Data Science Upskilling Bootcamp

A new and interesting trend is emerging as teachers from all over the world embrace virtual training. It opens many opportunities for both facilitators and knowledge-seekers from different continents and time zones. Training formats are changing too, as there’s no need to hire a venue and sessions can be shorter and better tailored to an audience’s attention span. Our world is changing and with better internet speeds we can now learn from any expert in the field, if they are happy to share their knowledge.

The recent WADSIH/Halliburton Data Science Bootcamp was the first virtual training event I’ve ever attended. For one week, Dr Satyam Priyadarshy and his team of scientists were guiding us through the world of data science, machine learning, the use of neural networks, and artificial intelligence. The unusual factor was that they were doing so from different parts of India.

On the first day of training, Dr Priyadarshy quoted the ancient parable of the Blind Men and an Elephant to help us understand fundamental data science and machine learning concepts.

The parable of the Blind Men and an Elephant can be dated back to the Buddhist text Udana 6.4, around 500 BCE.

So, how do we make sense from the sheer volume of data that is collected nowadays? What are the best ways? It can be very hard to see the big picture when one is overwhelmed by data coming just from one strategy or process in an organisation.

That’s where data science algorithms and tools come in – to find patterns and reveal how seemingly separate processes influence each other. Machine learning allows us to look at multiple variables and predict behaviours.

In this workshop we used Jupyter Notebook, accessible through Anaconda – a scalable data science platform. Because it is browser-based, I could verify each line of python code straight away. I was quite surprised how easy it was to remember syntax and to grasp the content of each learning module. Soon I was looking forward to each of the three-hour coding sessions.

We used python modules to predict trends and derive patterns from seismic data. Neural networks and machine learning algorithms were explained, demystified and illustrated through experience. And to my surprise it was fun! I look forward to implementing this new knowledge in future Gaia projects.

If you’d like to know more, feel free to reach out and see what Gaia Resources can do for you in this rapidly developing space. Comment below, contact me at barbara.zakrzewska@archive.gaiaresources.com.au, or start a chat via Facebook, Twitter or LinkedIn.

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