Learning Data Science

I just completed the book "R for Data Science" and I want to share my thoughts on the book and the subject in general. The book is free and contains extensive hands-on examples. The integrated environment for performing the work, R Studio, is also free.

My initial motivation was to learn what the R programming language was all about. In the process, I discovered the field of Data Science, and in so doing have been amazed at the possibilities for this skill. I highly recommend developing it.

Below is a key image from the book, depicting the workflow of a Data Science task, which could be expressed as a R program script. Import raw data, perhaps from an IoT device. Tidy the data to make it accessible. Then iteratively analyze the data to Understand the key messages contained within it. Finally, Communicate the findings to humans who need it.

You may now be thinking: this is great but you're a manufacturing guy, so what does this have to do with Manufacturing Operations Management? I'll tell you:

Somewhere between the data coming off the shop floor and the AI systems which will help us to use it is a human who is tasked with training the AI model. To train the model you need to Communicate to it your Understanding of the Data (I'm working backwards towards the data source in the image above.)

How do you understand the patterns and lessons within the data? Through a discovery process. This journey requires skills and tools. A key tool is the R programming language and key skills are knowing what questions to ask and how to express them in the language.

Here, I have only scratched the surface of a big field, but I've found a great starting point for further exploration.

If you're a human who wants to be highly valuable in the future, then knowing Data Science is a great way to a secure future in this new age.

If I were just now starting my career, rather than having just finished it, this is the direction I would take. I'd advise any interested young person to take a look at Data Science as a career.