as “Granite”-style models) across the software delivery lifecycle.It focuses on practical engineering workflows—requirements-to-code, refactoring, test generation, documentation, code reviews, and debugging—while reinforcing an important truth: AI can write code fast, but engineering accountability keeps it correct, secure, and maintainable.

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Course Details

  • Accelerate delivery: Use AI to draft features faster and reduce boilerplate effort
  • Improve code quality: Apply AI-assisted refactoring, code review suggestions, and consistency patterns
  • Boost test coverage: Generate unit tests and edge-case checks more efficiently
  • Reduce debugging time: Use AI to triage errors, reason about logs, and propose fixes
  • Standardize engineering workflows: Build reusable prompt templates and code-generation playbooks
  • Responsible adoption: Add governance guardrails for security, privacy, licensing, and correctness
  • Open to: developers, tech leads, QA engineers, DevOps engineers, engineering managers, and product engineers
  • Recommended: basic programming experience and familiarity with standard SDLC practices
  • Helpful (not mandatory): experience with Git workflows, code reviews, and test automation
  • No mandatory prerequisites required
  • Identify where AI code assistants add value (and where human review is non-negotiable)
  • Convert requirements into structured prompts that produce usable, maintainable code
  • Use AI for refactoring, documentation, and code comprehension
  • Generate tests and improve reliability through structured validation workflows
  • Apply AI-assisted debugging and root-cause reasoning techniques
  • Implement responsible usage practices (security checks, data handling, licensing awareness, review gates)
  • Introduction to AI code intelligence and modern auto-coding workflows
  • Prompting patterns for developers: constraints, structured outputs, and reusable templates
  • AI-assisted feature scaffolding: APIs, components, boilerplate, and integration-ready code
  • Refactoring and code modernization with AI support
  • Test generation: unit tests, edge cases, and regression mindset
  • Debugging assistance: interpreting errors, logs, stack traces, and proposing fixes
  • Code review augmentation: style consistency, performance suggestions, and maintainability
  • Governance & responsible use: security hygiene, IP/licensing awareness, privacy boundaries, human-in-the-loop QA
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What Our Corporate Clients Say

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James Abot
★★★★★

Much obliged to you for this course. I get know understanding and information in utilizing various types of online apparatuses which are helpful and viable. I'll utilize some of them during my exercises. Also, heaps of much obliged.

Sayali Patil
★★★★★

This was a very immersive and interesting course from NovelVista a lot of self-learning to be done on your own to really understand and put together into practice the technology into your own course and workflow.

Amit Shrivastav
★★★★★

It was truly an amazing learning session. I did have my apprehensions before signing up, but trainer made me feel so comfortable from the time we started the session till the very end of it.Thanks for this amazing experience.

Frequently Asked Questions

Who should take this course?+

Developers and engineering teams who want to use AI code assistants to speed up delivery while maintaining quality, security, and maintainability.

Will this teach “auto-coding” end-to-end?+

Yes—the focus includes using code generation tools across the SDLC, from drafting and refactoring to testing and debugging.

Do I still need to review AI-generated code?+

Absolutely. The course emphasizes human accountability: validation, security checks, testing, and review gates.

Is this tool-specific?+

It covers AI-assisted development patterns that transfer across tools and models (including automated code generators and “Granite”-style code-assist systems).