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Learn Scientific Computing, earn certificates with free online courses from Stanford, Johns Hopkins, UC San Diego, Princeton and other top universities around the world. Read reviews to decide if a class is right for you.
Prepare for your next coding interviews in Python.
Julia is a new programming language designed to be the ideal language for scientific computing, machine learning, and data mining.
Learn scientific computing with NumPy: create arrays, index multidimensional data, and use advanced functions. Suitable for beginners with animated examples and hands-on challenges.
Python அடிப்படைகளை தமிழில் கற்றுக்கொள்ளுங்கள். எளிமையான தொடரியல், பயன்பாடுகள், மற்றும் நிரலாக்க கருத்துக்களை அறிமுகப்படுத்தும் வழிகாட்டி.
Learn Fortran basics for scientific computing, including simple applications and DISLIN graphics. Ideal for STEM students and those working with legacy code.
Master Julia's fundamentals and functional programming concepts through hands-on practice, enhancing your problem-solving skills for scientific and technical computing.
Master the essential skills of data manipulation in Julia. Learn how to inspect, transform, group, and visualize DataFrames using real-world datasets.
Scientific Programming with C++ Masterclass with STL, BOOST, CUDA, OpenMP and MPI Libraries: 21 Hours!
Master Matlab and Simulink for engineering and scientific problem-solving. Gain hands-on experience in programming, data analysis, and model simulation to tackle real-world challenges with confidence.
Mastering Python and R for Scientific Data Analysis
Learn the Python Programming Language for scientific work and for Deep Learning (includes 4 Applications Projects)
Even if this is the only numerical methods course you ever take, dedicating yourself to mastering all modules will give you a foundation from which you can build a career in scientific computing.
Master Python for scientific computing, data structures, databases, and visualization in this comprehensive program.
Learn to squeeze high performance out of modern CPUs.
Learn to apply formal methods to systematically develop correct, loop-based programs, an essential skill for computer programmers.
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