40 Hour Self-Paced Course or 5 Day Instructor-Led Training

40 Hour Self-Paced Course or 5 Day Instructor-Led Training

40 Hour Self-Paced Course or 5 Day Instructor-Led Training

AI+ Telecommunications™

AI+ Telecommunications™

AI+ Telecommunications™

Transform Telecom Networks with AI-Driven Automation, Analytics, and Optimization.

Transform Telecom Networks with AI-Driven Automation, Analytics, and Optimization.

Transform Telecom Networks with AI-Driven Automation, Analytics, and Optimization.

Get the AI+ Telecommunications™ outline:

Course Prerequisites:

  • Telecommunications Knowledge: Basic understanding of telecommunications concepts and technologies.

  • Programming Skills: Familiarity with programming, preferably in Python.

  • Data Analysis: Basic knowledge of data analysis techniques is beneficial.

  • AI Familiarity: While prior experience with AI is helpful, it is not required to enroll in this course.

Modules:

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 Foundations 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

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 for 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 (NOCs)

8.1 Transitioning to AI-driven NOCs: From reactive to predictive operations

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

8.7 Case Study: Nokia's Integration of AI in Network Optimization

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

Date Issued: 01/06/2025