Data Scientist: Learn the Skills you need for free
Data Scientist: Learn the Skills you need for freeData Scientists are in big demand! We review career pathways, relevant data science skills, and how you can learn them at no cost.
By Dr. Mohamed Tharwat, John Snow Labs.
It is a well-known fact now that “Data Scientist” is the sexiest job for the current century, but how much
does it cost you to prepare yourself to be a data scientist? Are there other relevant jobs to data science and what is the career pathway for this job? What are the essential skills needed to enter this career? Where can we find free courses and what are the Must-Read Books in this field?
I will try to answer most of these questions in this blog. I know those are common questions that are mind-blowing for all those thinking to take the data science career.
Average Salaries
For me a sexiest job is the one which can be taught fast (relatively fast) with low costs or for free. Moreover, it should guarantee available job opportunities in the coming 20-30 years. It will be great if it can be done remotely or satisfy your relocation dreams. Finally, it must be highly paid.
I think data science satisfy all the previous conditions. To be more specific let us check average salaries for a data scientist in San Francisco, CA on Indeed.com website.
The search was done through Indeed.com on 20 May, 2017.
You can also search for average salaries for a specific location through Glassdoor.com. At least you can have a quick overview about the available jobs and salaries offered.
Relevant career pathways
Data scientist simply is the one who can make predictions from data. A data scientist usually need someone who manipulate and analyze the data (Data Analyst). The data engineer is the one who build data pipelines to work with large datasets. You can take whichever career pathway you like. Everyone need specific skills, although there are common essential skills among the three careers.
Essential skills
Math & Statistics
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Programming & Databases
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Soft Skills
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Visualization
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The 21st century sexiest job for zero payment
A lot of people already have the intention of taking the career pathway of data science or either recommend it for their children. Many people will think financing this type of education will be an obstacle and many may not proceed further due to insufficient funds.
The good news is that you can learn data science for free through “self-study” courses. The only condition in this case is “having a strong will”.
I can summarize the most famous and most beneficial websites for learning data science “for free” as follows:
1. MOOC
The evolution of Massive Open Online Courses (MOOC) or simply (free online courses) in the last 20 years has helped to a great extent in the progress of data science. One of the most helpful courses is “Harvard CS109 Data Science Course” created by Statistics Professor Joe Blitzstein and Computer Science Professor Hanspeter Pfister.
There are many other MOOC for data science, which you can find by thorough search on the internet. To save your valuable time, you can find the top 20 data science MOOC on KDnuggets at:
/2015/09/top-20-data-science-moocs.html (also /2016/07/top-machine-learning-moocs-online-lectures.html )
2. Coursera
Not only you can learn through Coursera, but you can get an interview with one of the top companies working in the field of Big Data (Splunk) by just finishing the Capstone Project at the end of the Big Data Specialization courses offered by University of California, San Diego.
There are many other free data science courses on Coursera offered by different universities, but from my point of view, the most organized and most beneficial is the specialization courses offered by University of California, San Diego in Big Data and the one organized by John Hopkins University in Data Science.
I think both courses can prepare you very well to start your career as a data scientist.
There are also specialized data science courses in specific domains like the one offered by Johns Hopkins University for Genomic Data Science. You can easily gain an exemption from the fees if you applied for a financial-aid through Coursera.
3. Microsoft Data Science Curriculum on edX
The data science program from Microsoft could be enough to prepare yourself for the competition in the data science market even if you are a beginner. The program contains different courses that run four times each year, starting on July 1st. During each run, the unit 1,2, and 3 course will be available for three months; and the final project will be available for 6 weeks at the end of the period.
More information can be available at:
https://academy.microsoft.com/en-us/professional-program/
You can have the full program in the (Audit) mode and so you can pay nothing. If you need a certificate, you can upgrade your membership and pay for the certificate (per course).
4. DataCamp
R and Python for a data scientist is like the mirror and the probe for a dentist or the saw and hammer for a carpenter.
DataCamp offers courses in R and Python (for free). In addition, it offers other courses in Data Visualization, Data Manipulation and Machine Learning.
5. Dataquest
There are three pathways on Dataquest (Data Analyst, Data Scientist, or Data Engineer). You have to choose one before proceeding further. Every pathway ends with a Capstone Project.
6. Win an amazing Data Science MSc Scholarship
If you are dreaming about a data science degree and do not have enough funds, Harbour.Space University might be the way to achieve your dreams. You can win FULL SCHOLARSHIP (valued at $50,000) to attend Data Science Master’s Program in Barcelona, Spain by joining Harbour.Space University big data challenge.
More details about the big data challenge can be found at:
Self-Study recommended reading list
The top 10 Free Must-Read Books for Machine Learning and Data Science are listed on KDnuggets™ at:
/2017/04/10-free-must-read-books-machine-learning-data-science.html
Original post. Reposted with permission.
Bio: Dr. Mohamed Tharwat is a Dentist, Health Informatics Researcher, Trainer and Evidence Analyst at John Snow Labs.
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