Get yourself trained on Tableau 2019.1 for with this Online Training Tableau 2019.1 for Data Scientists.
Online Training Tableau 2019.1 for Data Scientists
You’ve just completed an incredible data science or data analytics project. You still need to present your findings to your manager, client or even a large audience at the conference. In these kinds of situations, powerful visualization can make or break your project. What should you do? With Tableau 2019.1 for Data Scientists, you’ll be able to answer key data decision questions, learn how to deal with disorganized data, and even visualize your results with maps and dashboards.What makes this training module different? This step-by-step guide is designed to give you practical and essential skills that anyone doing data visualization and analytics needs to have. You’ll be able to boost your visualizations by learning techniques such as adding filters and quick filters, and using color schemas in dashboards.By the end of this course, you’ll have the skills to make your Tableau data visualization projects a success by creating fascinating stories and offering invaluable guidance when strategic business decisions are being made.About The AuthorManja Bogicevics mission is to help decision-makers gain more profit with machine learning insights. She is one of the first self-made women data science entrepreneurs in the world. Currently, she is pursuing her Micromasters at MIT (field: Data Science & Statistics). She finished an MBA (Leader Project) at Ivey Business School in London, Canada, and a BA at Faculty of Economics in Belgrade, Serbia. She helps Investors and Asset Managers with data and insights on the flow and behavior of institutional investors in emerging markets. Its a niche area, of serious interest to only around 1000 people in the world.Manja is a Data Science Mentor at VC fund Faster Capital from Dubai and Data Scientist Leader and Shareholder at Trounceflow from London. Currently she works as a Data Scientist on projects in the marketing, FinTech, and sports industries.She is a data Science blogger for Cambridge Spark, Towards Data Science, Data Driven Investor, and Becoming Human: Artificial Intelligence Magazine. She is also the creator and teacher of the course How to become Data Scientist in 6 months, with more than 300 students from Serbia.Manja has a strong interest in projects that require both conceptual and analytical thinking. Her strong economics and business background in combination with her technical skills, which delivers innovative and actionable data science solutions in business.She makes magic in the Data Science world with Python, SQL, Machine Learning algorithms, and Tableau.
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Investing in yourself through Learning
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.