TechNow has been training IT, programming, and Cyber Security for over 28 years. Artificial Intelligence skills are being developed across many enterprises.
Here is our list of Artificial Intelligence and Machine Learning related courses.
TechNow has been training IT, programming, and Cyber Security for over 28 years. To stay competitive and to adequately secure an enterprise, organizations need to move towards the DevOps Model. DevOps breaks down barriers between the developer and operations teams to improve collaboration and communication.
DevOps is radically changing the way organizations design, build, deploy, and operate online systems. Development and Operations teams come together to move requirements through a continuous workflow.
DevOps leaders deploy hundreds of changes every day, utilizing Continuous Integration and Continuous Delivery to leave their competitors behind. As DevOps becomes commonplace, organizations need to evolve their security practices to the DevOps Model.
Here is our list of DevOps related courses.
Course Overview:
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.
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Course Overview:
CompTIA Cloud Essentials+ is for both IT and non-technical professionals who require the essential business acumen needed to make informed cloud service decisions. Cloud Essentials is a vendor-neutral credential designed to validate the candidate has an understanding of basic terms and definitions of cloud computing along with the different processes involved in the successful adoption of cloud computing and its implications for organizations’ use.
TechNow is a CompTIA partner and uses official CompTIA Cloud Essentials+ curriculum.
Attendees to CT-213: Cloud Essentials+ will receive TechNow approved course materials and expert instruction.
Date/Locations:
No Events
Course Duration: 3 days
Course Objectives:
- Domain 1 : Cloud Concepts
- Understand cloud principles
- Identify cloud networking concepts & storage techniques
- Understand cloud design aspects
- Domain 2: Business Principles of Cloud Environments
- Identify and employ appropriate cloud assessments like feasibility studies, benchmarking, or gap analysis
- Highlight key business aspects of cloud vendor relation adoption, and comprehend cloud migration approaches
- Domain 3: Management and Technical Operations
- Explain aspects of operating within the cloud, such as data management or optimization
- Understand the role of DevOps in cloud environments, like API integration or provisioning
- Domain 4: Governance, Risk, Compliance and Security for the Cloud
- Understand risk management and response concepts related to cloud services and identify the importance and impacts of compliance in the cloud, such as regulatory concerns or international standards.
Course Prerequisites:
- CompTIA recommends that a candidate have at least 6 months of experience in an IT environment, with direct involvement in IT-related tasks responsibilities and/or decision making.
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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.