AI Agents are intelligent software programs designed to act autonomously to achieve specific goals. They can perceive their environment (like a user request, data, or events), make decisions, and perform actions without human intervention.
Generative AI is a type of artificial intelligence that can create new content such as text, images, music, code, or even videos by learning from existing data. Unlike traditional AI, which mainly classifies or predicts, generative AI generates entirely new outputs.
Oct 23, 2025 — 8 min read
LLM Ops extends ML Ops practices to large-scale language models like GPT, Claude, or PaLM. These models have unique challenges due to their size, inference cost, and continuous evolution.
Oct 23, 2025 — 8 min read
Large Language Models (LLMs) like GPT-4, Claude, LLaMA, or Mistral. It goes beyond just calling an API — it’s about building robust, scalable, and intelligent systems using LLMs effectively.
Oct 23, 2025 — 8 min read
RAG stands for Retrieval-Augmented Generation, a powerful technique in AI and LLM (Large Language Model) systems that combines information retrieval with text generation.
Oct 23, 2025 — 8 min read
Model Context Protocol (MCP)” used in an AI/LLM setting, it may refer to a custom or emerging framework that handles
Oct 23, 2025 — 8 min read
Our AI Programs
3 Months
6 Live Projects
4.7/5
AI Agents are autonomous software systems that can perceive their environment, make decisions, and act to achieve specific goals. They combine reasoning...
3 Months
6 Live Projects
4.8/5
Data Science is the field of extracting insights and knowledge from data using statistics, machine learning, and data analysis techniques. It combines programming...
3 Months
6 Live Projects
4.9/5
Generative AI is a type of artificial intelligence that creates new content such as text, images, audio, code, or video based on learned patterns from data. It powers tools like ChatGPT...
3 Months
6 Live Projects
4.8/5
ML Ops (Machine Learning Operations) focuses on managing the end-to-end lifecycle of ML models — from training to deployment and monitoring — ensuring reliability and scalability.
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