Get yourself trained on Data Visualization with with this Online Training Data Visualization with Python: The Complete Guide.
Online Training Data Visualization with Python: The Complete Guide
Datais becoming a force to recon with. Withthe amount of data that is being generated every minute, dealing withdata has become more important. Theimportance of data liesin the fact that it allowsus to look at our history and predict the future.DataScience is the field that deals with collecting, sorting, organizingand also analyzing huge amountsof data. This data is thenused to understand the current and future trends. This field borrowstechniques and theories from across multiple fields such asmathematics, statistics, computer science, information science, etc.It also aids other domains such as machine learning, data mining,databases and visualization.DataScientists are gaining importance and are also earning highersalaries, which means this is the right time to become a datascientist. While, it mightseem easy, sorting data, these scientists are responsible for writingimportant algorithms and programs to help sort and analyze the data andthis isnt an easy task.However,weve done everything we can to make it as simple as possible. Inthis beginner course to data visualization, youll get started withimportant concepts of data science. The course will help youunderstand exactly where to beginin this lucrative field. Startingat the very beginning, this course will help you understand theimportance of Data Science, along with becoming familiar withMatplotlib, Pythons very own visualization library. From there youwill learn about the linear general statistics and data analysis.Wellalso go overimportant concepts such as data clustering, hypothesis gradientdescent and advanced data visualizations.Thecourse will cover a number of different conceptssuch as introduction to Data Science including concepts such asLinear Algebra, Probability and Statistics, Matplotlib, Charts andGraphs, Data Analysis, Visualization of non uniform data, Hypothesisand Gradient Descent, Data Clustering andso much more. Thats notall, well also include projects to help you show exactly how tobuild visuals using Python.Youcan learn all this and tons of interesting stuff in this unique datascience course. Enroll now and start building next generationinterfaces for your data.
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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.