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- Data-analytiikka
Master´s degree in Philosophy of Science but Data Engineer by profession willing to teach efficiently (as I wish I had) Data Analytics and Data Engineering with serious career-relevant goal for studen
- Data-analytiikka
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I graduated from the University in 2016 with Master´s degree in Philosophy of Science, specialized in theories of scientific explanation and modeling. After that, I self educated myself first to professional Data Analyst and now professional Data Engineer. I have worked in my home country´s biggest bank and now in one huge international corporation as a Data Engineer.
As I mentioned, I self educated myself and without a mentor lost a lots of precious time learning technologies with no value in career and no one mentored me, what I should study, in what order and how so that is the main goal of mine: to be the teacher I never had.
All courses or learning paths I would create would be heavily based on background information and foundations, and the technology itself is to be mentored to an enterprise level. So this is no joke studying just for the sake of the concept.
I would start from basic programming with two languages for reason that students realize that the more languages you learn, the easier it gets. Basic programming would soon drift to Data Analytics and then I would mentor enterprise level skills in two languages of Data Analytics. Then I would introduce Database systems to the set. First only for the concept and query language but soon how to build complete Data Warehouses and keep all the Database relevant management systems and tricks on a high level.
After this, I would steer the programming languages to Machine Learning for every Data Analyst will in the end, end up to work with Machine Learning for in the end, they are just statistical tools that are self built for particular problems. Last section would be Business Intelligence reporting tools for visualize and control the whole data environment we have in our hands.
When I and the students feel confident, those who want to continue could follow me to jump from Data Analytics to Data Engineering. Teaching methods would be the same but then the amount of technologies starts to build up really fast. The subject is so vast that I am not going to place curriculum here but the idea is same as with Data Analytics.
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My intention is to teach as I wish I would have had the experience. We live in time where technology just increases as more systems to be learned increases almost monthly leads many learners to drown to new technologies with the cost of ending up with a poor fundamentals.
I carry the fundamentals constantly and in every course with me so no one will forget their importance, but also very aware and avid to keep students skill set more than enough for latest technologies and by my experience, I can do the screening, what is really worth to invest time and what not.
Typically course starts from understanding how we ended up in this technological innovation or solutions, what is the history behind these and so on. Then we would start to check not only how these technologies are installed or activated but for what reason they use setup systems they do. From this pre-introduction stage we would start from the very basics and something like 40% of the course is just honing the basics so that understanding is guaranteed. Last 60% is to build up the skill set to enterprise level. Lastly, I would create a project that is not obligatory but can be used in job applications and so on where these technologies are used in sync usually covering real-life problem and I continue to be mentor and support even though this project phase is not part of the particular course it is derived from.
Prerequisite information and skill set is different between courses but aim is career/enterprise level, but I would create courses so that students, following the curriculum, would always be ready for the next task.
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- 10h: 100€
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