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MATHEMATICS

Calculus

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InstructorZhenping
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Systems & NetworksDifficulty: Advanced

Parallel Computation

Parallel Computation is a specialized course that introduces students to parallel programming techniques and high-performance computing concepts essential for efficient AI and machine learning applications. The course covers fundamental concepts including thread-based programming, process synchronization, parallel algorithms, GPU programming with CUDA, and distributed computing frameworks. Through hands-on programming exercises using C++, Python, and CUDA, students will implement parallel algorithms for matrix operations, numerical computations, and data processing tasks. By the end of the course, students will understand how to leverage parallel processing to train deep neural networks, handle large-scale datasets, and optimize computational bottlenecks in modern AI systems.

DDave
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Core Programming AI14 minsDifficulty: Beginner

Advanced C++

This course provides a beginner-friendly introduction to C++ programming for students with basic Python experience, emphasizing fundamental concepts through a clear, side-by-side comparison between the two languages. Over eight weeks, students will learn essential topics including C++ syntax, data types, control flow, functions, arrays, pointers, and basic object-oriented programming, while developing an understanding of the compile-run workflow and static typing. Guided by the Practice-Centered Learning (PCL) approach, the course focuses on reading, understanding, and gradually building programs through extensive hands-on practice, mini-projects, and error-driven learning. By the end of the course, students will be able to write simple yet well-structured C++ programs and establish a strong foundation for future studies in systems programming, AI frameworks, and performance-critical software development.

RRaymond
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