Advanced NumPy Techniques: A Comprehensive Guide to Data Analysis and Computation begins with a profound exploration of NumPy's core: the powerful and efficient 'ndarray' data structure, which serves as the foundation for Python's data science ecosystem.

The book covers universal functions for element-wise operations, broadcasting semantics for operations on differently shaped arrays, and linear algebra computations within NumPy. These principles will enable you to handle numerical problems with efficacy. The guide also delves into random number generation and sampling techniques for simulations and probabilistic analysis, and explores NumPy's file I/O functionality for effective data management.

Throughout, clear explanations are accompanied by insightful tips and best practices. Practical examples clarify concepts, while common pitfalls are outlined to smooth your learning journey. This comprehensive guide equips you with the knowledge to perform advanced computations, and craft algorithms with NumPy, catering to both novices eager to learn and experienced analysts seeking to sharpen their skills.