Cloud Computing Fundamentals
Core concepts, service models, deployment models and cloud economics.
A structured course catalog for cloud system learners, certified teachers, partner institutions and enterprise training programs.
Core concepts, service models, deployment models and cloud economics.
Architecture patterns, reliability, observability and governance.
Containers, Kubernetes, service mesh, serverless and platform engineering.
Automation, CI/CD, incident response, capacity and reliability practices.
Identity, network security, compliance, secrets, risk and cloud security operations.
AI infrastructure, GPU clusters, model serving and intelligent platform operations.
Migration planning, workload assessment, hybrid cloud and modernization.
Virtualization, storage, networking and data center operation foundations.
Top-tier PhD with strong mathematical foundations; track record of top-conference papers and patents; sets technical strategy and drives foundational AI breakthroughs.
Proficient in PyTorch/TensorFlow; distributed training, Mixture-of-Experts (MoE), RLHF, and CUDA kernel-level optimization.
Publishes peer-reviewed papers and files patents; focuses on theoretical innovation rather than applied engineering.
Builds cross-modal models, such as CLIP-style architectures, that fuse image, text and speech understanding.
Object detection, image segmentation, pose estimation and 3D reconstruction; OpenCV and PyTorch Vision.
Language modeling and text processing; Hugging Face ecosystem; embeddings and vector-based retrieval.
Python, ML frameworks, SQL/NoSQL, feature engineering; MLOps fundamentals including CI/CD, Docker, Kubernetes and cloud platforms.
Full-stack delivery with Vue/React/Next.js, FastAPI/Flask/Django, vector databases, RAG pipelines, LangChain/LlamaIndex and inference optimization.
Kubernetes, Docker, CI/CD pipelines; model versioning with MLflow, A/B testing frameworks and feature stores.
Docker/Kubernetes containerization; lightweight on-premise and edge-device model deployment for offline-capable systems.
Designs and maintains high-performance computing clusters for foundation-model training; GPU allocation, memory bandwidth and inference latency optimization.
Automated test-case generation, model evaluation metrics and red-teaming for AI systems.
Prompting frameworks such as CRISP and RACE, chain-of-thought and few-shot techniques; working knowledge of GPT, Claude, Gemini and domain-specific prompting.
Feeds and labels training data, tunes prompts and reviews model outputs; no specific academic background required.
Understands agentic systems versus single-model API applications; production-grade agent deployment and multi-agent workflow orchestration.
Lightweight fine-tuning techniques such as LoRA and DeepSpeed to adapt foundation models to specific tasks.
Proficiency with Stable Diffusion, Blender and similar tools; virtual-human design and motion-capture pipelines.
Understands model capability boundaries, training pipelines and evaluation methods; judges which tasks are AI-suited.
Deep familiarity with industry-specific core systems such as manufacturing MES or healthcare HIS plus hands-on project delivery experience.
Combines domain experience in areas such as healthcare, finance or manufacturing with applied AI tool fluency to solve real business problems.
Broad knowledge of LLMs, MLOps and computer vision; typically 8+ years of experience; advisory-oriented client-facing role.
Defends against adversarial attacks, prompt injection and model poisoning; builds guardrails around deployed models.
Proficient with confusion matrices and other evaluation tools; detects and helps correct algorithmic bias.
Legal, policy or ethics background; understands regulatory frameworks such as the EU AI Act; conducts bias audits, compliance review and explainability analysis.
Industrial and service robots; visual perception, motion control and decision optimization; combined hardware and software skill set.
Multimodal perception, path planning and decision-making algorithms for self-driving systems.
Server, network and storage hardware installation and troubleshooting; Windows Server and Linux administration; 24/7 shift rotation; low/high-voltage electrical work certificate often preferred.
Installation, configuration and troubleshooting of servers, switches, routers and firewalls; virtualization with VMware/KVM; data center power, precision cooling and fire-suppression systems.
Design and operation of high-performance GPU clusters and AI/cloud platform architecture; network topology planning and hardware fault diagnosis.
Operating AI platforms on dedicated hardware; writing deployment runbooks; continuous improvement of inspection routines; standardized issue troubleshooting.
Kubernetes cluster management with Operators and service mesh, Helm packaging and GPU server tuning; typically manages 50+ node clusters.
Prometheus + Thanos monitoring stack; applying machine learning to operations, including LSTM-based forecasting, anomaly detection and log clustering.
Docker/Kubernetes operations, monitoring and alerting; Nginx/Keepalived maintenance and tuning; Shell/Python scripting for automation.
On-site installation, commissioning and program optimization for industrial robots and automation equipment; teach-programming, path planning, fixture integration and signal coordination.
Field commissioning and maintenance of service robots; service-robot commissioning and maintenance responsibilities aligned with national occupational standards.
On-site installation, commissioning and repair of robotic equipment; after-sales technical support and customer issue resolution.
On-site installation and commissioning of robot and 3D vision systems; background in image processing, automation, mechanical or electrical engineering.
Hardware performance testing and fault diagnosis using debugging equipment and test instruments; working knowledge of C/C++, ROS and Linux.
On-site hardware installation and hardware/software system commissioning for IoT project deployments.
Operations and maintenance of IoT hardware terminals and the associated software platform.
Hardware/software development for smart terminal devices and end-to-end project delivery.
Embedded hardware and software design; circuit and interface design for ARM/MCU platforms; RTOS driver development; optimization for low power and limited memory.
Phase one makes the catalog and route structure visible. Learning records, video delivery and payments can be connected as independent modules.
The same catalog can later support individual enrollment, teacher publishing, institution group registration and certification exam preparation.
Published courses can now be managed from the admin console and enrolled from the public website.
A foundation course for learners entering cloud computing and cloud system certification.
FOUNDATION · ONLINE · 24 hours
USD 199.00
View courseA practical operations course for Kubernetes and cloud-native platform teams.
ENGINEER · HYBRID · 36 hours
USD 399.00
View courseGPU cluster, model-serving and AI platform operations for enterprise teams.
ENGINEER · ONLINE · 40 hours
USD 499.00
View courseSecurity fundamentals for cloud identity, network, compliance and operational risk.
SPECIALIST · ONLINE · 30 hours
USD 299.00
View course