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AI+ Data Practitioner™
's-Hertogenbosch
ma 12 okt. 2026
Formerly known as AI+ Data™
Mastering AI, Maximizing Data: Your Path to Innovation
* Core Concepts Covered: Data Science foundations, Python, Statistics, and Data Wrangling
* Advanced Topics: Dive into Generative AI, Machine Learning, and Predictive Analytics
* Capstone Application: Solve real-world problems like employee attrition with AI
* Career Readiness: Develop skills for AI-driven data science roles with hands-on mentorship
Course Overview
* Course Introduction Preview Module 1: Foundations of Data Science
* 1.1 Introduction to Data Science
* 1.2 Data Science Life Cycle
* 1.3 Applications of Data Science Module 2: Foundations of Statistics
* 2.1 Basic Concepts of Statistics
* 2.2 Probability Theory
* 2.3 Statistical Inference Module 3: Data Sources and Types
* 3.1 Types of Data
* 3.2 Data Sources
* 3.3 Data Storage Technologies Module 4: Programming Skills for Data Science
* 4.1 Introduction to Python for Data Science
* 4.2 Introduction to R for Data Science Module 5: Data Wrangling and Preprocessing
* 5.1 Data Imputation Techniques
* 5.2 Handling Outliers and Data Transformation Module 6: Exploratory Data Analysis (EDA)
* 6.1 Introduction to EDA
* 6.2 Data Visualization Module 7: Generative AI Tools for Deriving Insights
* 7.1 Introduction to Generative AI Tools
* 7.2 Applications of Generative AI Module 8: Machine Learning
* 8.1 Introduction to Supervised Learning Algorithms
* 8.2 Introduction to Unsupervised Learning
* 8.3 Different Algorithms for Clustering
* 8.4 Association Rule Learning with Implementation Module 9: Advance Machine Learning
* 9.1 Ensemble Learning Techniques
* 9.2 Dimensionality Reduction
* 9.3 Advanced Optimization Techniques Module 10: Data-Driven Decision-Making
* 10.1 Introduction to Data-Driven Decision Making
* 10.2 Open Source Tools for Data-Driven Decision Making
* 10.3 Deriving Data-Driven Insights from Sales Dataset Module 11: Data Storytelling
* 11.1 Understanding the Power of Data Storytelling
* 11.2 Identifying Use Cases and Business Relevance
* 11.3 Crafting Compelling Narratives
* 11.4 Visualizing Data for Impact Module 12: Capstone Project - Employee Attrition Prediction
* 12.1 Project Introduction and Problem Statement
* 12.2 Data Collection and Preparation
* 12.3 Data Analysis and Modeling
* 12.4 Data Storytelling and Presentation Optional Module: AI Agents for Data Analysis
* 1. Understanding AI Agents
* 2. Case Studies
* 3. Hands-On Practice with AI Agents Tools you will explore
* Google Colab
* MLflow
* Alteryx
* KNIME
Online proctored exam included, with one free retake.
Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam
Access to all materials and exams is provided for 365 days after delivery.
Instructor-led OR Self-paced course + Official exam + Digital badge
€3.450
Klassikaal
max 12
5 dagen
AI+ Data Practitioner™ eLearning
Formerly known as AI+ Data™
Mastering AI, Maximizing Data: Your Path to Innovation
* Core Concepts Covered: Data Science foundations, Python, Statistics, and Data Wrangling
* Advanced Topics: Dive into Generative AI, Machine Learning, and Predictive Analytics
* Capstone Application: Solve real-world problems like employee attrition with AI
* Career Readiness: Develop skills for AI-driven data science roles with hands-on mentorship
Course Overview
* Course Introduction Preview Module 1: Foundations of Data Science
* 1.1 Introduction to Data Science
* 1.2 Data Science Life Cycle
* 1.3 Applications of Data Science Module 2: Foundations of Statistics
* 2.1 Basic Concepts of Statistics
* 2.2 Probability Theory
* 2.3 Statistical Inference Module 3: Data Sources and Types
* 3.1 Types of Data
* 3.2 Data Sources
* 3.3 Data Storage Technologies Module 4: Programming Skills for Data Science
* 4.1 Introduction to Python for Data Science
* 4.2 Introduction to R for Data Science Module 5: Data Wrangling and Preprocessing
* 5.1 Data Imputation Techniques
* 5.2 Handling Outliers and Data Transformation Module 6: Exploratory Data Analysis (EDA)
* 6.1 Introduction to EDA
* 6.2 Data Visualization Module 7: Generative AI Tools for Deriving Insights
* 7.1 Introduction to Generative AI Tools
* 7.2 Applications of Generative AI Module 8: Machine Learning
* 8.1 Introduction to Supervised Learning Algorithms
* 8.2 Introduction to Unsupervised Learning
* 8.3 Different Algorithms for Clustering
* 8.4 Association Rule Learning with Implementation Module 9: Advance Machine Learning
* 9.1 Ensemble Learning Techniques
* 9.2 Dimensionality Reduction
* 9.3 Advanced Optimization Techniques Module 10: Data-Driven Decision-Making
* 10.1 Introduction to Data-Driven Decision Making
* 10.2 Open Source Tools for Data-Driven Decision Making
* 10.3 Deriving Data-Driven Insights from Sales Dataset Module 11: Data Storytelling
* 11.1 Understanding the Power of Data Storytelling
* 11.2 Identifying Use Cases and Business Relevance
* 11.3 Crafting Compelling Narratives
* 11.4 Visualizing Data for Impact Module 12: Capstone Project - Employee Attrition Prediction
* 12.1 Project Introduction and Problem Statement
* 12.2 Data Collection and Preparation
* 12.3 Data Analysis and Modeling
* 12.4 Data Storytelling and Presentation Optional Module: AI Agents for Data Analysis
* 1. Understanding AI Agents
* 2. Case Studies
* 3. Hands-On Practice with AI Agents Tools you will explore
* Google Colab
* MLflow
* Alteryx
* KNIME
Online proctored exam included, with one free retake.
Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam
Access to all materials and exams is provided for 365 days after delivery.
Instructor-led OR Self-paced course + Official exam + Digital badge
€510
E-Learning
max 999
5 dagen
AI+ Security Practitioner™ eLearning
Formerly known as AI+ Security Level 1™
Empowering Cybersecurity with AI
This certification validates foundational knowledge of AI-driven cybersecurity concepts and assesses understanding of security principles, threats, and controls. The exam evaluates competency in applying core cybersecurity knowledge within AI-enabled environments.
Module 1: Computing, Linux, and Operating System Foundations
* You will learn about computer systems, operating systems, Linux administration, file systems, commands, user management, permissions, authentication, and access control concepts. Module 2: Networking Fundamentals and Traffic Analysis
* You will learn networking concepts, IP addressing, protocols, TCP/IP communication, DNS, network security, traffic analysis, firewalls, IDS/IPS, and VPN technologies. Module 3: Python for Security and Automation
* You will learn Python programming fundamentals and how to use scripting for security automation, log analysis, data processing, and efficient security workflows. Module 4: Cybersecurity Foundations and Threat Landscape
* You will learn cybersecurity principles, risks, vulnerabilities, attack surfaces, security controls, common cyber threats, and industry security frameworks. Module 5: Cryptography, Authentication, and Identity Security
* You will learn encryption, hashing, digital signatures, TLS security, authentication methods, identity management, access controls, and identity protection practices. Module 6: Introduction to Artificial Intelligence and Machine Learning
* You will learn AI, ML, and Deep Learning fundamentals, learning approaches, ML lifecycle, datasets, model evaluation, and AI applications in cybersecurity. Module 7: AI Applied to Security Detection and Threat Hunting
* You will learn AI-based threat detection, behavioral analytics, anomaly detection, threat intelligence, threat hunting, MITRE ATT&CK mapping, and AI-assisted SOC operations. Module 8: AI Security, LLM Security, and Responsible AI
* You will learn LLMs, Generative AI, AI copilots, RAG, OWASP LLM security risks, AI vulnerabilities, governance, and responsible AI practices. Module 9: Offensive Security for AI Systems
* You will learn AI threat modeling, attack surfaces, adversarial attacks, STRIDE methodology, AI vulnerabilities, red teaming, and security testing approaches. Module 10: Security Operations, Incident Response, and Malware Analysis
* You will learn about SOC operations, SIEM concepts, incident response, malware analysis, threat investigation, and AI-assisted security operations. Module 11: Governance, Compliance, and Ethical AI Security
* You will learn security governance, risk management, AI governance, compliance, privacy principles, and responsible AI security practices. Module 12: Capstone Project — AI-Driven Security Operations and Defense
* You will apply cybersecurity skills through an end-to-end AI security project involving threat analysis, AI risk assessment, incident response, and professional security reporting. Tools you will explore
* Scikit-learn
* TensorFlow
* PyTorch
* Kali Linux
* Wireshark
* Nmap
* Wazuh
* Splunk
* OWASP ZAP
Online proctored exam included, with one free retake.
Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam
Access to all materials and exams is provided for 365 days after delivery.
Instructor-led OR Self-paced course + Official exam + Digital badge
€200
E-Learning
max 999
1 dag
AI+ Security Expert™ eLearning
Formerly known as AI+ Security Level 2™
Protect and Secure: Leverage Intelligent AI Solutions
This certification validates intermediate-level knowledge of AI-driven cybersecurity concepts and assesses competency in applying security controls, risk management practices, and AI-enabled threat detection techniques. The exam evaluates understanding of advanced security principles within AI-augmented environments.
Module 1: Introduction to AI and Cybersecurity
* You will learn AI and cybersecurity fundamentals, AI-driven threat detection, vulnerability management, ethical considerations, regulatory requirements, and resilient security strategies. Module 2: Python Programming for AI and Cybersecurity Professionals
* You will learn Python programming for security automation, data analysis, AI scripting, visualization, and developing cybersecurity tools. Module 3: Applications of Machine Learning in Cybersecurity
* You will explore ML-based anomaly detection, behavior analysis, predictive threat identification, data protection, and advanced cybersecurity applications. Module 4: Detection of Email Threats with AI
* You will learn AI-powered email security, phishing detection, deep learning models, automation techniques, and email threat response solutions. Module 5: AI Algorithm for Malware Threat Detection
* You will learn AI-based malware detection, neural networks, model development, real-time mitigation, and malware analysis techniques. Module 6: AI Infrastructure and Deployment
* You will explore AI-based network anomaly detection, model implementation, deployment strategies, and challenges in handling advanced threats. Module 7: User Authentication Security with AI
* You will learn AI-driven authentication, biometric recognition, behavioral analysis, adaptive security controls, and emerging authentication trends. Module 8: GAN for Cyber Security
* You will explore GAN applications in cybersecurity, including threat simulation, synthetic attack generation, vulnerability detection, and defense improvement. Module 9: Penetration Testing with Artificial Intelligence
* You will learn AI-enhanced penetration testing, cyberattack simulation, automated vulnerability identification, and improved security assessment techniques. Module 10: Capstone Project
* You will apply AI cybersecurity concepts through real-world projects involving anomaly detection, email security, IoT protection, behavioral biometrics, and threat intelligence. Tools you will explore
* CrowdStrike Falcon
* Darktrace Enterprise
* Vectra Cognito
* SentinelOne Singularity
* Cylance PROTECT
* IBM QRadar Advisor with Watson
* Exabeam Advanced Analytics
* Rapid7 InsightIDR
* Cynet 360
* Fortinet FortiAI
Online proctored exam included, with one free retake.
Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam
Access to all materials and exams is provided for 365 days after delivery.
Instructor-led OR Self-paced course + Official exam + Digital badge
€510
E-Learning
max 999
5 dagen
AI+ Security Strategist™ eLearning
Formerly known as AI+ Security Level 3™
Validate Your Expertise in Cybersecurity
This certification validates advanced-level expertise in AI-driven cybersecurity strategy, governance, and risk management. The exam assesses deep knowledge of advanced security architectures, AI-enabled threat intelligence, and strategic security decision-making within complex enterprise environments.
Module 1: Foundations of AI and ML for Security Engineering
* This module equips you to implement cutting-edge AI-driven security solutions. You’ll explore core algorithms like neural networks, advanced NLP techniques, and deep learning models to analyze security logs. The module also guides you on designing AI pipelines, managing imbalanced datasets, and mitigating adversarial threats, ensuring that your security systems remain adaptive and robust against evolving cyber risks. Module 2: ML for Threat Detection and Response
* This module provides practical expertise in applying supervised and unsupervised learning methods for tasks such as malware classification, anomaly detection, and real-time threat response. You’ll also learn to build advanced pipelines, optimize AI models, and use tools like Apache Kafka and Spark for scalable real-time solutions. Module 3: Deep Learning for Security Applications
* In this module, you’ll gain proficiency in implementing CNNs, RNNs, and hybrid models for network traffic classification, phishing detection, and intrusion analysis. Additionally, you’ll explore autoencoders for anomaly detection and adversarial training methods to strengthen defenses against manipulated inputs. Module 4: Adversarial AI in Security
* This module explores the strategies for crafting secure AI systems, including adversarial training, ensemble methods, and red teaming. You’ll also explore tools for simulating attacks and designing architectures that resist adversarial inputs while maintaining transparency and trust. Module 5: AI in Network Security
* This module teaches you to implement AI-powered IDS, anomaly detection models, and zero-trust architectures. With case studies and hands-on projects, you’ll develop skills in integrating AI into next-generation firewalls and optimizing network security for high-throughput environments. Module 6: AI in Endpoint Security
* In this module, you’ll learn to build AI-based malware detection systems, optimize models for polymorphic threats, and leverage ML for anomaly detection on endpoints. The content also covers securing IoT devices and implementing lightweight AI solutions for resource-constrained environments. Module 7: Secure AI System Engineering
* This module provides expertise in designing robust AI pipelines, incorporating cryptographic techniques, and optimizing models for real-time security. You’ll also explore frameworks for ensuring explainability, scalability, and compliance with data protection regulations. Module 8: AI for Cloud and Container Security
* This module equips you to build AI systems for cloud security, integrate tools into container orchestration platforms like Kubernetes, and deploy AI-driven solutions for serverless architectures. You’ll also explore DevSecOps practices and advanced security testing methods. Module 9: AI and Blockchain for Security
* This module offers insights into integrating AI with blockchain for transaction security, optimizing consensus mechanisms, and safeguarding smart contracts. Practical case studies showcase applications in cryptocurrency exchanges and supply chain management. Module 10: AI in Identity and Access Management (IAM)
* This module focuses on automating role-based access controls, detecting unauthorized access, and implementing AI-driven MFA systems. You’ll also explore real-world applications of reinforcement learning and AI-based fraud detection in IAM scenarios. Module 11: AI for Physical and IoT Security
* This module covers AI solutions for securing smart cities, industrial IoT, and autonomous vehicles. You’ll also learn about federated learning for decentralized security and techniques for safeguarding smart home devices against unauthorized access. Module 12: Capstone Project – Engineering AI Security Systems
* This module guides you through every step, from defining project goals and selecting datasets to integrating AI models into existing infrastructures. You’ll gain hands-on expertise in creating scalable, adaptive, and effective security solutions. Tools you will explore
* Splunk UBA
* Microsoft Defender for Endpoint
* Microsoft Azure AD Conditional Access
* Adversarial Robustness Toolkit (ART)
* CrowdStrike Falcon XDR
* Palo Alto Cortex XDR
* Darktrace Enterprise
* Vectra for Cloud
* Fortinet AI Cloud Security
* Semgrep
Online proctored exam included, with one free retake.
Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam
Access to all materials and exams is provided for 365 days after delivery.
Instructor-led OR Self-paced course + Official exam + Digital badge
€510
E-Learning
max 999
5 dagen
AI+ Ethical Hacker Practitioner™
Formerly known as AI+ Ethical Hacker™
Protect Digital Landscapes: Harness AI-Enhanced Technologies
The AI+ Ethical Hacker Practitioner™ certification validates knowledge of the intersection of cybersecurity and artificial intelligence, a pivotal juncture in an era of rapid technological progress. Designed for cybersecurity professionals and ethical hacking practitioners, it assesses comprehensive knowledge of AI’s impact on digital offense and defense strategies. Unlike conventional ethical hacking certifications, this certification validates competency in applying AI techniques to enhance cybersecurity approaches. It is intended for professionals seeking to validate expertise in the integration of advanced AI methods with ethical hacking practices in a rapidly evolving digital landscape.
Module 1: Foundation of Ethical Hacking Using AI
* You will learn ethical hacking fundamentals, reconnaissance, scanning, penetration testing, hacking phases, legal compliance, and responsible cybersecurity practices. Module 2: Introduction to AI in Ethical Hacking
* You will learn the role of ethical hacking in cybersecurity, AI applications, penetration testing practices, compliance requirements, and risk management approaches. Module 3: AI Tools and Technologies in Ethical Hacking
* You will explore AI-based threat detection, machine learning frameworks, behavioral analytics, predictive analysis, anomaly detection, and automated vulnerability identification. Module 4: AI-Driven Reconnaissance Techniques
* You will learn AI-powered OSINT, network scanning, vulnerability discovery, social engineering detection, and ML-based analysis of open-source intelligence. Module 5: AI in Vulnerability Assessment and Penetration Testing
* You will learn AI-enhanced vulnerability scanning, penetration testing, threat prioritization, DAST, fuzz testing, risk modeling, and automated security reporting. Module 6: Machine Learning for Threat Analysis
* You will explore supervised, unsupervised, and reinforcement learning, NLP for threat intelligence, feature engineering, ensemble learning, and explainable AI. Module 7: Behavioral Analysis and Anomaly Detection for System Hacking
* You will learn behavioral biometrics, user behavior analytics, network monitoring, endpoint analysis, anomaly detection, and AI-driven threat hunting. Module 8: AI Enabled Incident Response Systems
* You will learn AI-powered threat triage, incident classification, predictive analytics, threat intelligence integration, and automated response techniques. Module 9: AI for Identity and Access Management (IAM)
* You will explore AI-based authentication, biometric security, anomaly detection, dynamic access controls, and privacy considerations in IAM. Module 10: Securing AI Systems
* You will learn AI system protection, adversarial attack defense, secure model training, data privacy, explainability, monitoring, and AI security architecture. Module 11: Ethics in AI and Cybersecurity
* You will learn ethical AI practices, privacy protection, fairness, transparency, explainability, AI bias management, and cybersecurity compliance principles. Module 12: Capstone Project
* You will apply AI cybersecurity concepts through real-world case studies covering threat detection, vulnerability assessment, penetration testing, IAM, and encryption security. Tools you will explore
* Acunetix
* Wapiti
* Nessus
* OWASP ZAP
* HackerGPT
* Cobalt Strike
* Shodan
* Wazuh
* Sumo Logic
* YARA Rules
Online proctored exam included, with one free retake.
Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam
Access to all materials and exams is provided for 365 days after delivery.
Instructor-led OR Self-paced course + Official exam + Digital badge
€3.450
Klassikaal
max 12
5 dagen
AI+ Ethical Hacker Practitioner™ eLearning
Formerly known as AI+ Ethical Hacker™
Protect Digital Landscapes: Harness AI-Enhanced Technologies
The AI+ Ethical Hacker Practitioner™ certification validates knowledge of the intersection of cybersecurity and artificial intelligence, a pivotal juncture in an era of rapid technological progress. Designed for cybersecurity professionals and ethical hacking practitioners, it assesses comprehensive knowledge of AI’s impact on digital offense and defense strategies. Unlike conventional ethical hacking certifications, this certification validates competency in applying AI techniques to enhance cybersecurity approaches. It is intended for professionals seeking to validate expertise in the integration of advanced AI methods with ethical hacking practices in a rapidly evolving digital landscape.
Module 1: Foundation of Ethical Hacking Using AI
* You will learn ethical hacking fundamentals, reconnaissance, scanning, penetration testing, hacking phases, legal compliance, and responsible cybersecurity practices. Module 2: Introduction to AI in Ethical Hacking
* You will learn the role of ethical hacking in cybersecurity, AI applications, penetration testing practices, compliance requirements, and risk management approaches. Module 3: AI Tools and Technologies in Ethical Hacking
* You will explore AI-based threat detection, machine learning frameworks, behavioral analytics, predictive analysis, anomaly detection, and automated vulnerability identification. Module 4: AI-Driven Reconnaissance Techniques
* You will learn AI-powered OSINT, network scanning, vulnerability discovery, social engineering detection, and ML-based analysis of open-source intelligence. Module 5: AI in Vulnerability Assessment and Penetration Testing
* You will learn AI-enhanced vulnerability scanning, penetration testing, threat prioritization, DAST, fuzz testing, risk modeling, and automated security reporting. Module 6: Machine Learning for Threat Analysis
* You will explore supervised, unsupervised, and reinforcement learning, NLP for threat intelligence, feature engineering, ensemble learning, and explainable AI. Module 7: Behavioral Analysis and Anomaly Detection for System Hacking
* You will learn behavioral biometrics, user behavior analytics, network monitoring, endpoint analysis, anomaly detection, and AI-driven threat hunting. Module 8: AI Enabled Incident Response Systems
* You will learn AI-powered threat triage, incident classification, predictive analytics, threat intelligence integration, and automated response techniques. Module 9: AI for Identity and Access Management (IAM)
* You will explore AI-based authentication, biometric security, anomaly detection, dynamic access controls, and privacy considerations in IAM. Module 10: Securing AI Systems
* You will learn AI system protection, adversarial attack defense, secure model training, data privacy, explainability, monitoring, and AI security architecture. Module 11: Ethics in AI and Cybersecurity
* You will learn ethical AI practices, privacy protection, fairness, transparency, explainability, AI bias management, and cybersecurity compliance principles. Module 12: Capstone Project
* You will apply AI cybersecurity concepts through real-world case studies covering threat detection, vulnerability assessment, penetration testing, IAM, and encryption security. Tools you will explore
* Acunetix
* Wapiti
* Nessus
* OWASP ZAP
* HackerGPT
* Cobalt Strike
* Shodan
* Wazuh
* Sumo Logic
* YARA Rules
Online proctored exam included, with one free retake.
Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam
Access to all materials and exams is provided for 365 days after delivery.
Instructor-led OR Self-paced course + Official exam + Digital badge
€510
E-Learning
max 999
5 dagen
AI+ Security Compliance Practitioner™ eLearning
Formerly known as AI+ Security Compliance™
Empowering Compliance Through AI
The AI+ Security Compliance Practitioner™ is an advanced certification that merges the fundamental principles of cybersecurity compliance with the transformative power of artificial intelligence (AI). Building on the CISSP framework, this certification focuses on how AI can enhance compliance processes, improve risk management, and ensure robust security measures in alignment with regulatory standards. This certification validates knowledge of core principles of cyber security compliance, and assesses understanding of how AI can enhance security posture. This certification structure integrates comprehensive cybersecurity compliance principles with advanced AI applications, validating candidate competency in ensuring compliance and enhancing security through AI technologies.
Module 1: Introduction to Cybersecurity Compliance and AI
* You will learn cybersecurity compliance principles, international standards such as GDPR and ISO, compliance program development, risk assessments, and how AI improves compliance monitoring and risk management. Module 2: Security and Risk Management with AI
* You will learn risk management frameworks, risk assessment techniques, AI-driven risk identification, predictive analytics, incident response, and compliance-focused risk mitigation strategies. Module 3: Asset Security and AI for Compliance
* You will learn AI-based data classification, encryption, privacy-preserving techniques, data anonymization, automated asset discovery, and AI-driven asset monitoring. Module 4: Security Architecture and Engineering with AI
* You will learn AI-driven security architecture, predictive threat modeling, cryptography enhancements, vulnerability assessment, penetration testing, and AI-based access control models. Module 5: Communication and Network Security with AI
* You will learn network security fundamentals, AI-based traffic analysis, intrusion detection, threat hunting, AI-driven firewalls, and automated compliance reporting. Module 6: Identity and Access Management (IAM) with AI
* You will learn authentication, authorization, identity lifecycle management, AI-enhanced biometric authentication, multi-factor authentication, and dynamic access control. Module 7: Security Assessment and Incident Response with AI
* You will learn penetration testing, vulnerability assessment, AI-powered security testing, incident response lifecycle, automated detection, and compliance audits. Module 8: Security Operations with AI
* You will learn SOC operations, AI-assisted threat detection, security orchestration, data protection, disaster recovery planning, and automated security workflows. Module 9: Software Development Security and Audit with AI
* You will learn secure coding practices, AI-based code analysis, vulnerability discovery, application security testing, CI/CD security, threat modeling, and security audits. Module 10: Future Trends in AI and Cybersecurity Compliance
* You will learn emerging AI technologies, predictive threat intelligence, AI governance, ethical AI practices, quantum computing impacts, and future cybersecurity compliance trends. Tools you will explore
* Checkmarx
* Snyk
* Nmap
* Wireshark
* Burp Suite
* Nessus
* Splunk
* IBM QRadar
* Palo Alto Cortex XSOAR
* Microsoft Sentinel
Online proctored exam included, with one free retake.
Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam
Access to all materials and exams is provided for 365 days after delivery.
Instructor-led OR Self-paced course + Official exam + Digital badge
€510
E-Learning
max 999
5 dagen
AI+ Telecommunications Practitioner™
Formerly known as AI+ Telecommunications™
AI in Telecommunications: Redefining the Future of Seamless Connectivity
* Foundational Insights: Explore AI technologies enhancing telecom networks, from predictive maintenance to network optimization and customer service automation.
* Advanced Applications: Master AI in 5G deployment, anomaly detection, and real-time resource management for improved network performance.
* Specialized Expertise: Learn AI solutions for cybersecurity, fraud detection, and efficient IoT integration to ensure network reliability.
* Capstone Project: Develop AI-driven solutions for real-world telecom challenges like network optimization and intelligent service delivery.
Module 1: Introduction to AI in Telecommunications
* 1.1 AI Fundamentals in Telecommunications
* 1.2 AI Technologies for Telecom
* 1.3 Emerging Trends in AI for Telecommunications
* 1.4 Case Study
* 1.5 Hands-on Module 2: Data Engineering for Telecom AI
* 2.1 Foundation of Telecom Data Engineering
* 2.2 Designing and Managing the Telecom Data Pipeline
* 2.3 Data Engineering tools and Technology
* 2.4 Case Study: SK Telecom’s Big Data Analytics with Metatron Discovery
* 2.5 Hands on Exercise Module 3: AI for 5G Networks
* 3.1 Introduction to 5G
* 3.2 AI Applications in 5G
* 3.3 Enhancing Network Management with AI
* 3.4 Case Study
* 3.5 Hands-on Module 4: AI in Network Optimization
* 4.1 Predictive Network Management
* 4.2 Performance Enhancement Techniques
* 4.3 Traffic Management Strategies
* 4.4 Case Study
* 4.5 Hands-on Module 5: AI in Network Security
* 5.1 Security Threats in Telecom
* 5.2 AI Security Solutions
* 5.3 Advanced Security Frameworks
* 5.4 Case Study
* 5.5 Hands-on Module 6: Enhancing Customer Experience with AI
* 6.1 Personalized Customer Service
* 6.2 Service Quality Improvement
* 6.3 Enhancing Customer Engagement
* 6.4 Case Study
* 6.5 Hands-on Module 7: IoT Integration with Telecommunications
* 7.1 IoT Fundamentals
* 7.2 Managing IoT Security Challenges
* 7.3 Enhancing Operational Efficiency with IoT
* 7.4 Case Study
* 7.5 Hands-on Module 8: AI-Integrated Network Operations Centers (NOC)
* 8.1 Transitioning to AI-driven NOCs
* 8.2 Automating escalations and root cause analyses
* 8.3 Closed-loop automation with AI and SDN integration
* 8.4 Designing AI-ready network architectures
* 8.5 Change management strategies for AI rollouts in operations
* 8.6 Case Study: Implementation of AI assistants in NOCs Module 9: Ethical Considerations in Artificial Intelligence
* 9.1 Ethical Implications of Using Artificial Intelligence
* 9.2 Responsible Deployment Practices
* 9.3 Emerging Trends and Challenges
* 9.4 Case Study
* 9.5 Hands-on Module 10: Capstone Project
Tools you will explore
* TensorFlow
* Keras
* Matplotlib
Online proctored exam included, with one free retake.
Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam
Access to all materials and exams is provided for 365 days after delivery.
Instructor-led OR Self-paced course + Official exam + Digital badge
€3.450
Klassikaal
max 12
5 dagen
AI+ Telecommunications Practitioner™ eLearning
Formerly known as AI+ Telecommunications™
AI in Telecommunications: Redefining the Future of Seamless Connectivity
* Foundational Insights: Explore AI technologies enhancing telecom networks, from predictive maintenance to network optimization and customer service automation.
* Advanced Applications: Master AI in 5G deployment, anomaly detection, and real-time resource management for improved network performance.
* Specialized Expertise: Learn AI solutions for cybersecurity, fraud detection, and efficient IoT integration to ensure network reliability.
* Capstone Project: Develop AI-driven solutions for real-world telecom challenges like network optimization and intelligent service delivery.
Module 1: Introduction to AI in Telecommunications
* 1.1 AI Fundamentals in Telecommunications
* 1.2 AI Technologies for Telecom
* 1.3 Emerging Trends in AI for Telecommunications
* 1.4 Case Study
* 1.5 Hands-on Module 2: Data Engineering for Telecom AI
* 2.1 Foundation of Telecom Data Engineering
* 2.2 Designing and Managing the Telecom Data Pipeline
* 2.3 Data Engineering tools and Technology
* 2.4 Case Study: SK Telecom’s Big Data Analytics with Metatron Discovery
* 2.5 Hands on Exercise Module 3: AI for 5G Networks
* 3.1 Introduction to 5G
* 3.2 AI Applications in 5G
* 3.3 Enhancing Network Management with AI
* 3.4 Case Study
* 3.5 Hands-on Module 4: AI in Network Optimization
* 4.1 Predictive Network Management
* 4.2 Performance Enhancement Techniques
* 4.3 Traffic Management Strategies
* 4.4 Case Study
* 4.5 Hands-on Module 5: AI in Network Security
* 5.1 Security Threats in Telecom
* 5.2 AI Security Solutions
* 5.3 Advanced Security Frameworks
* 5.4 Case Study
* 5.5 Hands-on Module 6: Enhancing Customer Experience with AI
* 6.1 Personalized Customer Service
* 6.2 Service Quality Improvement
* 6.3 Enhancing Customer Engagement
* 6.4 Case Study
* 6.5 Hands-on Module 7: IoT Integration with Telecommunications
* 7.1 IoT Fundamentals
* 7.2 Managing IoT Security Challenges
* 7.3 Enhancing Operational Efficiency with IoT
* 7.4 Case Study
* 7.5 Hands-on Module 8: AI-Integrated Network Operations Centers (NOC)
* 8.1 Transitioning to AI-driven NOCs
* 8.2 Automating escalations and root cause analyses
* 8.3 Closed-loop automation with AI and SDN integration
* 8.4 Designing AI-ready network architectures
* 8.5 Change management strategies for AI rollouts in operations
* 8.6 Case Study: Implementation of AI assistants in NOCs Module 9: Ethical Considerations in Artificial Intelligence
* 9.1 Ethical Implications of Using Artificial Intelligence
* 9.2 Responsible Deployment Practices
* 9.3 Emerging Trends and Challenges
* 9.4 Case Study
* 9.5 Hands-on Module 10: Capstone Project
Tools you will explore
* TensorFlow
* Keras
* Matplotlib
Online proctored exam included, with one free retake.
Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam
Access to all materials and exams is provided for 365 days after delivery.
Instructor-led OR Self-paced course + Official exam + Digital badge
€510
E-Learning
max 999
5 dagen