[PYTHON] A story of a person who started aiming for data scientist from a beginner

Introduction

The trajectory of the 4th year university students who are aiming for data scientist in the future started studying in October 2019 I would like to post to qiita with the theme of "a story of a person who started aiming for data scientist from a beginner". I write about what I learned in the first two months, including self-introduction and motivations.

Self-introduction

――From next year, I will get a job as an engineer of a major sler with no experience --MARCH level university 4th grade ――At university, majoring in the fields of statistics and management information --Full-scale study of Python from October 2019 ――Until then, I used R lightly and made a simple website with HTML \ CSS to some extent.

The opportunity to study machine learning

――Because I wanted to do advanced analysis in my seminar graduation thesis ――Because I wanted to acquire skills as an engineer, not completely inexperienced ――Because I really wanted to study something for the rest of the time as a college student ――I'm very interested in the mathematical approach ――Because I was originally interested in machine learning in the hot field of today ――Uncertain that the industry called sler will disappear as it is ――Honestly, I have a longing for the web industry

This is where I learn! I think the biggest aspect of investing in the future is: v: It's been less than two months since I started learning, but I've gradually come to understand it, so it's become a lot of fun.

How to study for Gekokujo

What I've done so far

Well, the main subject is from here! !! Please note that it is very hard to see because it is a bulleted list: woman_tone1:

① Self-taught programmer (read a little while traveling)

→ First, I was interested in something like programming, so I bought it.

② Progate Python course (4 days, 2 weeks)

→ You can roughly understand the description method. Feeling that the object-oriented meaning peculiar to programming is not well understood

③ Udemy's Kikagaku Co., Ltd. "De-Black Box Seminar" Beginner's Edition

I think it's about 5 hours in total in 2 days!

④ Udemy's Kikagaku Co., Ltd.'s "De-Black Box Seminar" Intermediate bias

This is a continuation of the above course. I think it's about 5 hours in total in 2 days as well! It was really good to be able to learn the theory such as supervised learning and unsupervised learning and regression analysis at a level that can be used in practice through the two courses! Highly recommended for beginners!

⑤ Reading: A book for those who want to become machine learning

I wanted to study after understanding the above four things, so I read it to see how to study for the rest of the time to become a professional. I finished reading it in about 3 hours.

⑥ Free trial of programming school

Speaking of programming school, web-based is the main, but I wanted to know a specific study method, so I went to experience with Aidemy and SAMURAI engineer who are focusing on AI. I went to codecamp, but I don't remember much because I didn't do AI in earnest. The SAMURAI engineer was particularly glad to have a free trial. I thought about studying at school, but it was financially difficult, and even if I learned it now, the code was too low, so I didn't have to ask the instructor and I mainly studied by myself. I thought it was bad. I will consider the school after strengthening a little more in the future.

⑦ Learning with PYQ

This was mostly the main thing in November. There are various courses, but I went through the Python grammar (study time is about 82 hours) course from inexperienced. I started to play basic chords, but it is difficult to draw a line as to how much I should remember. After this is over, I am doing a machine learning course (the standard study time is 42 hours or more). Currently in progress.

⑧ Reading: A book that understands mathematics for artificial intelligence programming

I bought and read the book that Aidemy had when I had a free trial. It took me about two weeks because I was reading slowly and solving the problems listed.

⑨ Reading: Is artificial intelligence beyond humans? What lies beyond deep learning

I started reading around November 20th. I think it is the most famous book related to artificial intelligence. It will be readable in about 5 days. It was very interesting.

⑩ Mathematics: Linear Algebra Campus Seminar

It was mentioned in a book for those who want to become machine learning. Knowledge of linear algebra is indispensable for understanding machine learning, so I have been learning since my second year of university. I think it will take about 2 weeks.

* Other

① Typing practice

I think it is essential for improving study productivity. I use a site called e-typinng. I've been doing it for 30 minutes every day since November 20, 2019.

② Learning English

Take the TOEIC (L / R) test on November 24, 2019. Average 1.5 hours during October. Before the exam in November, I spent about 3 hours studying. I got 700 points a year ago, so I was studying with the goal of 800 points. When I became a member of society, I was studying because the specifications were in English and I was thinking of studying at overseas sites such as Coursera in the future.

③ Seminar graduation thesis (late period of university)

Originally I was using R, but since I am studying python, I analyze it with python and write my thesis. I am doing data analysis for the J League of soccer. It is a valuable output place.

What I want to do from now on (during December 2019)

① Participation in TEAM AI study session ② Challenge Kaggule as a trial → This is also scheduled to participate in the study session ③ Try exercises with pyq mainly for machine learning ④ Linear algebra campus seminar (1 lap by December 10) ⑤ Check the statistical test level 2 and start studying

Future ambitions

E Qualification: To certify the skills of engineers who implement deep learning G test: Tests whether you have the knowledge to utilize deep learning in your business The qualifications from here are interesting so I will study

Finally

I will continue to do my best through trial and error! !! !!

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