CodeKidz vs. Codelicious vs. JavaScript vs. NumPy Comparison Chart

Codelicious Computer Science Curriculum is grade-level differentiated, aligns with state and national computer science standards, and is continually updated to reflect changes in computer science. Since computer science is more than just coding, Codelicious courses include coding, unplugged, digital citizenship, and STEM career lessons as well as hardware integrations. Explore all courses. Inspire your students with courses that spark their creativity. Coding lessons use Scratch, a block based coding language, ideal for the transitional and fluent reader. Motivate your students with courses that connect to their world. Coding lessons use line based languages JavaScript, HTML, CSS, and Java to explore programming options. Empower your students with courses that expand their skills. Coding lessons use JavaScript, Java, Python, and Godot to develop websites, programs, and games.

Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today. NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries. The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code. NumPy’s high level syntax makes it accessible and productive for programmers from any background or experience level. NumPy brings the computational power of languages like C and Fortran to Python, a language much easier to learn and use. With this power comes simplicity: a solution in NumPy is often clear and elegant.