How to become a data scientist without a degree
Interested in becoming a data scientist? Discover how to become a data scientist without a degree with FutureLearn.
In a world driven by data, data science has gained immense significance over the last few decades. With the ability to extract valuable insights from large datasets, data scientists are at the forefront of decision-making in various industries.
While a degree in computer science or a related field can provide a solid foundation, it’s not the only path to a successful data science career.
In this article, we’ll explore whether it’s possible to become a data scientist without a degree, reasons why data science can be a rewarding career path, plus a step-by-step guide to help you get started.
What is data science?
The origins of data science may be surprising to some as they are relatively young. In a 2001 journal article, American computer scientist William S. Cleveland coined the term ‘data science’ where he expressed an action plan for expanding the field of statistics.
Simply put, data science combines machine learning, programming, maths and artificial intelligence (AI) to analyse data and get accurate insights. These data insights are then used to make strategic and well-informed decisions.
Data scientists use a number of tools and programming languages such as Python, SQL and R alongside Tableau, Snowflake and MySQL to help visualise, store and manage data.
Why work in data science?
With an estimated $3.93 billion global platform market size and a 26.9% growth rate, data science is one of the fastest-growing industries. It was even once dubbed The Sexiest Job of the 21st Century by Harvard Business Review – but why exactly should you choose this career path? Here are just a few reasons.
High demand: Data science is one of the fastest-growing industries. Over the past few years, the increase in demand for data scientists and engineers in the UK has risen by 231% (compared to an average of 36%). Plus, with the £17 million government investment to create 2000 scholarships for data science and AI conversion courses, there’s never been a better time to enter the field.
Competitive salaries: With the ability to turn data into actionable insights, data scientists are often well-compensated for their skills. According to Glassdoor’s 25 Best Jobs in the UK for 2022, data scientist ranks fifth with an average salary of £49,449 and a job satisfaction score of 4.2 out of 5.
Versatile career paths: Offering a variety of career paths, including machine learning engineer, data analyst, data engineer, you’re able to choose a data science specialisation that aligns with your interests.
Impactful work: If you want to innovate and make a positive change, then data science could be for you. Data scientists often contribute to meaningful projects, from healthcare analytics to climate modelling. Your work can have a positive impact on society and the world.
Constant learning and problem solving: It’s clear that data science is a field that thrives on innovation. You’ll continually encounter new challenges and have the opportunity to develop creative solutions, so you can be sure that there will never be a dull moment.
Can you become a data scientist without a degree?
A degree is not an absolute prerequisite for becoming a data scientist. What matters most in this field is your skillset, your ability to solve complex problems, and your proficiency in various data science tools and techniques. Many successful data scientists have taken non-traditional paths into the field.
How long does it take to become a data scientist without a degree?
The time required to become a data scientist without a degree can vary significantly based on your starting point, your dedication, and the resources you have at your disposal.
On average, it might take anywhere from 6 months to a few years to acquire the necessary knowledge and skills to land your first data science job.
How to become a data scientist without a degree
Becoming a data scientist without a degree may take a few extra steps, creativity and a lot of initiative, but it’s not impossible. All you need is a clear plan in place, which luckily we have here.
Choose an online course (or three)
Begin with the basics: Start your data science journey by gaining a solid understanding of the fundamental concepts. We offer flexible, expert-led courses on mathematics, statistics, and programming, as well as courses on essential programming languages such as Python and R. These are the basic building blocks of data science, so you’ll want to make sure you have a solid understanding of all areas.
Dive into data analysis: Embrace data analysis and visualisation. Discover our courses on data analytics with Python and data visualisation with tools like Matplotlib and Seaborn.
Master machine learning: A strong foundation in machine learning is crucial. Explore more on the topic with our courses on machine learning and deep learning.
Get certified
Earn certifications: Boost your credentials with a certification upon completion of one of our many short courses and ExpertTracks from The University of Glasgow, RMIT University, University College London and CloudSwyft Global Systems, Inc.
Consider data science bootcamps: Alternatively, data science bootcamps (such as those offered by General Assembly and Data Science Dojo) are a great opportunity to receive intensive training and work on projects.
Build a portfolio
Showcase your work: As you progress, build a portfolio of data science projects. Work on real-world datasets, contribute to open source data science projects, solve practical problems, and showcase your skills on platforms like GitHub.
Gain practical experience
Apply for internships and entry-level roles: Start applying for internships and entry-level positions in data-related roles, such as data analyst, research assistant, or junior data scientist. These roles provide hands-on experience and a clear path into data science.
Keep learning
Stay ahead of the curve: The field of data science is continually evolving, so it’s best to stay curious and interested in what’s new. Keep up with the latest trends, tools, and techniques by reading research papers, attending conferences, and participating in webinars.
Join data science communities: Engage with the data science community by joining forums like Stack Overflow and Reddit’s r/datascience. Networking with professionals and enthusiasts can provide valuable insights and connections.
Create an online presence: If you’re so inclined, build a personal brand by sharing your insights and projects on platforms like LinkedIn, Medium, or on a personal blog. This can help establish your expertise and connect you with potential employers.
Become a data scientist with FutureLearn
While a degree in data science or a related field can be advantageous, it’s not the only way to become a data scientist. With dedication, self-learning, and a well-structured plan, you can achieve your goal of becoming a data scientist without a degree. It may take time and effort, but the reward of a data science career is well worth the journey.
Remember to build a strong portfolio, network, and keep building your technical and soft skills. Whether you choose online courses, bootcamps, or a combination of resources, the path to a data science career is within your reach, and we’re here to help you on your way.
Online data science courses at FutureLearn
- Introduction to Data Science for Educators by University of California, Riverside
- Data Science Projects and Applications by FutureLearn and Packt
- Data Science in the Games Industry by University of Dundee
- An Introduction to Machine Learning in Quantitative Finance by UCL (University College London)
- Introduction to Data Science for Business by FutureLearn
- Introduction to Data Science with Microsoft Azure by CloudSwyft Global Systems, Inc.
- Microsoft Future Ready: Introduction to Azure Cloud for Data Scientists by CloudSwyft Global Systems, Inc.
- Microsoft Future Ready: Fundamentals to R for Data Science by CloudSwyft Global Systems, Inc.
