IT Career Guides & Free Resources
Expert roadmaps, tutorials, salary guides and interview prep across Data Science, Generative AI, Python, Cloud & Analytics — written by GloryTecks trainers in Hyderabad.
All articles
Evaluating LLM Outputs: Metrics, Tools and Best Practices
Every change to a prompt or model needs evidence that it helped. This guide explains the main ways to evaluate LLM outputs, then checks a small local LLM judge against expert human verdicts from MT-Bench and finds it agreeing often, flipping often when answers swap places, and trustworthy only when consistent.
How to Reduce LLM Hallucinations in Production
Language models state wrong things fluently, and in production that becomes a support or legal problem. This guide explains why models hallucinate, then asks a small model twelve questions about an invented shop's policies under four set-ups, from no document to a document with rules and a quote check in code.
Generative AI and LLM Interview Questions
Many generative AI and LLM interviews now include questions you can only answer with numbers: how good is this retrieval, how many tokens will this cost, which search method should we use. This guide works through those questions on a real banking-queries dataset, with recall, MRR and token budgets actually computed.
Cost Optimization for LLM Applications in Production
LLM bills grow with every token, and most applications waste many of them. This guide breaks a request's cost into its parts, measures prompt caching and output length on a local model, then prices five options for a month of traffic using published list rates, from no changes to a cached small model.
Prompt Injection and LLM Security: What You Need to Know
Prompt injection is the top risk in the OWASP Top 10 for LLM applications, and there is no known way to prevent it outright. What direct and indirect injection look like, why RAG and agents widen the attack surface, and the design controls that limit the damage.