1. Artificial Intelligence in Communication Systems
Machine Learning Fundamentals
– Supervised, unsupervised, reinforcement learning
– Model training, evaluation metrics, overfitting, hyperparameter tuning
Deep Learning and Neural Networks
– CNNs, RNNs, LSTMs, Transformers
– Application in traffic classification, anomaly detection, and predictive analytics
AI in Network Optimization
– Intelligent routing, QoS prediction, congestion avoidance
– Resource allocation using reinforcement learning
AI for Wireless and Mobile Networks
– Handoff optimization, channel estimation
– AI-driven power management and spectrum allocation
Security and Privacy
– AI for intrusion detection and threat modeling
– Secure learning and privacy-preserving algorithms
Practical Skills
– Tools: Python, TensorFlow, PyTorch, Scikit-learn
– Datasets: CICIDS, NSL-KDD, KDDCup, DARPA
– Simulation & testing in NS-3 or Mininet with AI modules
2. Advanced Computer Networks
Network Architecture & Protocols
– TCP/IP, BGP, MPLS, IPv6, SDN
– Routing algorithms, NAT, tunneling
Next-Generation Networks
– 5G/6G architecture, network slicing, NFV, edge computing
Wireless and Mobile Networking
– LTE/5G systems, mobility management, MAC protocols
Quality of Service (QoS) and Traffic Engineering
– Delay, jitter, throughput, SLA management
Network Security
– Protocol-level security, VPNs, firewalls, IDS/IPS
– AI-enhanced network security
Curriculum
- 1 Section
- 0 Lessons
- Lifetime
- CCE – Doctorate Exam11
- 1.2Briefly explain how AI can improve Quality of Service (QoS) in a 5G network.15 Minutes
- 1.3Explain the difference between centralized and distributed intrusion detection systems15 Minutes
- 1.4How can reinforcement learning be used for load balancing in networks?15 Minutes
- 1.5How does graph neural networks (GNN) apply to network topology analysis?15 Minutes
- 1.6List two differences between TCP Reno and BBR congestion control strategies.15 Minutes
- 1.7Name two datasets used for training AI-based IDS systems and their key characteristics.15 Minutes
- 1.8What are the privacy challenges in training ML models on communication data?15 Minutes
- 1.9What is the role of the control plane in SDN, and how does AI enhance it?15 Minutes
- 1.10What is the use of autoencoders in anomaly detection in communication networks?15 Minutes
- 1.11Why is packet timestamping important for AI-based latency prediction?15 Minutes
- 1.12Thesis-Style Question (Narrowed)4 Hours

