Certnexus Training in Belgrade

Artificial intelligence (AI) and machine learning (ML) have become indispensable components of the toolkit for numerous organizations. When leveraged effectively, these technologies provide actionable insights that drive critical decision-making and empower organizations to develop exciting, innovative, and novel products and services. This course demonstrates how to apply various approaches and algorithms to resolve business challenges through AI and ML, adhere to a methodical workflow for developing robust solutions, utilize open-source and commercial tools to create, test, and deploy these solutions, and ensure the protection of user privacy. Each topic area includes hands-on activities to reinforce learning.

Course Objectives: In this course, you will implement AI techniques to address business problems. You will:

• Define a general approach to solve a specific business problem using 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 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.

Designed for professionals aiming to validate a vendor-neutral, cross-industry competency, this course equips learners with the skills to design, deploy, operate, and manage a secure IoT environment.

Target Audience: Ideal for IoT practitioners seeking to enhance their expertise in IoT security and privacy, as well as for individuals preparing for the CertNexus Certified Internet of Things Security Practitioner (CIoTSP) certification and Exam ITS-110.

Objectives:

In this course, you will identify many of the common risks involved in using conventional end-user technology, as well as ways to use it safely, to protect yourself from those risks.

You will:

• Identify security compliance measures.
• Address social engineering attempts.
• Secure devices such as desktops, laptops, tablets, smartphones, and more.
• Use the Internet securely.

Target Student

This course is designed for you as a non-technical end user of computers, mobile devices, networks, and the Internet, to enable you to use technology more securely to minimize digital risks.

This course is also designed for you to prepare for the Certified CyberSAFE credential. You can obtain your Certified CyberSAFE certificate by completing the Certified CyberSAFE credential process on the CHOICE platform following the course presentation.

Breakthroughs in computing and engineering are propelling technological advancement, spanning from blockchain and AI to gene editing and the IoT, presenting significant opportunities for enhancing productivity and human welfare. However, as recent scandals demonstrate, these innovations also introduce novel risks. Technology professionals are under growing pressure to tackle ethical challenges, balancing privacy, accuracy, fairness, and safety. This course offers practical tools for managing ethical risks within emerging data-driven technologies, grounded in theory, regulations, and industry best practices. Participants will acquire the skills needed to navigate ethical dilemmas in their professional roles and organizational contexts.

This program explores network defense and incident response methodologies, tactics, and procedures, aligning with industry standards such as NIST 800-61 r.2 (Computer Security Incident Handling), US-CERT’s NCISP (National Cyber Incident Response Plan), and Presidential Policy Directive (PPD) 41 on Cyber Incident Coordination Policy. It is tailored for candidates responsible for monitoring and detecting security incidents within information systems and networks, as well as executing standardized responses to these events. The course introduces tools, tactics, and procedures to manage cybersecurity risks, identify common threat types, evaluate organizational security, collect and analyze cybersecurity intelligence, and remediate and report incidents in real-time. This program offers a comprehensive methodology for individuals tasked with defending their organization's cybersecurity posture.

The course is designed to help students prepare for the CertNexus CyberSec First Responder (Exam CFR-310) certification. The skills and practices gained here are a significant component of exam preparation. Additionally, this course and the subsequent CFR-310 certification satisfy all personnel requirements for DoD directive 8570.01-M position certification baselines:

• CSSP Analyst

• CSSP Infrastructure Support

• CSSP Incident Responder

• CSSP Auditor

Course Objectives: Participants will learn to understand, assess, and respond to security threats while operating a system and network security analysis platform. Key learning outcomes include:

• Comparing and contrasting various threats and classifying threat profiles

• Explaining the purpose and usage of attack tools and techniques

• Explaining the purpose and usage of post-exploitation tools and tactics

• Explaining the purpose and usage of social engineering tactics

• Conducting ongoing threat landscape research and utilizing data to prepare for incidents, given a specific scenario

• Describing the purpose and characteristics of various data sources

• Utilizing appropriate tools to analyze logs, given a specific scenario

• Using regular expressions to parse log files and locate meaningful data, given a specific scenario

• Using Windows tools to analyze incidents, given a specific scenario

• Using Linux-based tools to analyze incidents, given a specific scenario

• Summarizing methods and tools used for malware analysis

• Analyzing common indicators of potential compromise, given a specific scenario

• Explaining the importance of best practices in incident response preparation

• Executing the incident response process, given a specific scenario

• Explaining concepts unique to forensic analysis

• Explaining general mitigation methods and devices

Target Student: This course is primarily intended for cybersecurity practitioners who are preparing for or currently performing job functions related to protecting information systems by ensuring availability, integrity, authentication, confidentiality, and non-repudiation. It is ideal for roles in federal contracting companies and private sector firms whose mission or strategic objectives involve executing Defensive Cyber Operations (DCO) or DoD Information Network (DODIN) operations and incident handling. The course focuses on the knowledge, ability, and skills necessary to defend these information systems in a cybersecurity context, including protection, detection, analysis, investigation, and response processes.

Furthermore, the course ensures that all members of an IT team—regardless of size, rank, or budget—understand their role in cyber defense, incident response, and incident handling.

The Internet of Things (IoT) offers extensive advantages for industries, energy and utility providers, municipal governments, healthcare sectors, and end consumers. It enables the collection of vast quantities of highly detailed data concerning almost any measurable aspect, including public health and safety, environmental conditions, industrial and agricultural output, as well as energy and utility metrics. Advanced data analysis tools, optimized for the massive volume of data generated by IoT, empower organizations to make rapid, well-informed decisions.

However, implementing IoT systems can be complex and fraught with potential risks. Solutions often require integrating devices and technologies from multiple vendors, demanding a solid grasp of both software and hardware, along with effective integration strategies. Professionals must also address critical risks related to security, privacy, and the safety of individuals whose work and living environments are managed by these systems.

IT professionals frequently lack experience with embedded systems, sensor networks, actuators, real-time systems, and other components typical of IoT. This course provides a foundational understanding of how these components interact with systems that IT professionals typically know well, such as networks, cloud computing platforms, and applications running on servers, desktops, and mobile devices.

Through various case studies and hands-on assembly and configuration of an IoT device within a sensor network, students will learn general strategies for planning, designing, developing, implementing, and maintaining IoT systems. Students will build an IoT device using an ESP8266 microcontroller, implementing 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).

This course is designed for professionals such as software developers, testers, and architects who create software across various programming languages and platforms, including desktop, web, cloud, and mobile environments. It aims to strengthen their ability to deliver high-quality software, with a particular emphasis on security and privacy.