Get a Master's In Data Science for FREE!
Education has been provided by schools and universities for a very long time. But in today’s digital era, there is nothing in this world you cannot learn using the Internet. Google has answers to every question you may have thought of but you would have to give it a minute or two of search. This brings us to the crux of this article,
Data Science can be self-taught.
As someone who has completed over 25 certifications in Data Science with so many open-source platforms and supportive platforms, I still learn more and more every day and enjoy the journey. The fact that you can learn anything you want to and that you can be flexible with it makes it very tempting to learn things on your own.
A master's degree is predominantly considered a really good level of education one can attain in the 21st century. The number of universities and students is growing at a rapid pace as well. Starting from the idea of schooling, international exchanges for students, multiple scholarships, online courses, and education sponsors… today one can gain knowledge with a little planning and effort.
If you’ve been a fan of Data Science for a while, you probably recognize this person or if you don’t, we are about to learn a lot of awesome things that need to be shared as much as possible.
Clare Corthell is a renowned individual in the world of Data Science. Working currently as a Senior Product Manager at Lyft, she is a self-taught Data Scientist who acquired the knowledge and skills with her collection of resources that turned into the Open Source Data Science Master’s — a curriculum of online courses, books, and other resources that one could use to learn the mathematical and programming foundation crucial to a data scientist.
OSDSM — OPEN SOURCE DATA SCIENCE MASTER’S
The Open Source Data Science Master’s is free for all collection of almost everything you need to learn to be a Data Scientist.
The official page starts with a very simple yet mind-blowing question :
With Coursera, ebooks, Stack Overflow, and GitHub — all free and open — how can you afford not to take advantage of an open-source education?
If you are someone who thinks hustle and grit are what it takes to make it big and not just a good college, then you are probably going to enjoy this.
As rightly pointed out in the Academic Shortfall section of the OSDSM;
“Academic credentials are important but not necessary for high-quality data science. The core aptitudes — curiosity, intellectual agility, statistical fluency, research stamina, scientific rigor, skeptical nature — that distinguish the best data scientists are widely distributed throughout the population.
We’re likely to see more uncredentialed, inexperienced individuals try their hands at data science, bootstrapping their skills on the open-source ecosystem and using the diversity of modeling tools available. Just as data-science platforms and tools are proliferating through the magic of open source, big data’s data-scientist pool will as well.”
— — James Kobielus, Closing the Talent Gap 17 Jan 2013
The talent gap can be bridged with open-source education which only requires the curiosity of a student and the eagerness to learn.
Clare says in an interview as a part of the book The Data Science Handbook, “The ability to evolve my career with a self-designed curriculum begins to outline the immense cracks in the foundation of higher education*. The deconstruction of this system was very long in coming, but it’s happening now. The lesson is the following: if you take initiative and acquire skills that increment your value, the market is able and willing to reward you.”
The contents of the OSDSM include;
- Math
- Computing
- Data Analysis
- Data Communication and Design
- Python (Learning)
- Python (Libraries)
- Datasets
- R resources
- Data Science as a Profession
- Capstone Project
and many other resources and links that one can harness to learn everything they need to be a Data Scientist.
Honestly, from a personal perspective, I wish I knew about this when I started on my journey because this gives the entire journey enough direction to set the feet in the right places. The mere fact that we as data science enthusiasts have such a vast active community, only calls for collaboration to build more resources such as the OSDSM to ensure education is easily accessible to all and with the right content.
Find more about OSDSM here:
For the GitHub repository:
For more about Clare Corthell:
The curriculum helps direct data enthusiasts on the right path to learn everything they need to excel in their careers. Breaking through from the routine syllabus of a college and being curious enough to want to learn more about what you are passionate about is a primary step to being a successful data scientist.
The investigation, while you are analyzing data, is something that gets a Data enthusiast fired up, so well? Get to investigate the possibilities of open-source learning at the earliest.
Check out the OSDSM and let me know if you think any other resources can be added to the curriculum!
Update as of May’22. I have added some resources that you can also look at when you attempt your shot at the OSDSM. Check it out in this article here, much thanks.
For more such articles, stay tuned with us as we chart out paths on understanding data and coding and demystify other concepts related to Data Science. Please leave a review down in the comments.
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