AI+ Telecommunications™
AT - 2501
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.
Why This Certification Matters
At a Glance: Course + Exam Overview
- Instructor-Led: 5 day (live or virtual)
- Self-Paced: 40 hours of content
Who Should Enroll?
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.
Job Roles & Industry Outlook
Telecom AI Consultant
Advise telecom companies on integrating AI solutions to optimize network performance, customer experience, and service delivery.
5G Network Manager
Oversee the development and deployment of AI-powered 5G networks, ensuring enhanced connectivity and network efficiency.
AI Network Architect
Design and implement AI-driven network systems for predictive maintenance, QoS monitoring, and real-time resource management in telecom.
Telecom Operations Manager (AI-driven)
Manage telecom operations using AI tools to optimize network performance, reduce costs, and improve customer satisfaction.
Chief Telecom Officer (CTO)
Lead the adoption of AI technologies across telecom infrastructure, driving innovation, scalability, and improved service delivery.
- The AI in telecommunications market, valued at $3.34 billion in 2024, is expected to reach $58.74 billion by 2032, growing at a CAGR of 43.3%. (Source: Fortune Business Insights)
- AI enhances network performance, reduces latency, and enables predictive maintenance for improved reliability.
- AI-driven chatbots and virtual assistants boost customer satisfaction and reduce churn rates.
- AI powers intelligent traffic management, resource allocation, and seamless connectivity for 5G applications.
- AI plays a key role in detecting and mitigating cyber threats, ensuring telecom network security.
Skills You’ll Gain
- AI & Machine Learning
- Telecommunications Technologies (5G, IoT, SDN)
- Network Security Tools (IDS, Intrusion Detection)
- Predictive Analytics
- Big Data Technologies
What You'll Learn
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
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
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
4.1 Predictive Network Management
4.2 Performance Enhancement Techniques
4.3 Traffic Management Strategies
4.4 Case Study
4.5 Hands-on
5.1 Security Threats in Telecom
5.2 AI Security Solutions
5.3 Advanced Security Frameworks
5.4 Case Study
5.5 Hands-on
6.1 Personalized Customer Service
6.2 Service Quality Improvement
6.3 Enhancing Customer Engagement
6.4 Case Study
6.5 Hands-on
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
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 Case Study
8.6 Hands-On
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
Tools You'll Explore
TensorFlow
Keras
Matplotlib
Prerequisites
- Telecommunications Knowledge: Basic understanding of telecommunications concepts, including networks, 5G, and IoT.
- Programming Skills: Familiarity with programming, preferably in Python.
- Data Analysis: Basic knowledge of data analysis techniques is beneficial.
- AI Familiarity: Prior experience with AI is helpful but not required for enrollment in this course.
Exam Details
Duration
90 minutes
Passing Score
70% (35/50)
Format
50 multiple-choice/multiple-response questions
Delivery Method
Online via proctored exam platform (flexible scheduling)
Exam Blueprint
- Introduction to AI in Telecommunications - 9%
- Data Engineering for Telecom AI - 13%
- AI for 5G Networks - 13%
- AI in Network Optimization - 13%
- AI for Network Security - 3%
- Enhancing Customer Experience with AI - 13%
- IoT Integration with Telecommunications - 13%
- AI-Integrated Network Operations Centers (NOCs) - 13%
Choose the Format That Fits Your Schedule
What’s Included (One-Year Subscription + All Updates)
- High-Quality Videos, E-book (PDF & Audio), and Podcasts
- AI Mentor for Personalized Guidance
- Quizzes, Assessments, and Course Resources
- Online Proctored Exam with One Free Retake
- Comprehensive Exam Study Guide
Instructor-Led (Live Virtual/Classroom)
- 5 days of intensive training with live demos
- Real-time Q&A, peer collaboration, and hands-on labs
- Led by AI Certified Trainers and delivered through Authorized Training Partners
Self-Paced Online
- ~40 hours of on-demand video lessons, e-book, podcasts, and interactive labs
- Learn anywhere, anytime, with modular quizzes to track progress
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Get CertifiedFrequently Asked Questions
Yes, you’ll gain practical, hands-on experience to immediately apply AI and BI skills in real-world business scenarios through case studies and a capstone project.
This course combines AI with telecommunications, teaching Python, machine learning, and network management, focusing on 5G, IoT, and predictive maintenance.
You’ll work on projects like network optimization, predictive maintenance, QoS, and resource management, culminating in a real telecom capstone.
You’ll work on projects like network optimization, predictive maintenance, QoS, and resource management, culminating in a real telecom capstone.
You’ll gain expertise in AI and telecom technologies, with hands-on experience and a capstone preparing you for roles in telecom networks and 5G deployment.