How is going on my ML/ Data Science journey?

( Source: )


First of all, as someone who is at the very beginning of the road, I would like to mention this: how i could not start this road ?

So, who am I?

I have been working as a software business analyst for about 5 years. My interest in data science for 5 years has now triggered my desire to do this professionally. I have to admit that it is not easy to change the sector in terms of my work intensity, continuing master’s degree and other daily hassle. You cannot be disciplined enough for a new adventure.

In addition, there are many points where your enthusiasm is discouraged when you are just starting the road. As you do research, you see the depth of the subject and this can intimidate you.

You are asking yourself the question: What if I don’t be successful?

A path you don’t already know and a world where you get lost while doing research! That’s why I got scared and run away for a long time and postponed it all the time. Until now!

If you’ve decided, let’s get started now!

Above all, we need a resource that can be a Roadmap and get an idea in small steps without getting too overwhelmed. Online trainings and blog posts in a simple level shed light on our way.

So is it enough?

What are you trying to reach at the end of the road?

Here is the answer to this determines our road map. I want to share what I did while I hadn’t found the answer yet.

Where did I start?

  • I have followed the blog posts and linkedin accounts of many people who have been doing this for about 2 years. In this way, I see the posts that each one likes, the more information I get about data science.
  • After getting familiar with the terms, I followed domestic and international job postings. My aim here was to learn what the expected competencies in this field are in the sector. Be sure, terms, job postings, projects become more familiar and interesting after little time.
  • After gathering enough information, I started free online training.
  • I created a list of minimum topics that I should learn, blending job postings, blog posts, and the competencies of the data scientists I followed.
  • I followed courses that would be considered an introductory / intermediate level, almost without going too deep for each. I’ve completed a few tutorials I found from Udemy and Coursera.

Here I would like to mention one point, I listened to trainings only once without practicing. After that, in another tutorial I continued by applying practices. In this way, my work has become more enjoyable and faster as I am familiar now while applying the practices…

What happened next?

Unfortunately, after the training and many things I researched on the internet, I haven’t been able to develop an end-to-end project yet. Since I did not have a road map, I got lost in the pool of knowledge I had accumulated through my own efforts.

I think everyone agrees that practical application is the best way to learn a job. For this reason, I thought that practical oriented face-to-face training would be useful. Thus, being on this path with an experienced trainer would give me more confidence.

Finally, our paths have crossed with Data Science School.

I started my education that will continue both theoretically and practically with the education that will continue until my Master’s Graduation Project. Im planning to do my Master’s Graduation Project within the scope of data science project. My education started at the beginning of August.

It took me almost 1.5 years to act…

I believe that instead of getting lost in the internet world, it is necessary to set a good road map and work from simple to discipline.

Starting today i have a roadmap for data world which i have dreamed so far.

I will be sharing my road map , see you in next post!

Business Analyst | Data Science Bootcamp Student @VBO | Data Science and ML Researcher

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