• GPA: 17.74 / 20
• Thesis: Seizure detection from multi-channel EEG using Graph Neural Networks

Covered Courses

• Digital Image Processing17/20
• Natural Language Processing19.12/20
• Advanced Computation Theory18.5/20
• Advanced Theory of Algorithms14.75/20
• Machine Learning18.45/20

• Last two years GPA: 16.98 / 20
• Total GPA: 16.12 / 20

Selected Courses

• Artificial Intelligence19.1/20
• Computer Graphics20/20
• Principles of Operating Systems20/20
• Principles of Computer Systems20/20
• Principles of Logic and Set Theory20/20
• Compiler20/20
• Database19/20

• High school GPA: 18.59 / 20
• Pre-university GPA: 18.03 / 20

Covered Topics

• Foundamentals of neuroscience, cognitive science and brain mapping
• Introduction to anatomy and physiology of the brain
• Foundamentals of EEG, MRI, fNIRS, iTMS/TES, and neurofeedback
• Introduction to virtual reality and eye tracking technology
• Introduction to cognitive assessment and rehabilitation tools
• Machine intelligence (application of artificial intelligence in visual neuroscience)

Covered Topics

• Core Concepts: Cluster architecture, API primitives, services, and networking
• Scheduling: Labels, selectors, resource limits, manual and automatic scheduling, taints, tolerations, and node affinity
• Logging & Monitoring: Monitoring cluster components and managing application logs
• Application Lifecycle Management: Rolling updates, rollbacks, deployments, jobs, CronJobs, ConfigMaps, Secrets, and multi-container pods
• Cluster Maintenance: Cluster upgrades, operating system upgrades, backup, and restore
• Security: Authentication, authorization, TLS certificates, network policies, security contexts, and secure images
• Storage: Persistent Volumes, Persistent Volume Claims, storage classes, and applications with persistent storage
• Networking: Network primitives, pod networking, CNI, service networking, and Ingress
• Installation, Configuration & Validation, Troubleshooting

Covered Topics

• Core Concepts: Cluster architecture, API primitives, Pods, YAML, ReplicaSets, Deployments, Namespaces, and imperative commands
• Configuration: Configuring containers, Multi-container pods, ConfigMaps, Secrets, resource requirements, security contexts, and service accounts
• Observability: Readiness and liveness probes, container logging, and monitoring applications
• Pod Design: Labels, selectors, annotations, rolling updates, rollbacks, Jobs, and CronJobs
• Services & Networking: Services, NetworkPolicies, and Ingress
• State Persistence: Volumes, Persistent Volumes, Persistent Volume Claims, and storage classes
• Security: Authentication, authorization, RBAC, cluster roles, role bindings, admission controllers, and custom resource definitions
• Additional topics: Helm fundamentals, Kubernetes challenges, certification tips, lightning labs, and mock exams

Covered Topics

• Docker Compose: In-depth concepts, Hands-on exercises
• Docker Swarm: Architecture and concepts, Setting up a Swarm cluster, Managing services, discovery, and load balancing
• Docker Stacks: Deploying multi-service applications, Placement constraints
• CI/CD with Docker: Integration and workflow, Docker Registry setup and usage
• Advanced networking with overlay networks

Covered Topics

• Network Fundamentals: OSI and TCP/IP models, IP addressing and subnetting, Network components (routers, switches, etc.)
• LAN Switching Technologies: Ethernet and switching concepts, VLANs and Inter-VLAN routing, Spanning Tree Protocol (STP)
• Routing Technologies: IP routing concepts, Static and dynamic routing, Routing protocols (RIPv2, EIGRP, OSPF)
• WAN Technologies: WAN concepts and technologies, Point-to-Point Protocol (PPP), Frame Relay
• Infrastructure Services: Dynamic Host Configuration Protocol (DHCP), Network Address Translation (NAT), Network Time Protocol (NTP)
• Infrastructure Maintenance: Device management and maintenance, IOS backup and restore, Network troubleshooting
• Infrastructure Security: Access control lists (ACLs), Device security features, Remote access (Telnet, SSH)