  Entanglement, a phenomenon that has puzzled scientists since its discovery,
has been extensively studied by many researchers through both theoretical and
experimental aspect of both quantum information processing (QIP) and quantum
mechanics (QM). But how can entanglement be most effectively taught to computer
science students compared to applied physics students?. in this educational
pursuit, we propose using Yao.jl, a quantum computing framework written in
Julia for teaching entanglement to graduate computer science students attending
a quantum computing class at Johns Hopkins University.
  David Mermin's just enough QM for them to understand and develop algorithms
in quantum computation [Mer98, Mer03] idea aligns with the purpose of this
work. Additionally, the authors of the study Improving students understanding
of QM via the Stern-Gerlach experiment (SGE) argue that this experiment should
be a key part of any QM education. Here, we explore the concept of entanglement
and it's quantification in various quantum information processing experiments,
including one inequality-free form of Bell's theorem: (1) Superposition via the
Hadamard, (2) Bell-state generation and (3) GHZ state generation. The
utilisation of circuit diagrams and code fragmentsis a central theme in this
work's philosophy.
