This is a data science career roadmap lecture that shares insights gained through trial and error as a non-major. You can optimize your career preparation time and process without wasting time or effort.
Reviews from Early Learners
5.0
johnnyljh
I took a weekend and finished it all. It was so concise and organized information about data science careers that I was able to save time searching here and there. The most impressive thing was that the major or job I have been doing is not necessarily disadvantageous to becoming a data scientist. I think the key is to find your own unique selling point and how to integrate it into the field of data science. Thank you for the great lecture :)
5.0
양키
I listened to the lecture well. The instructor organized it neatly and clearly, so it was organized in my head and absorbed well. They say that the job of data scientist is popular and in high demand, but I didn't know what specific skill sets I should build. After listening to the instructor's explanation, a roadmap was drawn up. ㅎㅎ However, if I had to choose something that was a bit disappointing in the lecture, I think it would have needed a little more specific explanation... For example, in order to understand a data science career, you said that you need to set a data science career goal and study efficiently to achieve the goal, but I felt like there were some specific examples or explanations missing throughout the lecture. Other than that, it was really well organized and good! Thank you!!!
5.0
Sean Yeon
thank you
My unique selling point as a non-major
A precise understanding of data science and careers
Skillset for achieving data science career goals
Study methods for building your skill set
Are you a non-major or someone without a background in data science who wants to start a career in the field? I have prepared this for you. This course is a data science roadmap lecture that provides study methods and direction on how a non-major can become a data scientist.
As a non-major from a liberal arts background, I successfully transitioned into a data science career and am currently working as a data scientist in the UK. Recently, I have been building my data science career by running a YouTube channel and data science projects. I will share practical methods on how to effectively enter a data science career path that might otherwise seem vague.
My lecture is an investment that will eliminate wasted time and effort. By following the course closely, you can learn the insights I gained through trial and error, allowing you to enter the field of data science effectively and more quickly.
Because I was once a non-major myself, I understand the frustration, difficulties, worries, and concerns of preparing for a career in data science better than anyone else. Based on the insights I gained through my own experiences and trial and error, I will share practical methods to help you shorten your career preparation time and optimize the process.
Are you wondering if you can do it even as a non-major? No matter what subject you majored in or what background you come from, anyone can complete a data science career roadmap that is right for them.
At the end of each chapter, we provide practice exercises that allow you to apply the lecture content to your own situation. By solving these exercises, you will have the opportunity to reflect on what you have learned and find the answers that are right for you. In particular, the practice exercises include specific examples based on my actual experiences to help you apply the concepts effectively.
• You can turn your non-major background into your own "Unique Selling Point" that makes you stand out compared to other competitors.
• You can accurately understand what data science is and set your own data science career goals considering your situation and preferences.
• Identify the skill set required to achieve your career goals and learn in detail about study methods to build that skill set.
• We help you reduce trial and error and optimize your preparation time and process.
Learn why your major can be an advantage for a career in data science, and create your own Unique Selling Point (USP) based on your background to gain an edge in the job search process.
Gain a precise understanding of data science and its career paths, and set data science career goals that are right for you, taking your background and situation into account.
Identify the skills required to achieve the goals you have set.
Learn the study methods to complete the skill set you need and establish a plan.
Course reviews from the first week of opening
🙋♂️ Can non-majors take this course?
A-1. Yes. My lecture is designed for those who have no background knowledge in data science but wish to enter a data science career. Even if you already have some prior knowledge of data science, if you feel overwhelmed about how to start preparing for your career, this lecture will help you prepare for it efficiently.
🙋♂️ Is there anything I need to prepare before taking the course?
A-2. There is nothing you need to prepare in advance, but an active attitude is required to utilize the lecture effectively. Instead of just passively listening to the lecture, think about the content yourself by solving the practice problems I provide in each chapter. By applying the practice problems to your own situation and finding the right answers, you can complete a roadmap that fits you.
🙋♂️ What are the benefits of taking this course?
A-3. Based on the things I realized through my long journey and my firsthand experience as a non-major, those taking this course can optimize their career preparation time and process.
Notes
I am currently working as a data scientist in the UK, and prior to moving to the UK, I completed my undergraduate and master's studies at Korea University. Personally, I run a data science project called "VisualisingKorea (https://visualisingkorea.com)." In 2020, under the name VisualisingKorea, I won first place in the 'Corona Data Visualization AI Competition' hosted by Dacon, which is often referred to as the Kaggle of Korea. In 2019, an article published by VisualisingKorea was also selected as a finalist for the Data Visualization of the Year award at the Data Journalism Awards.
Although I am currently active as an experienced professional in the field of data science and run a YouTube channel about data science (https://www.youtube.com/c/visualisingkorea), five years ago, I was also a non-major from a liberal arts background preparing for a career in data science.
Because I was a non-major myself, I understand very well what aspects are frustrating and worrying when preparing for a career from a non-technical background. To ensure you don't waste time like I did and can instead utilize your preparation time efficiently and optimize the process, I want to share everything I learned through trial and error. This includes things I realized while preparing as a non-major, things I regret not knowing sooner now that I am an experienced professional in the data science field, and above all, things that would have shortened my preparation time had I known them then. I aim to deliver all of this to those who are standing at the same crossroads.
Even if you are a complete beginner or a non-major with no prior knowledge of data science, I hope that by following my lectures, you will learn how to effectively prepare for a data science career without wasting time or effort, unlike how I missed various opportunities by wasting time.
Who is this course right for?
A beginner new to data science
A non-major who has never studied data science or related fields.
A humanities major who is afraid of programming languages or mathematics
Those who know what data science is but feel lost on how to prepare for it
Need to know before starting?
No prior knowledge is required, but an active attitude to apply the course content to your own situation is necessary.
All
31 lectures ∙ (2hr 25min)
All
40 reviews
4.4
40 reviews
Reviews 3
∙
Average Rating 5.0
5
I took a weekend and finished it all. It was so concise and organized information about data science careers that I was able to save time searching here and there. The most impressive thing was that the major or job I have been doing is not necessarily disadvantageous to becoming a data scientist. I think the key is to find your own unique selling point and how to integrate it into the field of data science. Thank you for the great lecture :)
That's right! You understood the content of the first chapter exactly :) I was also able to get my first job by using my background. I hope you will make good use of johnnyljh's unique selling points and get good results. Thank you for your positive review :)
Reviews 1
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Average Rating 5.0
5
As a non-major, I wanted to see someone who had succeeded in a similar environment, and thanks to this, all the things I was curious about and wanted to know were resolved. The content was organized easily, so it was easy to understand, and the practice problems were especially helpful. As a non-major, I was at a loss, but this lecture was perfect for me! I will prepare diligently as I have learned and succeed like the instructor! Thank you for creating a great lecture.
I think one of the difficulties of preparing as a non-major is that it is difficult to find people who have succeeded in similar environments. I am very proud that the parts you were curious about have been resolved! I hope you will prepare diligently as you have learned and have good results :)
Reviews 7
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Average Rating 4.6
5
I listened to the lecture well. The instructor organized it neatly and clearly, so it was organized in my head and absorbed well. They say that the job of data scientist is popular and in high demand, but I didn't know what specific skill sets I should build. After listening to the instructor's explanation, a roadmap was drawn up. ㅎㅎ However, if I had to choose something that was a bit disappointing in the lecture, I think it would have needed a little more specific explanation... For example, in order to understand a data science career, you said that you need to set a data science career goal and study efficiently to achieve the goal, but I felt like there were some specific examples or explanations missing throughout the lecture. Other than that, it was really well organized and good! Thank you!!!
Hello Yankee! I am glad that you have achieved the purpose of the lecture since you have drawn a roadmap :) If there was a part that was difficult to understand due to a lack of specific explanation, please leave a comment in the Q&A section! I will try to supplement the explanation. Thank you for your positive review :)
Reviews 1
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Average Rating 5.0
5
Whether you are a major or not, I think this is a must-have lecture to save your time. Because it fits the reason why the lecture was created. (Purpose of the lecture: To shorten the preparation time and provide an efficient preparation process for students to obtain a job in data science by providing organized information on the parts that the instructor was confused about while preparing for data science.) Personally, in the last stage, I think it would be better if the instructor shared the links that he recommends or is already subscribed to, although each student has a different desired career in relation to specialized books and newsletters/blogs. Thank you for the great lecture.. I listened to it all at once today and haven't been able to answer all the practice problems yet, but I don't think I will study anxiously without a clear roadmap. Thank you again for providing a great lecture!! ㅎㅎ If I have questions while sailing.. I will ask..ㅎㅎ Thank you!!
Hello, Arumnim, I am so happy to hear that the lecture was helpful! :D The list you mentioned is different for each individual depending on their curriculum goals, so I did not recommend it, but I think sharing links can be helpful. I will try to find links that can be helpful from a general perspective :) Thank you for your positive lecture review and comments :)
Hello, Arum, I have posted the list of questions you were curious about in the Q&A section (https://inf.run/wkJk). I hope it helps. Thank you :)
Reviews 3
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Average Rating 5.0
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