https:\/\/drive.google.com\/file\/d\/1AhVDvTKGMaYKLSQe6LMVdPYyqTz0uavB\/view?usp=sharing<\/a><\/p>\n\n\n\nToday there are significant critical shortage of people with AI skills. As I mentioned early in this lecture, there are a lot of people talk about AI, but not very many people know how to do that correctly. These are issues with theory and practice. A key thing is differences between knowledge and the skills. The knowledge is the theoretical or understanding of a subjet. The skills are the proficiencies by developing through the use or transfer of certain knowledge and experience. So basically in this class you learn theories and also you develop your skills by following through in a number of weekly quizzes to develop your own skills. And hopefully by the end of this class you have ability which is quality of be able to do something resulted from the experiences. In this class we will have weekly quizzes, we have a lot of homeworks that help you to improve your skills and also develop the abilities to do AI in the correct way.<\/p>\n\n\n\n
Of course AI technology is still changing fast. You can see that in the last couple years, I can see tremendous significant changes and each new research come up with much better performance. And of course AI education and traning is still evolving. But I strongly believe that our forces, our series of AI would provide you with the knowledge that you need, with skills that you can develop by doing the homeworks and the quizzes then eventually the goal is helping you to build the abilities to improve the AI technology and operation in your company, and giving you skills that you need that you can perform data analytic and AI correctly.<\/p>\n\n\n\n
So last look into the framework that I sketchily share with you. If you look at the Artificial Intelligence Framework today, the lowest level is called Device layer. That means a platform that you learn how to use it. From this platform when you are familiar, you have skills of implementing AI in such platform, then you can move to the next area be called Data Management. This is dealing with collecting data, pre-processing data, analysing data, and coming up with some predictions. The next layer is called Machine Learning. These are algorithms and software that you can build, that allows the machine to learn from existing data from a vast model data that you have been collecting. And from this Machine Learning you can do some modeling, building some prototypes, building some modellings, to come up with better predictions. And then from there you can get better predictions and decision support. And then up to that you can plan and optimize. The ultimate is help the machine autonomy to think of itself, be able to learn and perform the activities by itself.<\/p>\n\n\n\n
So you can see that within this framework that orders things for you to do. Today a lot of schools, a lot of places are teaching AI using machine learning, which is algorithms. My question is if you have all algorithms but you don’t have the right data, the performance cannot be optimized. If you focus on software and tools without understand the device layers there would be a thing that was not work. So basically for my poit of views to learn AI you have to understand the framework and go from one step to next step in an ordering fashion: understand a platform, understand the data connection, pre-processing, analytics, then using the algorithms like machine learning to create models. From this model you can adjust to make decisions and eventually optimize it. So there is an ordering in order the courses we can offer in the near future.<\/p>\n\n\n\n
And we can go from the first few classes focus on the device layers and the tools that you will use eventually you will get data collecting, data processing, and then machine learning. I hope that you understand the ordering that we have in our AI series.<\/p>\n\n\n\n
The question many people have asked me: why AI and why now? Well, AI field has been exploded recently. Because we have massive amount of data available, as well as the explosion in paralell computing power where the use of GPU clusters to train machine learning systems. Many years ago AI was not a new field but they had not been used intensively because the CPU is very very limited. And today we have so much data, all kind of data, everywhere you go you can collect certain data. All kind of data exists, but as I mentioned, in order to do correctly you really have to collect, to label data collected, identify redundancy and noise, pre-processing the data, get certain trends, get certain data in places before you allow the machine to learn.<\/p>\n\n\n\n
Today with a powerful GPU, it give you tremendous power in machine learning model, for much faster and performance. All the major companies, the Google, the Microsof, the Facebook, the Amazon, they all move very quickly into GPU to train machine learning models. For example, Google’s Tensor Processing Unit (TPU) can help you to accelerates of your machine learning activities using certain Google’s TensorFlow, which is major parts of this course.<\/p>\n\n\n\n
So today all of the major cloud platforms, the Amazon, the Microsoft’s Azure, the Google Cloud Platform, they provide access to GPU array for training and learning machine. So you can still using these clouds service companies to run your machine learning and to run things without have to build the own sever and own computing systems.<\/p>\n\n\n\n
And so in this class, in the next 20 classes or so we will focus on the platform, the layer and the tools that Google allows you to use a Tensor Processing Unit. In this course, you learn about AI tools, the platform using Google cloud based data store that has a huge of data to train such machine learning models and then transform the data for analysis and predicting as well as the Google visualization tool to display the results.<\/p>\n\n\n\n
Then I hope that by following our sequences of courses you be able to have, to develop your own skills in AI and machine learning. Thank you very much. Have a nice day.<\/p>\n","protected":false},"excerpt":{"rendered":"
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