Beginner Python Machine Learning Bootcamp (Easy! Solve real Kaggle problems and organize them) [Data Analysis/Science Part 3]
This is a new lecture, different from existing lectures, based on the instructor's experience of failure when first learning machine learning, so that machine learning can be easily understood and applied to real-world problems.
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[Janjae-mi Coding] Sharing news about Janjae-mi Coding and information related to data analysts
Hello. This is Dave Lee from Janjaemi Coding.
How have you been? It's just that sometimes, I get emails from people who are thankful to me that they got a job. When I think about it, I think that if I share these cases, it might motivate and inform the people who are taking the class a little more. Of course, I can't share the content of each email, but I'll share the main content.
If you learn IT, there are various positions you can approach. One position that is good to consider is a data analyst. Recently, there have been more and more people who have found employment in this position. Startups have tried to make decisions based on data since long ago. Now, it seems to be becoming more common. As a result, various data analyses are needed, and the position that performs this is the data analyst.
Data analysts need to be well-versed in IT technologies that deal with data. SQL for databases is key. In addition, Python-based data analysis technologies and a core understanding of machine learning/deep learning are sufficient from a technical perspective.
In the meantime, I met 50,000 students, and there are some who prefer data technology over programming and are learning it well. I think this is their aptitude. They all seem to be IT technologies, but programming and data require slightly different ways of thinking. Also, data analysts need to understand IT technology and business well after employment, rather than being immersed in IT technology, so it is a very good position for those who want to know both business and IT technology.
In fact, related technologies do not have to be immersed in IT technology, so you can learn them even if you do not go through a full-time 6-month course. The next data science roadmap is a lecture series that was created to allow non-majors to learn from IT basics to deep learning, assuming they know nothing about IT.
https://www.inflearn.com/roadmaps/66
Of course, it would be good to learn probability and statistics theories here, but considering the actual work, I don't think it's essential. (In reality, SQL is used the most. We are planning to add a SQL coding test (tentative title) that will allow you to practice SQL in various ways in the future.)
Anyway, through this process, I sometimes get emails from people who are completely non-majors, who started IT, learned about data analysts, developed their dreams, got jobs, or changed jobs. Also, even if you are not a data analyst, if you can handle data with IT, you can have a huge competitive edge in whatever you do, even in business. I think that in the next 2-3 years, the value of data analysts will be much greater than it is now.
Lastly, I'm currently preparing a Flutter course. It's a technology that allows you to create programs for Android/iOS, as well as web/MAC/WINDOW with a single code, and it's finally become hot recently. If you took my lecture two years ago, you probably know that I mentioned Flutter on the details page since then. (It's finally become hot, haha) I'll share it with you around the end of April.
I hope this email was helpful.
thank you