Agentic AI Skilling Program

Agentic AI Skilling Program Latest News

Recently, the National Institute of Electronics and Information Technology (NIELIT) and Intel India have launched two Agentic AI skilling programmes. 

About Agentic AI Skilling Program

• It is aimed at expanding access to industry-aligned Agentic AI learning opportunities and contributing to the development of a future-ready AI talent ecosystem in the country.
• It was launched by the National Institute of Electronics and Information Technology (NIELIT), Ministry of Electronics and Information Technology (MeitY), in collaboration with Intel India.
• Under the initiative, two programmes have been introduced
• Agentic AI for Everyone
  • It introduces learners to workflow automation, AI agents and multi-agent systems, with a focus on improving productivity, enabling business transformation and supporting intelligent decision-making.
  • The programme provides hands-on exposure to designing and governing AI-powered workflows and agentic systems using no-code platforms.
• Engineering Agentic AI Systems
  • It focuses on designing, building and deploying AI-powered agentic systems.
  • Learners will gain practical exposure to no-code/low-code platforms and code-based frameworks, covering areas including agent architecture, tool integration, orchestration, memory and deployment to develop scalable and production-ready solutions.

What is Agentic AI?

• It is an advanced form of artificial intelligence focused on autonomous decision-making and action. 
• It consists of AI agents—machine learning models that mimic human decision-making to solve problems in real time.
• Unlike traditional AI, which primarily responds to commands or analyzes data, agentic AI can set goals, plan, and execute tasks with minimal human intervention.
• “Agentic” indicates agency — the ability of these systems to act independently, but in a goal-driven manner.
• At its core, this technology is built on several key components:
  • Perception: Agentic AI starts by gathering information from its surroundings and different sources, such as sensors, databases, and user interfaces. 
  • Reasoning: Using a large language model (LLM), agentic AI analyzes the gathered data to understand the context, identify relevant information, and formulate potential solutions. 
  • Planning: The AI then uses the information it gathered to develop a plan. This involves setting goals, breaking them down into smaller steps, and figuring out the best way to achieve them.
  • Action: Based on its plan, the AI takes action. This could involve performing tasks, making decisions, or interacting with other systems.
  • Reflection: After taking action, the AI learns from the results. It evaluates whether its actions were successful and uses this feedback to adjust its plans and actions in the future.

Source: PIB

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