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How to Break into the Data Science Field (Without a Data Science Degree)

More than ever, data is influencing the way institutions and organisations operate. Whether it’s the Singapore General Hospital introducing a dashboard to help medical staff track the statuses of all ICU patients; Netflix recommending you similar titles to what you’ve been enjoying and producing shows based on the data of millions of users, insights from data analytics shape our user experiences.

It’s no surprise that data analysis and data literacy are highly sought-after skills by employers across many industries. At the National Library Board (NLB), we too, have a Data Office team that studies the borrowing patterns at our public libraries and other data so we can serve you better. (For more insights, head over to our data blog here!) So for those who’ve scribbled “learn data analytics” as one of your new year’s resolutions, here are some free resources to get you started.

Pick Up the Basics Online

Not ready to shell out the money for a formal course on data science? Start with free online learning resources and learn at your own pace. [Image source: iStock]

Dip your toes into the field of data science with our hand-picked beginner courses. Remember to also set aside time to tinker around with data sets and get some hands-on experience, which is something that your prospective employer will look for.

Guo Jia, one of our data analysts, says, “I’ve put a lot of time into learning about the different tools and methods through courses, but looking back, some of that time might have been better spent on personal projects where I put the theories into practice.”

“For those who want to join the data science field, I recommend having some basic understanding of SQL and picking up a BI (business intelligence) tool,” adds teammate Phyllis Tay.

You can find some of these free courses on Udemy Business through NLB’s eResources:

The Data Science Course 2022: Complete Data Science Bootcamp

All the different-but-related fields within data science can be overwhelming, especially if you’re a newbie. You can break it down by getting an overview of each field and the types of analysis carried out in them. Dive into maths, statistics, Python, data visualisation, machine learning and deep learning in this highly rated course.

The Complete SQL Bootcamp 2022: Go from Zero to Hero

Mastering SQL is one of the most in-demand skills within the data science field. This course will teach you how to use PostgreSQL to query a database. You’ll be able to apply these skills to other major SQL databases such as MySQL, Microsoft SQL Server, Amazon Redshift, Oracle, and more.

Machine Learning A-Z™: Python & R in Data Science

Machine learning, a type of artificial intelligence, is another hot and lucrative sub-field of data science. Get a step-by-step introduction to machine learning and pick up the relevant skills to programme robust analytical and prediction models using Python and R.

Other learning platforms also offer the following courses:

IBM Data Science Professional Certificate (Coursera)

Computing giant IBM offers a free professional certificate to help you pursue a career in data science. The course is structured to give you hands-on practice in the IBM cloud using real data science tools and real-world data sets. Upon completion, you’ll graduate with a portfolio of data science projects for a competitive edge among other entry-level data scientists.

Data Science Foundations (Codecademy)

Pick up the basics of cleaning, analysing, and visualising data responsibly in this course, then move on to many of the free data science courses offered on Codecademy, or subscribe to them for access to premium content designed to equip you with technical skills.

Connect with Data Scientists Through Workshops

The data science community is big on sharing insights, tips and tricks. So don’t miss out on learning from others at live events. [Image source: iStock]

When self-learning starts to feel too isolated, balance it out with some workshops where you can meet and network with the local data science community.

NLB’s Future of Work

Join our free online programmes where we invite instructors to teach you the skills required for the future workplace. This programme series provides easy-to-understand information about topics such as Artificial Intelligence, big data, and blockchain technology.

General Assembly Workshops

General Assembly runs free workshops on data science and data analytics to help with career development and transitions. They also offer paid courses, which you can offset with SkillsFuture Credits if you’re looking for more structured learning.

She Loves Data Events

She Loves Data is a social enterprise helping women to pursue careers in data and tech. Their offline and online events include free introductory courses on data analytics and hackathons.

Additional Reading

Of course, it would be remiss of us not to recommend popular data science books to support your learning journey. Check out these titles, including two special recommendations from our Data Office.

From left to right, top to bottom:

Data Science From Scratch — Joel Grus | Physical Copy, eBook

Data Science for Dummies — Lillian Pierson | eBook

Python Crash Course — Eric Matthes | eBook

The Big Book of Dashboards — Steve Wexler and Jeffrey Shaffer | Physical Copy, eBook

“I personally enjoyed The Big Book of Dashboards, which critiques some of the visualisations and gives insight on how to improve them. I like that it is not specific to any particular BI tool, so the learning points can be applied to whichever tool you use.” — Phyllis Tay, NLB Data Office

The Signal and the Noise — Nate Silver | Physical Copy, eBook, Audiobook

“This was a compulsory reading for one of my undergrad electives. Each chapter provides real world examples on the use of statistics, probability and forecasting in different industries. Data science relies on statistical concepts, and one of the key ideas is distinguishing between the truth of a matter (signals) from distractions (noise). This book makes these concepts accessible.” — Guo Jia, NLB Data Office

Change the World with Data

With a steep learning curve and hours of staring at data and programming languages on your computer screen ahead of you, what’s there to look forward to after entering the data science field?

“Being able to solve problems using data is the most impactful part of the job,” says Guo Jia.

“It’s rewarding when changes are made because of your projects,” Phyllis affirms. “For example, one project I did was to identify potential partners that NLB could work with to set up kidsRead clubs so that we can reach out to more vulnerable segments.”

If you’ve always dreamed of changing the world, there are plenty of opportunities in our data-driven world today, so take that first step to understand data analytics!

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National Library Board



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