Get yourself trained on Data Science for with this Online Training Data Science for AI and Machine Learning Using R.
Online Training Data Science for AI and Machine Learning Using R
Becoming Data Science professional (Data Scientist) is a long journey and need guidance fromseasoned Data Science professional (Chief Data Scientist). We are trying to manage the journey such a way that you learn right skills and in theright way. The whole concepts of the course areto make you ready for Data Science projects, mainly in Machine learning and AI projects. You will learn1. Foundation of Machine learning2. Supervised Machine learning – Regression3. Supervised Machine learning – Classifications4. Unsupervised Machine learning (Clustering, KNN, PCA)5. Text Analytics6. Time Series7. RShiny
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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.