Data Science vs Software Engineering: Which Bootcamp to Choose?

·Oct 06, 2022 09:17 PM

Curious on your thoughts - was discussing with a colleague which would be more useful for an ontologist looking to expand their skillset: data science bootcamp, or software engineering bootcamp. We couldn't really settle on a definitive answer so I thought I'd ask here and see if you all had opinions on this!

12 comments

· Sorted by Oldest

Donny W.
·
What’s the context? Is the ontologist “among” software engineers and feeling lacking? Or among data scientists and feeling lacking? In typical working contexts for me, it would be software engineering, hands down.
👍1
Nicole B.
·
That’s a good point. We were talking about it more from the perspective of, say we hire more ontologists and we want to offer them professional development paths or skill expansion opportunities, what ones would make sense.
Katariina K.
·
Learning to deploy software with kubernetes and other such devops principles were very useful to me, because that way I could understand what it takes to bring actual KG solution to production and it furthered my thinking. Data scientists also need to learn how to deploy their models, so if an ontologists learns about how to set up a triple store and deploy applications on top of it, I would find it very useful indeed for their career.
Ann
·
Donny W. I have the opposite response: data science for me, as I'm embedded in an AI team.
👍1
Nicole B.
·
Ann this is kind of how our conversation went .. I was saying I felt for me it'd be useful to know more about engineering and my colleague was talking about having been in a situation more like yours. Seems like no one-size-fits-all answer!
😆1
Ann
·
Sounds like you will need multiple development and learning paths.
Katariina K.
·
I think it is good to offer people options. For example, in my team, some domain experts are interested in deepening their skills in OntoClean, others in SHACL, the variety is what will make the team also stronger
🙌2
Eelke van der Horst
·
What about data engineering bootcamp?
👍1
Katariina K.
·
It is always great to be able to understand the relational database world and be able to talk to data engineers what becomes easier in graph dbs etc. Most engineers think in relational databases so a graph db capability is at first incomprehensible to them
👍1
Eelke van der Horst
·
Data engineering is not limited to the relational database world, being able to work with NoSQL databases (like triplestores, graphstores) is just as important. For instance, there's a NoSQL course as part of the Data Engineering curriculum at Coursera: https://www.coursera.org/learn/introduction-to-nosql-databases?specialization=ibm-data-engineer#syllabus
Eelke van der Horst
·
I think that data engineering skills like data wrangling, building ETL pipelines, data harmonization, data modeling, cloud deployment, scaling etc. are an ideal addition to ontology engineering skills when it comes to building and deploying knowledge graphs
Eelke van der Horst
·
Also, data engineering bootcamps include rudimentary coding which might already be a good start for ontologists aiming to expand their skills, where full-blown software engineering bootcamps might be an overkill.
👍2

Donny W.
·
What’s the context? Is the ontologist “among” software engineers and feeling lacking? Or among data scientists and feeling lacking? In typical working contexts for me, it would be software engineering, hands down.
👍1
Nicole B.
·
That’s a good point. We were talking about it more from the perspective of, say we hire more ontologists and we want to offer them professional development paths or skill expansion opportunities, what ones would make sense.
Katariina K.
·
Learning to deploy software with kubernetes and other such devops principles were very useful to me, because that way I could understand what it takes to bring actual KG solution to production and it furthered my thinking. Data scientists also need to learn how to deploy their models, so if an ontologists learns about how to set up a triple store and deploy applications on top of it, I would find it very useful indeed for their career.
Ann
·
Donny W. I have the opposite response: data science for me, as I'm embedded in an AI team.
👍1
Nicole B.
·
Ann this is kind of how our conversation went .. I was saying I felt for me it'd be useful to know more about engineering and my colleague was talking about having been in a situation more like yours. Seems like no one-size-fits-all answer!
😆1
Ann
·
Sounds like you will need multiple development and learning paths.
Katariina K.
·
I think it is good to offer people options. For example, in my team, some domain experts are interested in deepening their skills in OntoClean, others in SHACL, the variety is what will make the team also stronger
🙌2
Eelke van der Horst
·
What about data engineering bootcamp?
👍1
Katariina K.
·
It is always great to be able to understand the relational database world and be able to talk to data engineers what becomes easier in graph dbs etc. Most engineers think in relational databases so a graph db capability is at first incomprehensible to them
👍1
Eelke van der Horst
·
Data engineering is not limited to the relational database world, being able to work with NoSQL databases (like triplestores, graphstores) is just as important. For instance, there's a NoSQL course as part of the Data Engineering curriculum at Coursera: https://www.coursera.org/learn/introduction-to-nosql-databases?specialization=ibm-data-engineer#syllabus
Eelke van der Horst
·
I think that data engineering skills like data wrangling, building ETL pipelines, data harmonization, data modeling, cloud deployment, scaling etc. are an ideal addition to ontology engineering skills when it comes to building and deploying knowledge graphs
Eelke van der Horst
·
Also, data engineering bootcamps include rudimentary coding which might already be a good start for ontologists aiming to expand their skills, where full-blown software engineering bootcamps might be an overkill.
👍2