Opleiding: AI+ Telecommunications™ eLearning

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