AI+ Telecommunications™

AI+ Telecommunications™

AI in Telecommunications: Redefining the Future of Seamless Connectivity

Certificate Code: AT - 2501

About This Course

  • 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. 

Certificate Overview

Included

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

Duration

  • Instructor-Led: 5 days (live or virtual)
  • Self-Paced: 40 hours of content

Prerequisites

Basic understanding of telecommunications concepts and technologies, familiarity with programming, preferably Python, basic knowledge of data analysis techniques, prior experience with AI.

Exam Format

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

Course Modules

1

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
2

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
3

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
4

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
5

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
6

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
7

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
8

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
9

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
10

Module 10: Capstone Project

AI Tools You'll Learn

TensorFlow

TensorFlow

Keras

Keras

Matplotlib

Matplotlib