Get yourself trained on Interactive Computing with with this Online Training Interactive Computing with Jupyter Notebook.
Online Training Interactive Computing with Jupyter Notebook
Python is one of the leading open source platforms for data science and numerical computing. IPython and the associated Jupyter Notebook offer efficient interfaces to Python for data analysis and interactive visualization, and they constitute an ideal gateway to the platform.Interactive Computing with Jupyter Notebook, contains many ready-to-use, focused recipes for high-performance scientific computing and data analysis, from the latest IPython/Jupyter features to the most advanced tricks, to help you write better and faster code. This course covers programming techniques: code quality and reproducibility, code optimization, high-performance computing through just-in-time compilation, parallel computing, and graphics card programming.In short, you will master relatively advanced methods in interactive numerical computing, high-performance computing, and data visualization.About the AuthorCyrille Rossant, PhD, is a neuroscience researcher and software engineer at University College London. He is a graduate of cole Normale Suprieure, Paris, where he studied mathematics and computer science. He has also worked at Princeton University and Collge de France. While working on data science and software engineering projects, he gained experience in numerical computing, parallel computing, and high-performance data visualization.He is the author of Learning IPython for Interactive Computing and Data Visualization, Second Edition, Packt Publishing.
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As a society, we spend hundreds of billions of dollars measuring the return on our financial assets. Yet, at the same time, we still haven’t found convincing ways of measuring the return on our investments in developing people.
And I get it: If my bank account pays me 1% a year, I can measure it to the penny. We’ve been collectively trained to expect neat and precise ROI calculations on everything, so when it’s applied to something as seemingly squishy as how effectively people are learning in the workplace, the natural inclination is to throw up our hands and say it can’t be done. But we need to figure this out. In a world where skills beat capital, the winners and losers of the next 30 years will be determined by their ability to attract and develop great talent.
Fortunately, corporate learning & development (L&D), like most business functions, is evolving quickly. We can embrace some level of ambiguity and have rigor when measuring the ROI of learning. It just might look a little different than an M.B.A. would expect to see in an Excel model.