BEST OT/ICS CYBERSECURITY TRAINING , MACHINE LEARNING TRAINING AND GEN AI TRAINING IN DELHI NCR AND IN INDIA


 

OT/ICS/DCS Cybersecurity Training

This specialized training focuses on securing industrial environments. It addresses the unique challenges of protecting Operational Technology (OT), Industrial Control Systems (ICS), and Distributed Control Systems (DCS), which are used in critical infrastructure like power plants, manufacturing, and utilities.

Unlike traditional IT security, the primary goals here are safety and continuous availability. Key topics include:

  • Understanding industrial protocols (e.g., Modbus, DNP3).

  • Network segmentation (like the Purdue Model).

  • Securing legacy systems that often can't be patched.

  • Incident response where physical processes are at stake.

Generative AI (Gen AI) Training

This is a cutting-edge field of AI focused on models that create new content (text, images, code, or audio). This training teaches individuals how to build, use, and deploy these powerful models.

Key topics often include:

  • Prompt Engineering: The skill of writing effective inputs to get desired outputs from models.

  • Large Language Models (LLMs): Understanding the architectures (like Transformers) that power models like GPT.

  • Fine-Tuning: Customizing pre-trained models for specific, niche tasks.

  • Applications & Ethics: Using Gen AI for tasks like content creation, code generation, and business automation, while managing ethical considerations.

Machine Learning (ML) Training

This is the foundational discipline on which Generative AI is built. ML training focuses on teaching computers to learn patterns from data to make predictions or decisions.

It covers the core algorithms and statistical principles of AI. Key topics include:

  • Supervised & Unsupervised Learning: Training models with labeled data (e.g., for spam detection) or finding patterns in unlabeled data (e.g., customer segmentation).

  • Core Algorithms: Understanding and implementing models like linear regression, decision trees, and neural networks.

  • Data Preprocessing: The critical skill of cleaning, transforming, and preparing data to be used by an ML model.

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