This concentration was developed in conjunction with the U.S. National Security Agency (NSA) providing an invaluable tool for any systems security engineering professional. CISSP®-ISSEP is the guide for incorporating security into projects, applications, business processes, and all information systems. Security professionals are hungry for workable methodologies and best practices that can be used to integrate security into all facets of business operations. The SSE model taught in the IATF portion of the course is a guiding light in the field of information security and the incorporation of security into all information systems.
Attendees to TN-812: Information Systems Secuirty Engineering Professional (ISSEP) will receive TechNow approved course materials and expert instruction.
This course is designed for professionals that are expected to do malware analysis. A skills focus enables the student to better absorb the subject matter and perform successfully on the job. This is not death by power point. The course is aligned with information assurance operators and executing hands-on labs. Lecture and labs walk the student through the knowledge required to truly understand the mechanics Reverse Engineering Malware.
Attendees to TN-999: Reverse Engineering Malware will receive TechNow approved course materials and expert instruction.
Date/Locations:
No Events
Duration: 5 days
Course Objectives:
Toolkit and Lab Assembly
Malware Code and Behavioral Analysis Fundamentals
Malicious Static and Dynamic Code Analysis
Collecting/Probing System and Network Activities
Analysis of Malicious Document Files
Analyzing Protected Executables
Analyzing Web-Based Malware
DLL Construction and API Hooking
Common Windows Malware Characteristics in x86 Assembly
Unpacking Protected Malware
In-Depth Analysis of Malicious Browser Scripts, Flash Programs and Office
In-Depth Analysis of Malicious Executables
Windows x86 Assembly Code Concepts for Revers-Engineering Memory Forensics for Rootkit Analysis
Prerequisites:
Strong understanding of core systems and network concepts
Exposure to programming and assembly concepts
Comfortable with command line access
Comments
Latest comments from students
User: marcus.osullivan
Instructor comments: Good stuff. I like the beginning half where there was help from an additional instructor to facilitate fixing computer errors that inevitably popped up.
Facilities comments: The baby deer were neat! I like the resort.
Certified AI Program Manager (CAIPM) is EC-Council’s professional certification for people responsible for owning AI decisions and driving execution: business, technology, data, and risk.
The Certified AI Program Manager (CAIPM) Course equips you with hands-on expertise across the full spectrum of AI tools, from conversational AI and image generation to code assistants and audio synthesis.
Participants will learn how to evaluate, deploy, and integrate AI tools into enterprise workflows, understanding not just how they work, but how to leverage them for maximum business impact. This course covers how to assess AI readiness across teams and processes, Prioritize AI use cases tied to business outcomes, Design adoption and rollout roadmaps , Coordinate delivery across cross-functional teams, implement governance, Responsible AI, and security controls , and how to track performance and ROI to prove value
By the end of the course, learners will be well-prepared to take the Certified AI Program Manager (CAIPM) exam and demonstrate the ability to own AI initiatives end to end , validate mastery of decision framing and trade-off analysis for AI initiatives and Apply governance, ethics, and risk management principles across the AI lifecycle.
Course Objectives:
•MLOps Principles: Model life cycle management for scalable, production-ready AI •Use Case Evaluation: ROI-driven assessment and prioritization of AI initiatives •AI Strategy Frameworks: Enterprise AI roadmapping, portfolio planning, and value prioritization •AI Investment Justification: Quantifying AI value, ROI, and mission impact for funding decisions •Change Management: Workforce enablement and stakeholder alignment •KPI Development: AI metrics, success indicators, and executive dashboards •AI Governance: Risk, ethics, compliance, and responsible AI principles •Vendor Evaluation: AI platform and tool selection aligned with enterprise needs
Dates/Locations:
No Events
Prerequisites:Familiarity with generative AI concepts, prompt engineering fundamentals, and AI workflows will help you succeed.
