Here are the Cisco Security course offerings:
TechNow has heard many students talk about virtualized/remote training that TechNow Does Not Do. While training our most recent offering of PA-215: Palo Alto Networks Firewall Essentials FastTrack a student told his story of how he endend up in our course. His story we have heard for other technologies like Cisco, VMware, BlueCoat and other products.
A large percentage of training is moving to the virtualized/remote lab environments. Students are asked to use some variant of remote access software and remote into the training company's lab environment. Our student in our Palo Alto Networks Firewall course informed us that he went to a very costly offering of that course from the vendor and was not able to perform any labs. There were either network connectivity issues, or issues with the remote access software, or other problems. The whole training experience was very frustrating and not productive.
We keep our labs open to students if they would like after hours, or before hours access. Repeatedly going through a lab engrains that knowledge for later recall. Touching hardware is so critical in understanding the problems that arise when a cable comes loose, or a cable gets plugged in the wrong port. There are other scenarios such as just pulling the power cable, or turning off a power strip, or accidently overwriting a configuration. These disaster scenarious requires hands-on physical access to hardware. Preventing and recovering from disasters is what it's all about, and that requires hands-on, instructor led, real hardware.
Course Overview:
This course will be fast paced with in-depth and live demonstrations.
Date/Locations:
Duration: 1 day
Course Objectives:
Prerequisites:
Latest comments from students
Course Overview:
Getting started with the Elastic Stack (ELK), optimizing search performance and building efficient clusters. Ingest and process data, writing complex search requests and response utilization, scaling of clusters up or down, managing indices in large clusters and multiple clusters, management of clusters and troubleshooting recommendations.
Attendees to TN-430: Elasticsearch Engineer (ELK) will receive TechNow approved course materials, expert instruction, and prepare you to take ELK exam.
Dates/Locations:
Duration: 5 Days
Course Outline:
Data Management
Searching Data
Developing Search Applications
Data Processing
Cluster Management
Latest comments from students
Certified Offensive AI Security Professional (COASP) validates the competencies required for practitioners who need to demonstrate offensive AI security skills, emulating adversaries, validating defenses, and leading red-team/blue-team exercises to keep AI resilient, reliable, and auditable
The Certified Offensive AI Security Professional (COASP) equips you to identify and neutralize AI-specific threats before attackers do. And Bridges security, engineering, and data science so controls exist across the full AI life cycle.
Participants will gain hands-on experience to perform end-to-end adversarial testing and deliver defensive validation evidence including the ability to simulate adversarial AI kill chains, Harden AI architectures by secure system prompts, context windows, tool integrations, RAG pipelines, and agent memory, Conducting AI security assessments aligned to MITRE ATLAS, OWASP LLM/ML Top 10, NIST AI RMF, and DoD Test & Evaluation practices , This course covers how to build SOC-ready capabilities for AI-focused detection logic, incident playbooks, and forensic procedures , & how to execute prompt injection, adversarial prompting , Assess AI supply-chain risk , Implement defensive engineering controls and Produce assurance and compliance artifacts.
By the end of the course, learners will be well-prepared to take the Certified Offensive AI Security Professional (COASP) exam and demonstrate the ability to exploit vulnerabilities in LLMs and agents, and build defense that survive real world attacks, learners will master offensive techniques that break AI before the attackers do.
Course Outline:
01. Offensive AI and AI System Hacking Methodology
02. AI Reconnaissance and Attack Surface Mapping
03. AI Vulnerability Scanning and Fuzzing
04. Prompt Injection and LLM Application Attacks
05. Adversarial Machine Learning and Model Privacy Attacks
06. Data and Training Pipeline Attacks
07. Agentic AI and Model-to-Model Attacks
08. AI Infrastructure and Supply Chain Attacks
09. AI Security Testing, Evaluation, and Hardening
10. AI Incident Response and Forensics
Prerequisites:
TN-412: Artificial Intelligence Essentials (AI|E)
Dates/Locations: