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Guided learning journeys that build knowledge step by step.
category · Learning · slug · learning · 7813 Paths
7813 Paths · page 438 / 782
This advanced path equips systems programmers with the principles and practices of systems-level programming, covering pointers, manual memory management, system calls, assembly integration, and debugging. It builds on computer architecture and C/C++ experience to deepen understanding of low-level execution and OS interaction.
This advanced learning path equips professional developers with deep expertise in the Django framework, covering core architecture, ORM mastery, security hardening, testing, and production deployment. Through a structured sequence of foundational to advanced topics, learners will build, secure, and deploy robust Django applications.
This path takes engineers and developers from hardware backgrounds through the fundamentals of embedded systems programming. It covers computer architecture basics, C/C++ for microcontrollers, hardware interaction, and real-time constraints, culminating in a practical project.
This advanced learning path equips data engineers and scientists with the skills to design, build, and manage robust data pipelines. It covers core ETL processes, data warehousing concepts, and modern tools like Apache Spark and Airflow, along with handling streaming data. Prerequisites include Python, SQL, and database fundamentals.
This advanced learning path equips cloud developers with the knowledge to design, build, and deploy cloud-native applications. It covers core cloud services, containerization, Kubernetes orchestration, serverless computing, microservices architecture, and essential DevOps practices. The path emphasizes practical, applied learning for professional developers.
This learning path guides aspiring full-stack developers from foundational web technologies to advanced deployment strategies. It covers frontend development with React, backend development with Node.js and Express, database management with SQL and MongoDB, and deployment practices. The path emphasizes practical application and project-based learning to build job-ready skills.
A learning path for developers interested in creating educational tools, covering foundational programming skills, web development, and principles of interactive learning design. It progresses from core programming concepts through full-stack development to specialized topics like gamification and assessment tools.
This learning path equips developers with the knowledge and skills to contribute effectively to open-source projects. It covers essential version control, licensing, contribution workflows, code review, and community collaboration practices.
A focused learning path for STEM students and researchers to apply Python programming to solve scientific problems and analyze data. It covers essential Python programming, NumPy for numerical computing, SciPy for scientific algorithms, Matplotlib for visualization, data cleaning, and numerical methods.
This path introduces programmers to core game development concepts, including game loops, sprites, collision detection, user input, and game engines. It builds on object-oriented programming and basic physics to create a solid foundation for building simple games.