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

Self study materials are available for 365 days.

Instructor-led OR Self-paced course + Official exam + Digital badge