Learning Data Science on your own (Resource Guides)
Learning Data Science on your own (Resource Guides)
The Internet is your pandora’s box and with the countless options, it can feel as confusing as a mind maze with no way out.
There’s always going to be a cringe fest on social media about “how I became a data scientist by doing this and that for years”. Viral posts about the personal struggle and empathy talks will always be revolving around.
There’s nothing particularly wrong with those advices but the truth is often neglected that learning data science requires labor. It is in fact very hard to become a data scientist.
You can spot actual disappointed learners in social media groups, writing about how they gave up learning and couldn’t keep up with the course. For this reason we want to provide a little guidance. We’ve written a slew of data science articles this year and created learning guides for beginners.
The resources listed below will I hope equip you with the Data Science core skills as you learn.
Skills Guide
To prepare for a rewarding career in data scientist, you should developing a speciality by building the indispensable skills to build a strong data science portfolio.
Beginner’s Guide to Python for Data Science
7 Indispensable Data Scientist Skills
How to Build a Strong Data Science Portfolio
7 Data Analyst Skills for Beginners
Statistical Programming
You need to be equipped with a good understanding of Mathematics and Statistics for Data Science.
Beginner’s Study Guides:
Essential Statistics for Data Science ( Basic Concepts)
Linear Algebra Courses for Data Science - Beginners
Basic Math for Data Science ( Beginners Guide)
Mathematics for Machine Learning - Basic Guide with resources
Learning Resources:
Probability and Statistics for Data Science (Non-programmers)
Computational Statistics with Python
Learn Statistics with R for Data Science
Programming for Data Science
Both Python and R are state-of-the-art open-source programming languages with an excellent community support. SQL is also important and easier to learn.
Python:
Python is suitable for absolute beginners with simple syntax.
Learn Python for Data Science - Skill Tracks
R Programming:
R is suitable for statisticians and data miners for effective data analysis.
Learn R for Data Science
SQL:
Easier and Critical data science skills that you can gain is SQL, even if you have no programming experience.
Master SQL for Data Science
Data Science Educators (technical guidance)
Some data science educators help you seriously to build the essential skills and develop good understanding of the principles of machine learning to learn how to derive practical solutions using predictive analytics.
There are three data science educators offering career tracks with technical guidance and mentorship.
Specialty Skills
You should focus on becoming and specialist as the times goes by.
Learn Geospatial Data Science and Spatial Analysis
Learn Data Engineering — Career Tracks
pandas for Data Science and Machine Learning
Key Data Engineering Skills, Tools and Resources
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Also, did you know that we have created a Data Science Stack on kanger.dev? You can check out quality resources, articles, courses or books without membership.
Happy learning!
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