Get yourself trained on Tensorflow on Google’s with this Online Training Tensorflow on Google’s Cloud Platform for Data Engineers.
Online Training Tensorflow on Google’s Cloud Platform for Data Engineers
Welcome toTensorflow on the Google Cloud Platform for DataEngineersThis is thefourthcourse in a series of courses designed to help you attain the covetedGoogle Certified Data Engineer.Additionally, the series of courses is going toshow youthe role of thedata engineer on the Google Cloud Platform.NOTE:This is not a course on how to develop machine learning models with TensorFlow. This is a very targeted course on TensorFlow for data engineers. My goal is to give data engineers what they need to know for the exam and provide learners with the foundations of TensorFlow onGoogle’s Cloud Platform.At this juncture theGoogle Certified Data Engineeris the onlyreal world certificationfor data and machine learning engineers.TensorFlowis an open source software library created by Gogglefor doing graph-based computations quickly. It does this by utilizing the GPU(Graphics Processing Unit)and also making it easy to distribute the work across multiple GPUs and computers.Tensors, in general, are simply arrays of numbers, or functions, that transform according to certain rules under a change of conditions.Nodes in the graphs represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them.In the courseyou’ll discover how to apply TensorFlow to machine learning, the concept of a Tensor, the anatomy of a simple program, basic constructs such as constants, variables, placeholders, sessionsand the computation graph.You’ll work with basic math operations and image transformations to see how common computations are performed.You’ll learn TensorFlow within the context of the Google Cloud Platform. *Five Reasons to take this Course.*1) You Want to be a Data EngineerIt’sthe number one job in the world. (not just within the computer space)Thegrowth potential career wise is second to none. You want the freedom to moveanywhere you’d like. You want to be compensated for your efforts. You want tobe able to work remotely. The list of benefits goes on.2) The Google Certified DataEngineerGoogleis always ahead of the game. If you were to look back at a timeline of theiraccomplishments in the data space you might believe they have a crystal ball.They’ve been a decade ahead of everyone. Now, they are the first and theonly cloud vendor to have a data engineering certification. With their trackrecord I’ll go with Google.3)The Growth of Data isInsaneNinetypercent of all the world’s data has been created in the last two years.Business around the world generate approximately 450 billions transactions aday. The amount of data collected by all organizations is approximately 2.5Exabytes a day. That number doubles every month.4) TensorFlow in Plain EnglishTensorFlow is a low level language. The basic concept of a tenor is hard to grasp if you aren’t familiar with neural networks. In the course we will break down TensorFlow in to bite sized pieces ensuring you learn the fundamentals first. After we’ve built a base understanding of tensors and how they flow we will move on to more complicated examples.5) You want to be ahead of the CurveThe data engineer role is fairly new. While your learning, building your skills andbecoming certified you arealso the first to be part of this burgeoning field. You know that the first to be certified meansthe first to be hired and first to receive the top compensation package.Thank you for your interest inTensorflow on the Google Cloud Platform for DataEngineersand we will see you in the course!!
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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.