advanced search
Do you have any questions?
+420 731 175 867 (Mo-Fr: 9A.M.-5P.M.)
EN
0 Basket

AI+ Telecommunications Practitioner™

Course code: NPAT2501

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

91 EUR including VAT

Selection of dates
onas
Do you have a question?
+420 731 175 867 edu@edutrainings.cz

Professional
and certified lecturers

Internationally
recognized certifications

Wide range of technical
and soft skills courses

View soft skills courses

Great customer
service

Making courses
exactly to measure your needs

Course dates

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 40 hours

Language: en

Price without VAT: 285 EUR

Register

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 40 hours

Language: en

Price without VAT: 75 EUR

Register

Starting
date		 Place
Type Course
duration		 Language Price without VAT
G Upon request Self-paced 40 hours en 285 EUR Register
G Upon request Self-paced 40 hours en 75 EUR Register
G Guaranteed course

Didn't find a suitable date?

Write to us about listing an alternative tailor-made date.

Contact

Course description

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

Course structure

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

Prerequisites

  • 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.

Do you need advice or a tailor-made course?

onas

product support

+420 731 175 867

edu@edutrainings.cz

ComGate payment gateway MasterCard Logo Visa logo