Workshop on AI-Powered Telecommunications Networks: Intelligent Automation Using Machine Learning and Deep Learning
5 DAYS
INSTRUCTOR LED HANDS-ON WORKSHOP
“OUR COURSES CAN BE SPECIALLY TAILORED TO ADDRESS YOUR REQUIREMENT – TELECONTRAN”
As telecommunications networks continue to evolve toward more complex and data-driven architectures, AI-powered technologies are playing a critical role in network automation, predictive analytics, resource optimization, cybersecurity, and autonomous decision-making. Telecom operators that strategically adopt AI-driven solutions will be better positioned to address future operational challenges while capitalizing on emerging opportunities such as smart infrastructure development, digital transformation initiatives, intelligent network automation, and next-generation communication services including 5G, future 6G networks, and advanced connected ecosystems.
The objective of Telecontran’s “Workshop on AI-Powered Telecommunications Networks: Intelligent Automation Using Machine Learning and Deep Learning” is to present an overview of artificial intelligence (AI) along with system architecture, design principles, concepts of Machine Learning (ML) and Deep Learning (DL) and their application in telecom industry, assisting participants understand how intelligent systems are transforming modern telecom operations.
After successful completion of this 5-day workshop participants will be able to
- Understand the impact and evolution of Artificial Intelligence, Machine Learning and Deep Learning and its role in modern telecommunication network.
- Explore AI-driven applications in telecom networks including network optimization, traffic prediction, spectrum management and performance enhancement.
- Examine intelligent automation techniques for predictive maintenance, fault detection, self-healing networks and autonomous operations.
- Analyze AI integration within next-generation telecom technologies including 5G, cloud-native networks and future 6G systems.
- Explore the ethical considerations and regulatory challenges of implementing Artificial Intelligence in Telecom industry.
- Develop strategic knowledge of AI adoption in telecom operations to improve efficiency, strengthen security, enhance customer experience and accelerate digital transformation.
COURSE CURRICULUM
This course targets telecom engineers and professionals, project managers, RF Engineers, Core Network Engineers, OSS/BSS Teams, Network Operations Center (NOC) Engineers, Telecom Regulators, ICT Professionals, Telecom Technology Managers within telecom industry.
Modern and Next Generation Telecommunication Industry
- Evolution of Telecommunication Technologies
- Digital Transformation in Telecommunications
- Key drivers and challenges of Digital Transformation
- Emerging Technologies (5G / 6G / IoT / AI) and Implementation
Artificial Intelligence (AI) in Modern Telecommunication
- Evolution of Artificial Intelligence
- Types of Artificial Intelligence
- Applications of AI in Telecommunications
- Impact and Principles of AI
- Ethics and Regulation of Artificial Intelligence
Machine Learning (ML) and Deep Learning (DL) Fundamentals
- Evolution of Machine Learning
- Methods of ML
- Neural Networks and Deep Learning Architectures
- Deep Learning Models
AI Tools and Python Programming
- Basics of Python Programming
- Python Tools for AI
Generative Artificial Intelligence in Modern Telecommunication
- Importance of Generative AI in Telecommunications
- Types of Generative Models
- Applications of Generative Models in Various Industries
Generative Adversarial Networks (GANs)
- Understanding GANs
- Architecture and Applications of GANs
Variational Autoencoders (VAEs)
- Introduction to Variational Autoencoders
- Architecture and Applications of VAEs in Telecommunications
Use Cases of Generative AI in Telecommunications
- Network Optimization and Management
- Content Creation
- Predictive Maintenance
- Synthetic Data Generation
- Fraud Detection and Security
- Customer Experience Enhancement
Machine Learning in RAN and Network Performance Management
- ML-based coverage prediction
- Automatic cell planning and optimization
- Predictive congestion detection
- QoS and QoE prediction models
- Capacity forecasting for mobile networks
Case Study: Network KPI analysis and anomaly detection
Deep Learning Applications in Telecom Networks
- Traffic pattern prediction
- User mobility prediction
- Radio signal classification
- Video traffic optimization
- Voice quality prediction
- Intelligent packet routing optimization
- Satellite link performance prediction
Case Study: Deep learning model for traffic prediction
AI in Radio Network Automation
- AI-powered Self-Organizing Networks (SON)
- Automatic neighbor relation management
- Automated antenna tilt optimization
- AI-based beamforming optimization
- Massive MIMO optimization using AI
- AI for energy-efficient radio networks
- Mobility prediction models
AI in Core Network and Service Platforms
- Intelligent traffic engineering in core network
- AI-driven EPC and 5G Core optimization
- Virtualized network function management
- AI in SDN and NFV environments
- Cloud-native network orchestration
Autonomous Telecom Network Operations
- Zero-touch network automation
- Predictive maintenance for telecom infrastructure
- AI-based alarm correlation
- Intelligent fault detection systems
- Automated service provisioning
- Closed-loop network automation
Case Study: Designing autonomous network automation workflow
AI for Telecom Security and Fraud Detection
- AI-based intrusion detection systems
- SIM fraud detection
- Roaming fraud analytics
- Malware detection systems
- Fraud prevention using behavioral analytics
- Cybersecurity automation
AI in 5G Advanced and Future 6G Networks
- AI-driven network slicing management
- Edge AI computing
- AI in private enterprise networks
- AI in Open RAN architecture
- AI-powered satellite and NTN communication
- AI-native 6G network architecture
- Digital twin networks for telecom optimization
Challenges and Future Directions
- Ethical Considerations
- Regulatory Challenges of Implementing Artificial Intelligence
- Trustworthy Artificial Intelligence
- Future Trends in Generative AI for Telecommunications
TRAINING/WORKSHOP | DURATION | TRAINING DATE | LOCATION |
Workshop on AI-Powered Telecommunications Networks: Intelligent Automation Using Machine Learning and Deep Learning | 5 Days | 7 - 11 September 2026 | Singapore |
OUR HAPPY CLIENTS
WHAT OUR CLIENTS SAY ABOUT TELECONTRAN !!
Content of the course covers well in the area of Project Management.
I learned the overall concepts of cloud computing from the viewpoints of clients, service providers and organizations.
The trainer and the hands-on sessions were fantastic and this workshop helped me to learn about PowerBI and Cyber Security.
All the telecommunication concepts are well explained and learnt new technologies like 5G, IOT, M2M etc.
The course was thorough and covering all aspect in the technical environment which are from engineering, IT and also the basic background of the telco industry.
