Course Overview:

PERL programmers need a clear roadmap for improving their skills. Intermediate PERL teaches a working knowledge of PERL's objects, references, and modules — all of which makes the language so versatile and effective. This class offers a thorough introduction to intermediate programming in PERL. Topics include packages and namespaces, references and scoping, manipulating complex data structures, writing and using modules, package implementation, and using CPAN.

Attendees to P-315: Intermediate PERL Programming will receive TechNow approved course materials and expert instruction.

Dates/Locations:

No Events

Duration: 5 Days

Course Objectives:

  • Packages and namespaces
  • References and scoping
  • Manipulating complex data structures
  • Object-oriented programming
  • Writing and using modules
  • Testing PERL code
  • Contributing to CPAN

Prerequisites:

 

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User: J Masters

Instructor comments: Instructor kept it interesting and brought a wealth of knowledge to the classroom environment. Kept a good pace and provided relevant examples.


 

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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.
 

Course Overview:

The introduction to SQL Databases training course is designed to train the learners on the fundamentals of database concepts. You will not only learn about the different types of databases, the languages and designs as well as describe important database concepts using SQL Server 2016. Anyone who is moving into a database role will benefit from taking this course.

 

Attendees to MS-5002: Introduction to SQL Databases will receive TechNow approved course materials and expert instruction.

Date/Locations:

No Events

Course Duration: 2 days

 

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Course Overview:

In this course, the students will design various data platform technologies into solutions that are in line with business and technical requirements. This can include on-premises, cloud, and hybrid data scenarios which incorporate relational, NoSQL, or Data Warehouse data. They will also learn how to design process architectures using a range of technologies for both streaming and batch data. The students will also explore how to design data security, including data access, data policies, and standards. They will also design Azure data solutions, which includes the optimization, availability, and disaster recovery of big data, batch processing, and streaming data solutions.

TechNow has worked worldwide enterprise infrastructures for over 20 years and has developed demos and labs to exemplify the techniques required to demonstrate cloud technologies and to effectively manage security in the cloud environment.

Attendees to DP-201: Designing an Azure Data Solution will receive TechNow approved course materials and expert instruction.

Date/Locations:

No Events

Course Duration: 3 days

Course Outline:

  • Data Platform Architecture Considerations
  • Azure Batch Processing Reference Architectures
  • Azure Real-Time Reference Architectures
  • Data Platform Security Design Considerations
  • Designing for Resiliency and Scale
  • Design for Efficiency and Operations

Prerequisites :

      • In addition to their professional experience, students who take this training should have technical knowledge equivalent to the following courses:
      • AZ-900: Microsoft Azure Fundamentals
      • DP-200: Implementing an Azure Data Solution

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