Get yourself trained on Learn Data Science with this Online Training Learn Data Science with Python.
Online Training Learn Data Science with Python
Python is a popular general purpose programming language used for both large and small-scale applications. Pythons wide-spread adoption is due in part to its large standard library, easy readability and support of multiple paradigms including functional, procedural and object-oriented programming styles.This Course followspragmatic approach to tackle end-to-end data science project cycle right from extracting data from different types of sources to exposing your machine learning model as API endpoints that can be consumed in a real-world data solution.This course will not only help you to understand various data science related concepts, but also help you to implement the concepts in an industry standard approach by utilizing Python and related libraries.First, you will be introduced to the various stages of a typical data science project cycle and a standardized project template to work on any data science projectIn this course, you will learn:IntroductionWhy Python for Data Science?Setting up Working EnvironmentSelection, Indexing, and FilteringSpread Measure: Variance and Standard DeviationPerformance MetricsLinear and Logistic Regression ModelK-Fold CrossvalidationSoftwares used in CourseJypiter 3By the end of this course, you will have a solid foundation to handle any data science project and have the knowledge to apply various Python libraries to create your own data science solutions.On course completion, You will be Mastered in PythonLanguageand can implement Successfully it in your work place or willsurelyland on High Paying Job
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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.