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AI+ Telecommunications Practitioner™

Kód kurzu: NPAT2501

Táto časť nie je lokalizovaná

Formerly known as AI+ Telecommunications™

AI in Telecommunications: Redefining the Future of Seamless Connectivity

  • Core Foundational Insights:Discover AI innovations transforming telecom networks, including predictive upkeep, performance tuning, and automated customer support.
  • Advanced Applications: Gain expertise in AI for 5G rollouts, spotting irregularities, and dynamic resource allocation to elevate network efficiency.
  • Specialized Solutions: Dive into AI strategies for threat protection, fraud prevention, and smooth IoT connectivity to maintain robust networks.
  • Capstone Project:
    Create AI-powered fixes for practical telecom issues like optimizing networks and smart service provisioning.
75 EUR

92 EUR s DPH

Výber termínov
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+420 731 175 867 edu@edutrainings.cz

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Široká ponuka technických
a soft skills kurzov

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Skvelý zákaznicky
servis

Prispôsobenie kurzov
presne na mieru

Termíny kurzov

Počiatočný dátum: Na vyžiadanie

Garantovaný

Forma: Self-Paced

Dĺžka kurzu: 40 hodín

Jazyk: en

Cena bez DPH: 285 EUR

Registrovať

Počiatočný dátum: Na vyžiadanie

Garantovaný

Forma: Self-Paced

Dĺžka kurzu: 40 hodín

Jazyk: en

Cena bez DPH: 75 EUR

Registrovať

Počiatočný
dátum		 Miesto
konania		 Forma Dĺžka
kurzu		 Jazyk Cena bez DPH
G Na vyžiadanie Self-Paced 40 hodín en 285 EUR Registrovať
G Na vyžiadanie Self-Paced 40 hodín en 75 EUR Registrovať
G Garantovaný kurz

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Popis kurzu

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AI and Telecommunications Integration

Learn how AI integrates with telecom technologies to optimize network performance and improve customer experience.

Python for Telecom Applications

Master Python for network optimization, predictive maintenance, and telecom data analysis.

Data Analysis and Network Optimization

Understand how to process telecom data and apply AI for enhanced network reliability and resource management.

AI-Driven Network Management

Apply AI techniques for intelligent traffic management, resource allocation, and real-time network monitoring

Štruktúra kurzu

Táto časť nie je lokalizovaná

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

Predpokladané znalosti

Táto časť nie je lokalizovaná

  • Telecom Sector Understanding: Fundamental grasp of telecommunications principles, covering networks, 5G technology, and IoT systems.
  • Coding Capabilities: Experience with programming, ideally Python.
  • Data Interpretation: Foundational understanding of data analysis methods is advantageous.
  • AI Background: Previous exposure to AI concepts is useful but not mandatory for course participation.

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pruduktová podpora

+420 731 175 867

edu@edutrainings.cz