This course identifies how business analysts can elicit Agile requirements by writing user stories from use cases and personas of customer profiles. This leads to the processes of confirming the validity and usability for quality of the product development. An Agile Business Analyst has become a new recognized role within the other Agile Framework roles.
Attendees to PM-242:Defining Agile Requirements with User Stories will receive TechNow approved course materials and expert instruction.
Dates/Locations:
No Events
Duration: 2 Days
Course Objectives: At the conclusion of this course, students will be able to:
Understand the Scrum Flow, the core components of the Scrum framework
Understand the scope of the Product Owner role in detail
Understand the scope of the Agile Business Analysis role in coordination with the Product Owner, Scrum Master and Development Team
Understand the scope of the Scrum Master role at a high level
Understand the scope of the Scrum Development Team roles
Document the interactions between the user of a system and the system itself
Dive into understanding the Agile principles for requirements using user stories in a card, conversation, and confirmation format
Target Student:
Designed specifically for Agile project team members, product owners, project leaders and business analysts or anyone wanting to understand the Agile Framework.
Looking to move up in the information security field? If you have at least one year of security experience, you qualify for the Systems Security Certified Practitioner (SSCP) certification, which offers junior security professionals a way to validate their experience and demonstrate competence with (ISC²)®’s seven domains.
Attendees to TN-715: Systems Security Certified Practitioner (SSCP) will receive TechNow approved course materials and expert instruction.
Instructor comments: Instructor was very knowledgeable on most items covered during this course. There were some topics he did lack the answer to. Instructor would also get sidetracked easily
User: keginth
Instructor comments: he was phenomenal with test prep and knew the book well
TechNow Cloud Security Fundamentals addresses the loss of hands-on control of system, application, and data security in the Cloud computing environment. Security teams wrestle with the impact and liability of Cloud computing on an organization. This course enables the security team to assist in contract language and Service Level Agreements (SLAs) when utilizing Cloud Service Providers (CSPs).
Compliance and auditing are introduced with strategies for control verification and audit analysis in the CSP environment. Software as a Service (SaaS) to Infrastructure as a Service (IaaS) and everything in between require a compliance strategy. Students will go in-depth into the architecture and infrastructure fundamentals for private, public, and hybrid clouds. Topics covered include: patch and configuration management, virtualization security, application security, and change management. Policy, risk assessment, and governance within cloud environments will be covered with recommendations for both internal policies and contract provisions to consider.
TechNow has worked worldwide enterprise infrastructures for over 20 years and has developed demos and labs to exemplify the techniques required to effectively manage security in the cloud environment.
Attendees to TN-913: Cloud Security Fundamentals will receive TechNow approved course materials and expert instruction.
CompTIA SecAI+ is the first certification in CompTIA’s expansion series, designed to help you secure, govern and responsibly integrate artificial intelligence into your cybersecurity operations. You’ll build the skills to defend AI systems, meet global compliance expectations and use AI to enhance threat detection, automation and innovation—so you can strengthen your expertise and help keep your organization’s systems and data secure.
SecAI+ helps you build practical AI security and automation skills on top of your existing expertise, so you can secure AI deployments, use AI‑assisted security tools with confidence, and stay ready for the next step in your cybersecurity career.
Course Objectives:
Apply AI concepts to strengthen your organization’s cybersecurity posture
Secure AI systems using advanced controls and protections to safeguard data, models, and infrastructure
Leverage AI technologies to automate workflows, accelerate incident response, and scale security operations
Navigate global GRC frameworks to ensure ethical and compliant AI adoption across industries
Defend against AI-driven threats like adversarial attacks, automated malware, and malicious use of generative AI
Integrate AI securely into DevSecOps pipelines and enterprise security strategies.
Dates/Locations:
No Events
Prerequisites: Recommended experience: 3–4 years in IT and 2+ years hands-on cybersecurity; Security+, CySA+, PenTest+, or equivalent recommended
SecAI+ (V1) exam objectives summary
Basic AI concepts related to cybersecurity (17%)
Explain core AI principles and terminology: Machine learning, deep learning, natural language processing, and automation.
Identify AI applications in security: Use cases for AI in threat detection, defense, and security operations.
Recognize AI-driven threats: Automated phishing, polymorphic malware, adversarial machine learning, and malicious use of generative AI.
Securing AI systems (40%)
Implement security controls: Protect AI systems, data, and models using robust technical safeguards.
Secure AI deployment environments: Apply best practices across on-premises, cloud, and hybrid infrastructures.
Mitigate adversarial risks: Defend against attacks targeting AI models, data pipelines, and inference layers.
AI-assisted security (24%)
Enhance detection and response: Use AI-driven tools to identify anomalies, detect threats, and accelerate incident remediation.
Automate security workflows: Integrate AI for event triage, alert correlation, and response orchestration.
Apply AI techniques in operations: Incorporate AI into threat modeling, behavior analysis, and continuous monitoring.
AI governance, risk, and compliance (19%)
Understand regulatory frameworks: Identify global governance requirements and their implications for AI adoption.
Integrate GRC into AI projects: Incorporate governance, risk management, and compliance practices throughout the AI lifecycle.
Ensure responsible AI use: Apply ethical guidelines, legal standards, and industry frameworks such as GDPR and NIST AI RMF.
