AI+ Telecommunications™

Cílová skupina

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Telecom Engineers: Professionals looking to integrate AI for network optimization, 5G deployment, and predictive maintenance.

Data Analysts: Individuals eager to apply AI in data processing and analysis within the telecom industry.

Network Security Experts: Those interested in leveraging AI to enhance telecom infrastructure security and threat detection.

AI Enthusiasts: People with a passion for AI looking to apply it in the rapidly evolving telecommunications sector.

Project Managers: Professionals overseeing telecom projects who wish to understand AI’s impact on efficiency and innovation in telecom.

Struktura kurzu

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Module 1: Introduction to AI in Telecommunications

1. 1.1 AI Fundamentals in Telecommunications
2. 1.2 AI Technologies for Telecom
3. 1.3 Emerging Trends in AI for Telecommunications
4. 1.4 Case Study
5. 1.5 Hands-on

Module 2: Data Engineering for Telecom AI

1. 2.1 Foundation of Telecom Data Engineering
2. 2.2 Designing and Managing the Telecom Data Pipeline
3. 2.3 Data Engineering tools and Technology
4. 2.4 Case Study: SK Telecom’s Big Data Analytics with Metatron Discovery
5. 2.5  Hands on Exercise

Module 3: AI for 5G Networks

1. 3.1 Introduction to 5G
2. 3.2 AI Applications in 5G
3. 3.3 Enhancing Network Management with AI
4. 3.4 Case Study
5. 3.5 Hands-on

Module 4: AI in Network Optimization

1. 4.1 Predictive Network Management
2. 4.2 Performance Enhancement Techniques
3. 4.3 Traffic Management Strategies
4. 4.4 Case Study
5. 4.5 Hands-on

Module 5: AI in Network Security

1. 5.1 Security Threats in Telecom
2. 5.2 AI Security Solutions
3. 5.3 Advanced Security Frameworks
4. 5.4 Case Study
5. 5.5 Hands-on

Module 6: Enhancing Customer Experience with AI

1. 6.1 Personalized Customer Service
2. 6.2 Service Quality Improvement
3. 6.3 Enhancing Customer Engagement
4. 6.4 Case Study
5. 6.5 Hands-on

Module 7: IoT Integration with Telecommunications

1. 7.1 IoT Fundamentals
2. 7.2 Managing IoT Security Challenges
3. 7.3 Enhancing Operational Efficiency with IoT
4. 7.4 Case Study
5. 7.5 Hands-on

Module 8: AI-Integrated Network Operations Centers (NOC)

1. 8.1 Transitioning to AI-driven NOCs
2. 8.2 Automating escalations and root cause analyses
3. 8.3 Closed-loop automation with AI and SDN integration
4. 8.4 Designing AI-ready network architectures
5. 8.5 Change management strategies for AI rollouts in operations
6. 8.6 Case Study: Implementation of AI assistants in NOCs

Module 9: Ethical Considerations in Artificial Intelligence

1. 9.1 Ethical Implications of Using Artificial Intelligence
2. 9.2 Responsible Deployment Practices
3. 9.3 Emerging Trends and Challenges
4. 9.4 Case Study
5. 9.5 Hands-on

Module 10: Capstone Project

Certifikace

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50 questions, 70% passing, 90 minutes, online proctored exam