These are chat archives for FreeCodeCamp/DataScience
discussion on how we can use statistical methods to measure and improve the efficacy of http://freeCodeCamp.com
@Wvictor07 good luck in your journey to be a data scientist! When I saw "initial kit", I thought of "foundations". Doing a quick search on the topic, I came across a "textbook" called "Foundations of Data Science", which was written with this intention:
With this in mind we have written this book to cover the theory likely to be useful in the next 40 years, just as an understanding of automata theory, algorithms and related topics gave students an advantage in the last 40 years. One of the major changes is the switch from discrete mathematics to more of an emphasis on probability, statistics, and numerical methods.
Also came across "Data 8: The Foundations of Data Science", a UC Berkeley (in California, US) course that focuses on inferential thinking, computational thinking, and real-world relevance. There appears to be a wealth of information (e.g. slides, assignments, and readings) along with a free online book "Computational and Inferential Thinking: The Foundations of Data Science", which includes interactive Jupyter notebooks and data. Lastly, for a more R twist on data science, there's "R for Data Science" by Hadley Wickham of tidyverse fame, which has been mentioned several times in this room.
Sorry if that was a lot to take in, but I was curious of those materials and they appear to be solid resources.
@erictleung yes I agree with you on that, although interestingly it is never quite perfect :) . I am sure depending who you ask there are who might come with a different syllabus.
And thanks for sharing those too!!
evaristoc sends brownie points to @erictleung :sparkles: :thumbsup: :sparkles:
PROJECT 1: "I GOT A JOB!"
An old fCC student, @ThiagoFerreir4, wrote the following post long time ago:
Well if it helps in any way, once I focused on one thing I liked(Front-end) things got way better to the point a got a job recently, and I started with FCC this January with no past web dev experience
He left this comment on 2015-10-07 to someone else in the chat back in 2015 some months before disappearing from the freeCodeCamp radar. Thiago was a missed guy, he was a very popular one in the main chatroom. Still, everyone was really happy about him.
He made it.
As him, there were few others that left after finding jobs. I found some between 100 and 300 who announced finding jobs in the chat room since its inauguration. Those about 300 are not a complete list though. There are many reasons to suggest the number could be bigger. Just to mention one reason, there are some who never announced or even participate in the chatroom. It may be hard to come with an actual figure.
However this project is not exactly about making an statistics. It is actually about trying to answer the following question:
What made them different to others so they managed to get a job at the end? Can we construct a profile of the "successful" self-taught (web) developer? How that profile would look like?
There are already obvious answers to that question.
But can we find more? Perhaps overlook details that might give a more comprehensive picture of that profile?
This project consists in a research phase, followed by an article and if everything goes fine a visualization-based page characterizing those profiles.
PROJECT 2: HEALTH RELATED INVESTIGATION
I am going to give you less details about this project because it is still too early but I can tell that it will explore health issues. The data to be used will be similar to the one above. As soon as we start and see if there is no problem to comment I will come back to you with more details.
So far we are 3 people signed to work on both projects above in their initial phases (research). It is likely but not necessarily that I will write the articles. As long as the projects progress we could see how we will deal with the visualization section.
None of the projects is about Big Data or similar but they are in fact data driven. Another difference is that for those 2 projects the resulting information won't be for business/research decision making: the target group we want to reach is the general public. However there are few by-products I would expect from the projects:
The success of our work should be evaluated in terms of exposure. For example:
Let's start simple hoping that working on these ideas will bring us to much more complex and challenging tasks in the future. However...
I think there is the time to think big, people. We are ready.
OK. I will contact soon a few of you who I think could help with some other aspects of the projects.
finally but not last...
If you are interested in joining any of the projects above or want to know about other ideas I have,
We will evaluate possibilities together.