Identify Problems with Artificial Intelligence - Case Study
What you'll learn
- Identify anomaly within several similar objects
- Apply Unsupervised Machine Learning algorithm kmeans
- Develop and deploy ShinyApp
- Apply Version Control to your projects or activities
- Re-use provided template and course exercises in R and ShinyApp
- Use Deep Learning Autoencoder Models to Detect Anomalies in Time-Series data
- Create a System that Supervises Industrial Process and helps Process Operators to detect anomalies
- Computer with Internet connection
- Mac or PC
- R Statistical Software, R-Studio
- Version Control Software e.g. Github for Desktop [recommended]
- Installed Java on your computer
Inspired by Albert Einstein [1879-1955]
Learn how to identify anomaly within several similar objects with Artificial Intelligence
Working with time-series sensor generated data
Understand how Unsupervised Machine Learning Algorithm works using real life dataset
Learn developing in R and ShinyApp with a possibility to better explore the data, instantly deploy your project
Explained use of Version Control to be organized and save time
Practice with real life generalized Dataset coming from Manufacturing!
Versatile method is presented using a Case Study approach.
This method helped to discover real life inefficiency and to solve the problem!
Start with R here! Step by step introduction with examples and practice
Basic understanding on Time-Series data manipulation in R
More approaches of Anomaly Detection including Deep Learning on h2o framework is covered in the course
Practical Developing the idea of Industrial Process Control with Artificial Intelligence with DEMO Shiny Application included
Course video captions are translated to [Chinese-Simplified, Hindi, German, French, Italian, Portuguese, Turkish, Spanish, Malay, Indonesian, Russian] languages
Problem-solving in Manufacturing is usually perceived as a slow and boring activity especially when many possible factors involved. At the same time it's often common that problems going on and on unobserved which is very costly. Is it possible to apply Artificial Intelligence to help human to identify the problem? Is it possible to dedicate this boring problem solving activity to computer? Apparently yes!!!
This course will help you to combine popular problem-solving technique called "is/is not" with Artificial Intelligence in order to quickly identify the problem.
We will use data coming from four similar Machines. We will process it through the Unsupervised Machine Learning Algorithm k-means. Once you get intuition understanding how this system work You will be amazed to see how easy and versatile the concept is. In our project you will see that helped by Artificial Intelligence Human eye will easily spot the problem.
Course will also exploit different other methods of Anomaly Detection. Probably the most interesting one is to use Deep Learning Autoencoders models built with help of H2O Platform in R.
Using collected data and Expert Knowledge for Process Control with AI:
In this course we will build and demo-try entire multi-variables process supervision system. Process Expert should select dataset coming from the ideally working process. Deep Learning model will be fit to that specific pattern. This model can be used to monitor the process as the new data is coming in. Anomaly in the process then can be easily detected by the process operators.
Ready for Production:
Another great value from the Course is the possibility to learn using ShinyApp. This tool will help you to instantly deploy your data project in no time!!! In fact all examples we will study will be ready to be deployed in real scenario!
You will learn R by practicing re-using provided material. More over you can easily retain and reuse the knowledge from the course - all lectures with code are available as downloadable html files. You will get useful knowledge on Version Control to be super organized and productive.
Join this course to know how to take advantage and use Artificial Intelligence in Problem Solving
Who this course is for:
- Anyone willing to be more advanced in Complex Problem Solving
- Production Supervisor or Process owner in Manufacturing
- Data Analyst
Hello, I am really excited that you read my little story here!
I am a Chemical Engineer by education, Problem Solver by nature and Instructor by hobby. I currently work in Swiss Multinational Company as Senior Engineering Specialist in R&D. I like to learn and apply modern technology to gain value. I believe that it is very important to always learn new technologies and apply them to reduce inefficiencies by finding complex patterns or applying new methods to close gaps.
In my public educational projects I would like to bring some ideas on how to apply computing power to be more productive. How to collect data in a smarter way using simple tools, how to analyze data to take a decision, and … why not to automate the decision using Artificial Intelligence? I will try to cover very practical side of technology, show how to benefit from it with concrete examples.
p.s. I will try my best to provide the best possible learning experience. If it would not be the case I would be very happy to receive any constructive feedback on how can I be better.