Online or onsite, instructor-led live Certnexus training courses demonstrate through hands-on practice how to implement Certnexus solutions for solving real-world problems.
Certnexus training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Certnexus training can be carried out locally on customer premises in Qatar or in NobleProg corporate training centers in Qatar.
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Certnexus Course Outlines in Qatar
Target Student: This course is designed for IoT practitioners who are looking to improve their skills and knowledge of IoT security and privacy. This course is also designed for students who are seeking the CertNexus Certified Internet of Things Security Practitioner (CIoTSP) certification and who want to prepare for Exam ITS-110.
Course Objectives: In this course, you will implement AI techniques in order to solve business problems. You will:
- Specify a general approach to solve a given business problem that uses applied AI and ML.
- Collect and refine a dataset to prepare it for training and testing.
- Train and tune a machine learning model.
- Finalize a machine learning model and present the results to the appropriate audience.
- Build linear regression models.
- Build classification models.
- Build clustering models.
- Build decision trees and random forests.
- Build support-vector machines (SVMs).
- Build artificial neural networks (ANNs).
- Promote data privacy and ethical practices within AI and ML projects.
Target Student: The skills covered in this course converge on three areas—software development, applied math and statistics, and business analysis. Target students for this course may be strong in one or two or these of these areas and looking to round out their skills in the other areas so they can apply artificial intelligence (AI) systems, particularly machine learning models, to business problems.
So the target student may be a programmer looking to develop additional skills to apply machine learning algorithms to business problems, or a data analyst who already has strong skills in applying math and statistics to business problems, but is looking to develop technology skills related to machine learning. A typical student in this course should have several years of experience with computing technology, including some aptitude in computer programming. This course is also designed to assist students in preparing for the CertNexus® Certified Artificial Intelligence (AI) Practitioner (Exam AIP-110) certification.
This course is designed to assist students in preparing for the CertNexus CyberSec First Responder (Exam CFR-310) certification examination. What you learn and practice in this course can be a significant part of your preparation. In addition, this course and subsequent certification (CFR-310) meets all requirements for personnel requiring DoD directive 8570.01-M position certification baselines:
• CSSP Analyst
• CSSP Infrastructure Support
• CSSP Incident Responder
• CSSP Auditor
Course Objectives: In this course, you will understand, assess and respond to security threats and operate a system and network security analysis platform. You will:
• Compare and contrast various threats and classify threat profile
• Explain the purpose and use of attack tools and technique
• Explain the purpose and use of post exploitation tools and tactic
• Explain the purpose and use of social engineering tactic
• Given a scenario, perform ongoing threat landscape research and use data to prepare for incident
• Explain the purpose and characteristics of various data source
• Given a scenario, use appropriate tools to analyze log
• Given a scenario, use regular expressions to parse log files and locate meaningful data
• Given a scenario, use Windows tools to analyze incidents
• Given a scenario, use Linux-based tools to analyze incidents
• Summarize methods and tools used for malware analysis
• Given a scenario, analyze common indicators of potential compromise
• Explain the importance of best practices in preparation for incident response
• Given a scenario, execute incident response process
• Explain the importance of concepts that are unique to forensic analysis
• Explain general mitigation methods and devices
Target Student: This course is designed primarily for cybersecurity practitioners preparing for or who currently perform job functions related to protecting information systems by ensuring their availability, integrity, authentication, confidentiality, and non-repudiation. It is ideal for those roles within federal contracting companies, and private sector firms who whose mission or strategic objectives require the execution of Defensive Cyber Operations (DCO) or DoD Information Network (DODIN) operation and incident handling. This course focuses on the knowledge, ability, and skills necessary to provide for the defense of those information systems in a cybersecurity context, including protection, detection, analysis, investigation, and response processes.
In addition, the course ensures that all members of an IT team—regardless of size, rank or budget— understand their role in the cyber defense, incident response, and incident handling process.
But putting IoT systems into place can be a complicated proposition, and fraught with hazards. Solutions may involve devices and technologies from many different vendors, requiring a good understanding of software and hardware and strategies to integrate them, as well as the risks associated with security, privacy, and the safety of those whose working and living environments are managed by these systems.
IT professionals often have little or no experience working with embedded systems, sensor networks, actuators, real-time systems, and other components that are common to IoT, so this course provides a foundation for understanding how these components work with other systems that IT professionals typically have more experience working with—such as networks, cloud computing, and applications running on servers, desktop computers, and mobile devices.
In this course, students will learn general strategies for planning, designing, developing, implementing, and maintaining an IoT system through various case studies and by assembling and configuring an IoT device to work in a sensor network. Students will create an IoT device based on an ESP8266 microcontroller, implementing various common IoT features, such as analog and digital sensors, a web-based interface, MQTT messaging, and data encryption.
Course Objectives: In this course, you will learn how to apply Internet of Things technologies to solve real-world problems. You will:
• Plan an IoT implementation.
• Construct and program an IoT device.
• Communicate with an IoT device using wired and wireless connections.
• Process sensor input and control an actuator on an IoT device.
• Manage security, privacy, and safety risks on IoT projects.
• Manage an IoT prototyping and development project throughout the development lifecycle.
Target Student: This course is designed for IT professionals with baseline skills in computer hardware, software support, and development who want to learn how to design, develop, implement, operate, and manage Internet of Things devices and related systems. The student is interested in learning more about embedded systems, microcontroller programming, IoT security, and the development life cycle for IoT projects.
While students will gain hands-on experience assembling a prototype IoT device and using software development tools, these activities are closely guided, so previous experience in electronics assembly and programming are not required. This course prepares students for taking the CertNexus Certified Internet of Things (IoT) Practitioner (Exam ITP-110).