LLM Applications

Learn best practices for generating high-quality code with LLMs

Sentiment analysis, topic classification, and intent detection

Extract key points and create summaries from long texts

Extract entities, relationships, and structured data from unstructured text

Build systems that answer questions from documents and knowledge bases

Generate synthetic data for training, testing, and augmentation

Learn how to build reliable chatbots by configuring system prompts, setting behavioral rules, and handling edge cases

Master text transformation techniques: translation, rewriting, simplification, formalization, and tone adaptation using LLMs

Learn how embeddings and cosine similarity enable semantic search that understands meaning, not just keywords

Learn to generate high-quality marketing copy, emails, product descriptions, and creative content with LLMs

Convert natural language questions into SQL queries using LLMs — schema-aware, validated, and production-ready

Get reliable structured data from LLMs using JSON mode, function calling, output schemas, and validation patterns

Go beyond positive/negative with aspect-based sentiment analysis, sarcasm detection, and multi-dimensional opinion mining