{"id":8814,"date":"2020-05-20T13:42:55","date_gmt":"2020-05-20T11:42:55","guid":{"rendered":"http:\/\/www.ie.edu\/exponential-learning\/blog\/?p=8814"},"modified":"2020-05-20T13:42:55","modified_gmt":"2020-05-20T11:42:55","slug":"bootcamp-diary-paula-kurylowicz","status":"publish","type":"post","link":"https:\/\/www.ie.edu\/lifelong-learning\/blog\/data-science\/bootcamp-diary-paula-kurylowicz\/","title":{"rendered":"Reaching a Personal Milestone | Bootcamp Diary by Paula Kurylowicz"},"content":{"rendered":"

So, where do I begin?<\/strong><\/p>\n

This was the same question I asked myself a while back when considering data science for the first time. Back then, I did not have a good understanding of what being a data scientist really meant. I understood the job as having two extremes: working with spreadsheets by using SQL and Python on one hand, and trying to solve intelligence through the development of AGI systems on the other.<\/p>\n

I always wanted to do the latter, but this felt too big a dream to ever become realistic. How does one jump from SQL to AGI? <\/em>I constantly asked myself this, as it was something that didn\u2019t feel achievable.<\/p>\n

However, someone once said that if you want to get from point A to point B and it\u2019s dark outside and the distance seems overwhelming, you don\u2019t really need to see the entire path right away. Visibility of less than a few meters is more than enough for you to move forward. Eventually, you\u2019ll arrive at your destination.<\/p><\/blockquote>\n

About half a year ago, I applied for a scholarship to take part in the Data Science Bootcamp\u2014it felt like the right way to get involved in this field. I had a lot of hope and a little bit of faith. But I\u2019ve made it here to Madrid, and to the Bootcamp.<\/p>\n

It\u2019s been almost two months since I took my dog and suitcase and headed out on a crazy two-day trip by car toward sunny Spain, leaving not-so-sunny London behind. I knew it wasn\u2019t an easy undertaking, especially since I\u2019ve decided to keep working remotely and full time for one of today\u2019s fastest-growing fintech companies. But I had no idea what would happen after.<\/p>\n

At the beginning, everything was difficult. Looking for an apartment was not easy. Not knowing the language was hard. And getting into a study and work routine proved even harder.<\/p>\n

But wrapping my head around the initial material in the course was probably my biggest challenge.<\/p><\/blockquote>\n

I couldn\u2019t\u2014and I still can\u2019t\u2014get rid of a feeling that I am not doing enough to get the best out of this course. I keep dreaming about coding and math every night, as it all can be quite overwhelming. But it\u2019s also amazing and fun. I love it.<\/p>\n

Even though it seems like it\u2019s not a lot of time to truly get to know data science, I do feel like it\u2019s been ages since I typed in my first line of Python code and saw my first equation on the Math and Stats slide. The course is so intense that it throws you right into the middle of it all.<\/p>\n

I can\u2019t tell you how good it feels to see your code running and producing real-world results after hours of editing it and trying to crack a problem, or how satisfying it is to finally make sense of all of these equations in Math and Stats. But the best feeling comes from all the moments in between, when I realize how this new and exciting chapter of my life is being written right now.<\/p><\/blockquote>\n

Being here is a real challenge. It takes a lot of discipline and focus, but it\u2019s very rewarding at the same time\u2014we all know why we\u2019re doing it!<\/p>\n

I\u2019m confident that by being here, I am getting closer to my goal of working with AGI.<\/p>\n

And you know what they say: \u201cYou can get wherever you want, but every journey starts with a single step.\u201d This Bootcamp may be a small step, but it\u2019s truly a personal milestone.<\/p>\n

Now it\u2019s your turn. What is your next step going to be?<\/p>\n","protected":false},"excerpt":{"rendered":"

So, where do I begin? This was the same question I asked myself a while back when considering data science for the first time. Back then, [\u2026]<\/span><\/p>\n","protected":false},"author":4,"featured_media":8819,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[384],"tags":[],"_links":{"self":[{"href":"https:\/\/www.ie.edu\/lifelong-learning\/blog\/wp-json\/wp\/v2\/posts\/8814"}],"collection":[{"href":"https:\/\/www.ie.edu\/lifelong-learning\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.ie.edu\/lifelong-learning\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.ie.edu\/lifelong-learning\/blog\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/www.ie.edu\/lifelong-learning\/blog\/wp-json\/wp\/v2\/comments?post=8814"}],"version-history":[{"count":4,"href":"https:\/\/www.ie.edu\/lifelong-learning\/blog\/wp-json\/wp\/v2\/posts\/8814\/revisions"}],"predecessor-version":[{"id":8818,"href":"https:\/\/www.ie.edu\/lifelong-learning\/blog\/wp-json\/wp\/v2\/posts\/8814\/revisions\/8818"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.ie.edu\/lifelong-learning\/blog\/wp-json\/wp\/v2\/media\/8819"}],"wp:attachment":[{"href":"https:\/\/www.ie.edu\/lifelong-learning\/blog\/wp-json\/wp\/v2\/media?parent=8814"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.ie.edu\/lifelong-learning\/blog\/wp-json\/wp\/v2\/categories?post=8814"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.ie.edu\/lifelong-learning\/blog\/wp-json\/wp\/v2\/tags?post=8814"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}