How to Build Machine Learning Skills for All Employees in Your Company

Everybody loves Artificial Intelligence and Data Science (DS) and that is likely to continue for the next ten years. Most people don’t know much about data science and the capabilities of machine learning and AI algorithms.

This is a very common phenomenon in every field of expertise. You might ask yourself: Do you know what DevOps (Network Operation Center), Support, or NOC (DevOps) really do? Yes, technology professionals can explain it better than those who aren’t in the industry. However, it is often difficult to understand what others do if it hasn’t been done before.

This would usually be fine in most cases. Although it is nice to have knowledge from other areas of expertise, you can still manage your life well enough without all the details. You might find that the extra knowledge you acquire is not helpful in many cases. However, Data Science is very different than the examples I have just given because data is everywhere.

Data science and data-driven decision-making are easier than ever. Data-driven decision-making can be used by every department of an organization. DevOps can make use of Machine Learning (ML), to analyze their pipelines and identify anomalies. Support can use clustering algorithms for similar customer requests to reduce their workload. Network Operation Center can also use anomaly detection algorithms, to detect problems in networks. We believe everyone can benefit from DS so we created a way for every employee to be able to use data science skills to empower them and share our love of data science.

Data Science Workshop Goals

We created a workshop to help anyone who has basic Python skills quickly grasp DS and understand how it works.

The following goals were set by us:

• We can provide “Data Science Ambassadors” outside our team with tools, a basic understanding of Data Science, and the ability to work with them.
• So that “ambassadors”, can be “on the job”, and keep the training short and effective.
• Spread awareness about data-driven decision making, and explain the benefits of it

These goals would be achieved with the following agenda

• Explain ML and the basics of algorithms
• Demonstrate your ability to spot machine-learnable issues
• You will be able to practice ML with Python and Sklearn.

We thought that an online DS course was possible. We did find many online courses but none that we liked for the reasons listed below.

• We were able to cover as much information in our short courses as possible, but very few courses do.
• Many courses are not meant to be taught in a class. They are designed for individuals to learn by themselves.
• Math and statistics weren’t prerequisites for the workshop. Therefore, we needed theoretical explanations about ML models that could easily be understood by everyone

Originally published on The Tech Trend