Data Science and DX-related educational materials provided free of charge by companies and other organizations
First, there is gacco. Even now, there is a lot of high-quality content related to data science available. There is an abundance of both quality and quantity of materials that are very useful even for free.
Data science and DX-related educational materials provided free of charge by central government agencies is also used as a platform, and you can check this link for future training schedules provided free of charge by the Statistics Bureau of the Ministry of Internal Affairs and Communications and others.
In addition, Tohoku University and Shiga University provide free content (including non-data science topics), which helps with university branding.
Furthermore, gacco offers paid services for corporations. I haven't used Udemy's corporate services, so I don't know the difference.
Personally, I recommend gacco. Udemy allows anyone to publish content and become an instructor, so the quality is mixed, but I hear that gacco's content is relatively screened. Also, gacco is where you can find excellent free content provided by central government agencies and universities. By the way, when purchasing paid content, the instructor's share seems to be about the same for both, but from the perspective of whether the remaining money flows overseas or circulates domestically, I think gacco is better.
As mentioned above, once you have decided what to learn, training materials published by leading companies are also useful. I will link to a collection of links covering a wide range of fields, not just data science.
[New Graduate Training Materials] Basic of statistics
Basics of analysis ~modeling~
Regarding other individual technologies, Japanese articles are written with careful attention to the basics.
Google and Microsoft articles can sometimes feel like direct translations or have a strong push toward their own products, but well, it's enough if you can read this much for free.
The rest is just a list.
Apparently, this also exists. If the Data Science Society, the Deep Learning Association, the IPA, and the Ministry of Economy, Trade and Industry really cooperate, and if no other noise gets in the way, I feel like things might progress reasonably well, but I wonder what the reality is.
Looking at it this way, many people misunderstand because there are more articles using Python than R, but R is also more than useful enough.Data analysis texts provided for free, R edition, I'm not specifically pushing R, but just as a supplement please take a look.
If you want to see other information, go to the table of contents page
Starting over by organizing collected information | Kusuguttagari | note