Preparing your Path…
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Path Catalog
Data is pulled live from GET /api/v1/paths, and only Paths with a published version are listed.
7801 Paths · page 267 / 781
This path equips network engineers with the knowledge and skills to administer and secure modern computer networks. It covers foundational network concepts, advanced routing and switching, network management, security protocols, and firewall technologies, culminating in practical application scenarios.
This learning path equips software engineers with the knowledge and skills to develop professional-grade embedded software. It covers C and embedded C, RTOS concepts, device drivers, debugging, and optimization techniques, building from foundational hardware understanding to advanced development practices.
This learning path equips hardware designers with the essential skills to use CAD tools for digital design, covering HDL, simulation, synthesis, and verification. Starting from HDL fundamentals, it progresses through simulation and synthesis, culminating in advanced verification techniques and design flows.
A professional learning path for hardware engineers to master System-on-Chip (SoC) architecture, covering foundational VLSI concepts, core architecture, integration, and verification. Progress from digital design basics to advanced SoC integration and testing.
This learning path explores how digital technologies shape society, focusing on digitalization, ethics, privacy, and the digital divide. It is designed for university students and professionals with basic computer knowledge, aiming to build a nuanced understanding of the opportunities and challenges of our digital age.
This path equips senior and graduate computer engineering students with the knowledge and skills to design computing technologies for people with disabilities. It covers user-centered design, accessibility standards, assistive technologies, adaptive interfaces, and software engineering practices, culminating in a capstone project.
This learning path introduces the principles and practices of energy-efficient computing, covering hardware foundations, software optimization, and data center design. It bridges computer architecture and sustainability, equipping learners to analyze and reduce the energy footprint of computing systems.
This advanced learning path equips senior and graduate students with the computer engineering skills needed to design and implement robotic systems. It covers embedded systems, control systems, perception, navigation, and AI integration, emphasizing practical application.
This path equips learners with a deep understanding of high-performance computing (HPC) systems, from parallel architecture to performance analysis. It covers parallel computing fundamentals, cluster design, MPI programming, and performance optimization, preparing learners for careers in HPC.
This learning path provides a comprehensive understanding of cloud computing architectures and services, covering core concepts, service models, virtualization, distributed systems, and security. It progresses from foundational knowledge to advanced design and security considerations, suitable for senior or graduate students.