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Data Science

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Data Analysis

Data Analyst Resume Rejected? I'll show you a portfolio that actually works

Are you knocking on the door of employment, but finding it difficult? As a non-major humanities graduate and academy completer, I will share the "portfolio that actually works" which I used to break through and open the doors to employment after months of trial and error.

(4.6) 29 reviews

174 learners

Level Beginner

Course period Unlimited

Python
Python
SQL
SQL
MySQL
MySQL
Python
Python
SQL
SQL
MySQL
MySQL

Reviews from Early Learners

Reviews from Early Learners

4.6

5.0

로로

82% enrolled

Hello, I am a student seeking a career in data analysis. Thanks to your lectures, I am nearing the completion of my portfolio. I was feeling quite lost about how to approach it, but I feel like I've finally found my way, so thank you very much. Would it be alright if I sent you an email to ask for some brief advice regarding the structure before I finalize my portfolio? I will leave my email address in a reply. I would truly appreciate it if you could get in touch when you have a moment!! :)

5.0

kimhj4355

100% enrolled

I'm interested in data analysis and preparing for job hunting. Through this course, I was able to get a sense of what a portfolio should look like. If possible, I would like to ask if I could have a coffee chat or communicate via email with you..!

5.0

박재완

100% enrolled

It was a special lecture on portfolio building for excellent Data Scientists, and for those preparing not just for Data Scientist but also Data Analyst roles, it was an incredibly cost-effective lecture where, for the price of coffee, you could grasp what a current professional considers a well-crafted portfolio. Personally, I'd like to send an email and have a coffee chat with the instructor... Is there no way to find out their email address...

What you will gain after the course

  • When applying for entry-level data analyst positions, you can find out what constitutes a "winning portfolio."

  • Portfolio creation methods that help non-majors get hired quickly

  • Preparing for Data Analyst Technical Interviews

Is the 'Data Analyst' career just an illusion for non-majors, humanities graduates, and academy completers? 🤔

I entered the data analyst job market at age 31 and got hired, so it's not an illusion!

At the time I jumped into the job market, my specs were like this😑

College? Just a liberal arts graduate

Career after graduation? 4 years of liberal arts office work (virtually a "water career" that wasn't even remotely related to data..)

Education for data analysis? 6 months at a government-funded academy


When I suddenly said I was going to quit my office job to become a data analyst, everyone around me said the same thing.

💭"Changing careers after thirty? It's tough, especially at your age."

💭"They say you can't get a job unless you have a master's degree. It'll be hard to even pass the initial screening."

But I just did it anyway. Because,

"Oh, because I want to be a data analyst!"

<But here is my job hunt failure story>

I boldly declared my goal and applied to nearly 40 places, but news of passing the resume screening? Only two spots. (And even those were a bit strange...)


(These are just the records from Wanted... My applications on other platforms before May were also a parade of document rejections.. ^^ Wow.. really..)

saying I would become a data analyst

I told my parents and let all my acquaintances and friends know, but including the academy course period (6 months) and the period of constant document rejections (3 months), I spent quite a long time as a gloomy, unemployed person. 😥

At that time, I would walk around the neighborhood to try and get rid of the depression, but around quitting time, my friends' group chat would be filled with talk about their companies and work...

And when I came back to my room, I'd think, 'What am I even doing..?' and feel depressed all over again. It was a repeating pattern. (I even got stress-induced gastritis back then.. haha😂)

After completing the academy, every single day was depressing during the period when I couldn't even pass the initial document screening.

"What on earth is the problem.."

After spending 2-3 months in this state,

I had a strong feeling that the reason things weren't working out to this extent wasn't just because of my specs.


'I'm a non-major and an academy graduate, but if you hire me, I can definitely do "this much"'—maybe that's what's missing from my portfolio. My portfolio is the only thing I have to show...😯

It was because I kept having these thoughts.


Anyway, I knew I had to revise my portfolio, but I just couldn't get a feel for how to do it.

But I couldn't just stop there,

I kept looking through well-made data analysis materials on overseas sites,

I started getting hints by looking at the patterns in their analytical writing.


As soon as I realized it, I applied it to my portfolio immediately.

Once I felt confident in my portfolio, I applied to about 10 places I wanted to go, and more than 90% of them sent me news that I had passed the document screening.

<After Portfolio Changes>

JANDI_Screenshot_2025-03-17 15.46.21

Since it's been a while since I passed, I've only brought what's left on my phone and email. I didn't blur out well-known or large-scale companies.

✅<So, the story of my successful job hunt>

The reason I, someone with no impressive credentials to speak of, was able to successfully transition into a technical IT role in the STEM field as a data analyst is that I deeply realized the importance of a "portfolio."


At first, I was dazed by the continuous stream of notifications that I had passed the document screening, but

Later, as I looked at the portfolios of new applicants at our company and provided portfolio consulting for aspiring non-major data analysts from the outside, I became increasingly convinced that the method I realized was correct.


The reason why I had virtually zero document screening passes for 2-3 months

I have come to my own conclusion that it was because "I presented a portfolio that was impossible to evaluate."

I, too, just like everyone else,

Even though I submitted my portfolio structured as Data Analysis Goals -> Preprocessing -> Visualization -> Machine Learning Modeling -> Conclusion, I failed every single application.

The structure of the portfolios that passed and those that failed were similar, but the problem lay in a completely different place.

There is a clear distinction between a portfolio that can be evaluated and one that cannot be evaluated.

So, I am sharing these tips with you.

First. Portfolios that can be evaluated

Second. A highly rated portfolio


This course is more tailored toward job seekers who are non-majors.

📢 Especially why non-majors should take this course.

  • I review resumes for entry-level data analyst positions and provide portfolio consulting for non-majors in large communities. I can confidently say that I have reviewed over 300 entry-level data analyst portfolios to date.

  • Usually, data analyst portfolios are similar. Only one in a thousand stands out, while the rest are indistinguishable, so to put it simply, they are all pretty much the same.

  • If all portfolios are of equal value, they will hire the major who receives additional points for their credentials.

  • Therefore, non-majors with relatively weaker credentials must compete with a "portfolio that can be evaluated" differently from others in order to get hired!


This course is not difficult at all.😎

This is not a lecture about how to do machine learning more brilliantly or how to increase accuracy.

Therefore, anyone preparing for a job as a data analyst can take this course.

Additionally, I will even provide tips on how to handle interviews after passing the document screening!

The reason I am posting this lecture at this price is,

I have been running a free portfolio consulting post for aspiring data analysts for 3-4 years, and many of them sent me coffee gift icons as a token of gratitude after getting hired. So, the price is roughly around that amount... (considering the commission paid to Inflearn...() )


However, please do not take this course if you fall into these categories ❌❌

  • Those who want to "become interested" in the data analyst profession. (This course is for those who already know what data analysis is and have decided to start as a data analyst. It is not a course designed to spark interest in the profession.)

  • Those who have already passed the document screening 3 or more times with their own portfolio. (Since you have experience passing with your own method, you don't necessarily need to take this course.)


  • Those who have not studied data analysis-related languages at all. (You need to at least know what machine learning is.)

  • Data analysis job seekers in fields that do not involve machine learning (this lecture emphasizes machine learning)

Recommended for these people

I'm not confident because I'm a non-major

I want to become a data analyst, but
everyone around me just says "it's not possible."

I don't know what's wrong
I made a portfolio, but I get rejected every single time I submit it.
I don't even get a chance to interview.

Preparing a portfolio is so overwhelming
Since it's my first time applying for an IT technical position,
I have no idea how to go about creating a portfolio.


After taking the course,

  • You can find out what kind of portfolio hiring managers are looking for.

  • No matter how poorly it is made, you will at least learn what a portfolio that is "worthy of evaluation" looks like.

  • As a non-major, you can learn how to respond to questions you might receive during an interview.

Prerequisite Knowledge

  • Basic programming grammar knowledge (Python, SQL)


  • Basic knowledge of how to run machine learning


Recommended for
these people

Who is this course right for?

  • A job seeker who needs to create a portfolio but has no idea where to start.

  • A job seeker who doesn't know how to appeal to employers as a non-major.

  • Job seekers who are afraid of everything from document screening to technical interviews

Need to know before starting?

  • python

  • sql

Hello
This is finishup

174

Learners

29

Reviews

4

Answers

4.6

Rating

1

Course

  • 2020.04 - 2021.06 : Unemployed for one year at age 30 to transition careers to data analyst

  • 2020.09 - 2021.02 : Completed a government-funded data analysis bootcamp at age 31

  • 2021.03 - 2021.06: Job hunting for 3 months (got sick from stress..)

  • 2021.07 - Present: Currently in my 4th year as a Data Analyst (Data Scientist) at my first company, consistently involved in the hiring process from reviewing resumes to conducting interviews for data analyst positions.

  • At the same time, I have been running a career advisory blog for aspiring data analysts for 4 years.

More

Curriculum

All

22 lectures ∙ (58min)

Published: 
Last updated: 

Reviews

All

29 reviews

4.6

29 reviews

  • qorrl1231344님의 프로필 이미지
    qorrl1231344

    Reviews 1

    ∙

    Average Rating 5.0

    5

    100% enrolled

    Thank you for the good lecture. It was very helpful.

    • kimhj43550073님의 프로필 이미지
      kimhj43550073

      Reviews 1

      ∙

      Average Rating 5.0

      Edited

      5

      100% enrolled

      I'm interested in data analysis and preparing for job hunting. Through this course, I was able to get a sense of what a portfolio should look like. If possible, I would like to ask if I could have a coffee chat or communicate via email with you..!

      • finishup
        Instructor

        Yes, that's possible ^^ If you leave your email address here, I'll reply to you via email!

      • kimhj43550073

        Yes, thank you! It's kimhj4355@naver.com!

      • finishup
        Instructor

        I've sent you an email!

    • vhamair4942님의 프로필 이미지
      vhamair4942

      Reviews 1

      ∙

      Average Rating 5.0

      5

      100% enrolled

      I am preparing to apply to a specialized graduate school for Artificial Intelligence and Data Analysis. Despite being a current professional in a data analysis team, I had many concerns about preparing my application documents, but it seems this lecture helped me find my direction. Thank you.

      • rororo님의 프로필 이미지
        rororo

        Reviews 1

        ∙

        Average Rating 5.0

        5

        82% enrolled

        Hello, I am a student seeking a career in data analysis. Thanks to your lectures, I am nearing the completion of my portfolio. I was feeling quite lost about how to approach it, but I feel like I've finally found my way, so thank you very much. Would it be alright if I sent you an email to ask for some brief advice regarding the structure before I finalize my portfolio? I will leave my email address in a reply. I would truly appreciate it if you could get in touch when you have a moment!! :)

        • finishup
          Instructor

          I've sent you an email! ^^

      • pjw2505505님의 프로필 이미지
        pjw2505505

        Reviews 1

        ∙

        Average Rating 5.0

        5

        100% enrolled

        It was a special lecture on portfolio building for excellent Data Scientists, and for those preparing not just for Data Scientist but also Data Analyst roles, it was an incredibly cost-effective lecture where, for the price of coffee, you could grasp what a current professional considers a well-crafted portfolio. Personally, I'd like to send an email and have a coffee chat with the instructor... Is there no way to find out their email address...

        • finishup
          Instructor

          I'm glad my lecture was helpful to 박재완님, and thank you for your heartfelt course review! 😁 Currently, due to personal commitments, I cannot do coffee chats. However, if there's anything you need help with, we can communicate via email. But if I leave my email address here, I might receive random mentoring requests. So, if you leave your email address here, I will contact you via email when I have time! (You can delete your email address later)

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