Generative AI for Software Engineers & Developers By Edcorner Learning
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Generative AI for Software Engineers & Developers · Program
About this program
Generative AI for Software Engineers & Developers
Online Course
Learning format
Generative AI
Subcategory
English
Course language
$19.99 (list $9.99)
Price
Price may change · updated within 1–2 weeks
Official program page
What you'll learn in Generative AI for Software Engineers & Developers
- Understand the fundamentals of Generative AI, including Transformers, Diffusion Models, and their relevance to software engineering.
- Access a curated 1000+ expert prompts tailored to accelerate software engineering tasks across coding, testing, DevOps, architecture, and security.
- Differentiate clearly between Predictive AI and Generative AI in the context of software development workflows.
- Explore real-world use cases of GenAI for code generation, bug fixing, documentation, DevOps automation, and architecture design.
- Master Prompt Engineering techniques: Zero-shot, Few-shot, Chain of Thought (CoT), Tree of Thought (ToT), and reusable prompt templates.
- Generate high-level software architectures, including ER diagrams, sequence diagrams, and make architectural trade-off analyses using GenAI.
- Auto-generate multi-file codebases, classes, modules, and functions while adhering to SOLID and DRY principles.
- Perform code refactoring, enhance readability, optimize performance, and add professional-grade documentation using AI assistance.
- Automate static code analysis, bug detection, anti-pattern recognition, and pull request reviews via Generative AI prompts.
- Learn how to generate Unit Tests, Integration Tests, E2E Tests, API Tests, Fuzz Tests, and achieve better code coverage.
- Build Dockerfiles, Kubernetes manifests, Terraform scripts, and automate GitHub Actions/GitLab CI/CD pipelines using GenAI.
- Design robust Infrastructure as Code (IaC) systems and automate monitoring setups with Prometheus and Grafana using prompt-driven workflows.
- Define and monitor Service Level Objectives (SLOs) and Service Level Indicators (SLIs) to maintain operational excellence.
- Create automated runbooks and disaster recovery playbooks driven by AI to boost reliability engineering practices.
- Implement Secure Code Generation, threat modeling, vulnerability detection, and automate SOC2, HIPAA, GDPR compliance drafts.
- Apply AI-based tools for Static Application Security Testing (SAST) and Dynamic Application Security Testing (DAST).
What's Included in Generative AI for Software Engineers & Developers
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