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⚙️ Reconstructed AI Engineering Life Cycle with MLOps, AgentOps, and DevOps 🔹 Phase 1: Planning and Strategy (The Blueprint) ❓ “Should I even build this?” Activities: Ops Overlay: 🔹 Phase 2: Evaluation-Driven Development ❓ “How do I evaluate my application?” Activities: Ops Overlay: 🔹 Phase 3: Production Readiness and Advanced Techniques Activities: Ops Overlay: 🔹 […]
This systematic process moves the AI application from a conceptual blueprint to a continuously improving product. AI Engineering Life Cycle Visual (Text Flowchart) The AI Engineering Life Cycle is defined by a systematic process of planning, evaluating, prompt engineering, using RAG, and knowing when to apply advanced techniques like agents and fine-tuning. Phase 1: Planning [&#...
AI Business Analyst (AIBA) Role — With GenAI, AI Agents & Agentic AI Responsibilities The AI Business Analyst (AIBA) role extends far beyond traditional Business Analyst (BA) responsibilities by emphasizing deep technical understanding of artificial intelligence (AI), machine learning (ML), generative AI (GenAI), and emerging agentic AI systems. This includes working closely...
90+ Cloud & DevOps Interview Questions with Hands-On Demos for Job Mastery 1. AWS Load Balancers 2. AWS VPC Peering 3. Amazon S3 Usage 4. MongoDB on EC2 with NAT Gateway 5. WordPress & MariaDB on LAMP 6. Terraform Demos 7. Intranet POCs 8. AWS CloudFormation Templates and POCs 9. Infrastructure as Code (IAC) Design […]
🌐 Offering: AWS Hands-On Mastery for Job Interviews – Demos Position yourself with confidence in cloud, DevOps, and infrastructure interviews.This offering provides a structured library of practical demos, each designed to showcase real-world skills that recruiters and hiring managers value. Every module is QA-locked, scenario-driven, and built for async learning. 🔑 What You’l...
