The job market keeps evolving, and people are selling their skills and capabilities like hotcakes, while some others have assumptions about the job market that to pursue a career in data science, you need a degree.
This has led to a lack of confidence among themselves to move forward and pursue their dream career. Sometimes, these beliefs also force them to divert their career into something against their wish.
Some of them might be worried because they have an irrelevant degree and highly confused if companies would oppose hiring data scientists with no degree.
However, this is probably a myth, and people are unaware of the ongoing demands of the technological sector.
How many of you know that the “Big MNCs are providing privilege to skills rather than the degree of the candidate”?
It is high time to realize this fact and come out of a job you didn’t like to do and explore the career opportunities in data science as you wish.
Data scientists require a strong background in statistics and mathematics. Mathematics, statistics, computer science, and engineering are the most popular academic specialties in data science.
This article aims to take a sneak peek at the significance of being a Data Scientist and the ways on how to become a data scientist without a degree.
Table of Contents
What is Data Science?
Data Science includes multidisciplinary fields such as scientific methods, Statistics, Artificial Intelligence, Data Analysis, etc.
Data scientists are those who practice data science, and they possess a spectrum of skills to evaluate the data collected from various sources such as customers, smartphones, devices, the web, sensors, etc. to arrive at actionable insights.
It encompasses the preparation of data for data analysis, aggregation, data cleansing, manipulation, etc. to implement high-end data analysis.
The data scientists can then view and explore the patterns from results, to drive business decisions. Data science jobs are one of the most exciting, however, the majority of the capabilities are still untapped, due to the lack of appropriate data science skills among the candidates, existing employees, and job seekers.
Every day, there are around 2.5 exabytes of data generated globally.
Since companies get enormous amounts of data from various sources, modern technology has compelled businesses to enable the production and storage of massive information.
It is estimated that about 90% of the data that exists globally has been created in the past two years. This is visible from Facebook, where users post almost 10 million photos every single hour.
Since the data collected and stored using top-notch technologies can be useful to bring gigantic benefits to organizations across the world, they need experts to interpret them. This is where data science comes into the vicinity.
Who is a Data Scientist? What do Data Scientists Do?
A data scientist is defined as a professional who usually collects, evaluates, and interprets massive amounts of organizational data.
The data scientist job is a blend of several technical roles that include statistician, scientist, mathematician, and computer expert.
The core tasks of a data scientist include:
- Identification of data analytics issues that can be mitigated to be beneficial to the organization
- Collect and determine the accurate data sets and the variables
- Source huge sets of both structured and unstructured data from various sources
- Arranging and validating data to make sure about uniformity and accuracy
- Implementing models and algorithms to excavate the storage of big data
- Performing data analysis to discover the trends and patterns
- Data interpretation to identify the solutions and opportunities
- Using data visualization to communicate the findings to the stakeholders
Why become a Data Scientist?
As per a Burtch Works survey about data scientists, the median base salaries were not impacted with the onset of the Covid 19 outbreak and remained steady over the previous year.
The increased hiring, salary hike, and more job opportunities have strengthened the significance of data science as a career.
Nevertheless, the median base salary for data science managers is found to be 2,50,000 USD and this is about 1,60,000 USD for the individual experienced professionals. (Forbes).
If you still ponder on solid reasons to choose data science as your career, here are the inferences from the Glassdoor report, that justify your decision.
- In the report, Data Scientist has secured #2 position among the 50 Best jobs in the US, identified by Glassdoor for 2021.
- The median base salary for a data scientist is as huge as 113,736 USD.
- The job Satisfaction index value is 4.1 out of 5.
- There are more than 5,971 job openings, which clearly shows huge demand, but a lack of skilled professionals to occupy the position.
Subsequently, here are the reasons why you should choose data science as your career.
- Increased demand for data scientists, more scope in the job market for the right skill set.
- Improved salary trends, even entry-level data scientist jobs make not less than 69,000 USD, says Ziprecruiter.
- Tagged as one of the best jobs across the globe, demand is much more than supply, with a lot of vacant positions.
What skills do Data Scientists require?
Data Scientists, unlike the earlier form of statisticians, are expected to exhibit a wide range of skills based on the complexity and the scope of the job.
It now requires a blend of technical and interpersonal skills to ace the data scientist job.
- Python Programming: Since Python is the most adaptable and popular programming language, it can be used to conduct everything ranging from data mining to the running of embedded systems.
- R Programming: The software is highly prevalent in the implementation of software facilities for calculation, manipulation, and graphical display of data.
- Hadoop: The combined features of Hadoop can be utilized to let data scientists process huge data sets with simple programming models.
- SQL: This domain-specific language is used to query and manage the data held in RDBMS (Relational Database Management System), and used to read/retrieve data from the database along with the insertion of new data
- Machine Learning and Artificial Intelligence: Used to analyze large amounts of data, use algorithms and data-specific models to automate the repetitive jobs, and make NLP (Natural Language Processing), detection, and recommendation processes easy.
- Data Visualization: Graphical representation of data in the form of maps, charts, infographics, etc. Visualization of data with various tools like d3.js, Tableau, ggplot, etc.
- Business Strategy: Ability to analyze the business problems and build infrastructure to slice data that help the organization they serve.
- Communication skills: Understand business requirements, probe the stakeholders for further data and ideas, and communicate the core actionable insights.
- Storytelling: Oral communication, writing and data visualization needs analytical solutions communicated in storytelling like concise form.
- Teamwork: Collaboration and working in a team is important to identify the business requirements and arrive at a conclusion. It is important to have an understanding among data engineers Vs data scientists, junior data scientists and managers, fellow data architects, data analysts, Chief Data Officer and the whole team, and so on.
- Quick learning skills: It is important to cultivate discipline and patience, and learn new concepts very soon.
Steps on how to become a data scientist without a degree
Is it logical to fulfill the role of a data scientist without a degree?
When you witness candidates with Masters’ or Bachelors’ getting into safe and secure data science-related jobs, you are forced to believe that this is not your cup of tea.
But this is not true, and you can still grab a data science job without a degree. Let’s explore the roadmap to becoming a data scientist without a degree.
1. Self Learning
Data Science is a huge field that involves many segments of subjects like Computer Science, Mathematics, and Statistics.
You can develop basic theoretical knowledge about the concepts through books, online resources, and Internet as a prerequisite to developing your skills in data science.
2. Analyze the real-time case studies
As you get a good hold of Data science and related tools, you can read and research the various case studies and how the businesses use the data science tools to improve their organizations’ benefits along with the profits.
This can let you find out the problems to be solved, and the method to be adopted towards addressing specific problems, etc.
3. Data Science Workshop and Bootcamps
These can be helpful to develop basic know-how and get real-time experience in some specific areas, though not ideally covering all the aspects of data science.
These workshops can trigger your first experience with learning and exploring data science.
4. Build Portfolio
The Portfolio is a reflection of the work you have performed in the Data Science field. You can use various Data Science projects to magnify your portfolio.
Through social networking sites like LinkedIn, Github, etc, you can grab the attention of the recruiters.
5. Get Data Science Certifications and Online Courses
This is the most recommended above all these steps because once you land a perfect data science course that can cover all your needs, the above steps will be taken care of by the course provider.
When you take the top data science online courses, you can learn practical concepts and develop the skills required to be a successful data scientist, which is highly in-demand in the current job market.
Check this out -> How to crack a coding interview
Best Data Science Online Courses to become a Data Scientist
Data Scientist is the most sorted and highly in-demand job segment that attracts people towards the plentiful opportunities they showcase.
Having that said, now it is natural to be curious about finding the most reliable courses among the numerous data science courses available.
Here is the filtered list of most recommended data science courses online to reap the best results worth your investment.
1. Data Scientist Nanodegree Program-Udacity
These courses are designed to master the relevant skills to become successful data, science professionals.
This course is ideal if you have experience in Machine Learning and you have the prerequisite know-how in Python, Statistics, and SQL.
The core highlights of this 4 months course are: Industry relevant content, Real-world project, and Reviews by experts in projects
Link to the course:
2. Complete Data Science Bootcamp -Udemy
This course can give you the whole toolbox required to become a data scientist.
Skills like Python, Statistical analysis, Seaborn, NumPy, Pandas, matplotlib, Tableau, Scikit-learn, and Machine Learning, along with Deep learning through TensorFlow can be learned.
Business cases are also available to induce real-life skills development in this 30 hours course.
Link to the course:
3. IBM Data Science Professional Certificate – Coursera
This 11 months course is specially built to give insights and build a career in ML and Data Science.
You get trained in data science skills, Data visualization, Python, SQL, and Machine learning models. There is no requirement for any prior experience or a degree.
IBM also gives provisions for financial aid. The highlights of the course are data science concepts, hands-on skills, tools, languages, libraries, data analysis, and visualization.
Link to the course:
4. Data Scientist with Python Career Track (Datacamp)
The course is designed to build the Python skills you require as a data scientist.
If you don’t have prior coding experience, this is the best course you can take.
You can learn the integral skills to manipulate, import, clean and visualize data and be well versed through interactive data science exercises.
You can also work with real-world data sets and learn the technologies like NLP, decision trees, Python skills, statistics, Machine learning, etc. with this 88 hours course.
5. Data Scientist Career Path – Codecademy
The course is divided into two Pro Paths: Skill Paths and Career Paths.
The former helps you to understand the requirements to build skills and develop domain knowledge, while the latter deals with specific skillsets for career building.
The Data Scientist Path offers a promising career path to be industry-ready and be in demand by giant companies.
Link to the course:
6. Upgrad Data Science Course
Upgrad focuses on providing various online learning courses for master’s degree, executive PG, and Advanced Certificate programs, leaving the choice to the learners based on interest and eligibility.
The course also offers referrals and earn benefits which lets you share the course and be eligible for discounts on the course price.
Link to the course:
Apart from the above-paid courses, you can also access free Data Science courses to boost your knowledge in the field, here.
Quick Overview of the Resources –
|Online Course||Approx. Pricing|
|Udacity Data Scientist Nanodegree Program||$1045|
|IBM Data Science Professional Course||$429|
|Datacamp Data Scientist with Python Career Track||$12.42 per month|
|Codecademy Data Scientist Career Path Course||Depends on Path Selected|
|Upgrad Data Scientist Course||$160 per month|
|Udemy Complete Data Science Bootcamp||$47.04|
The Parting Shot
Data science is one of the swiftly growing and lucrative careers of this century.
Data scientists were believed to be highly educated and have high-end technical skills alone to be capable of grabbing data science job opportunities.
However, today’s job market demands communication skills apart from mathematical, statistical, and computer-related knowledge.
The increased data scientist job requirement and numerous opportunities available leave huge scope to data science as a career option.
The above-recommended courses can let you choose the course based on your requirement and eligibility to excel as a data scientist. Hope you like the approach and information mentioned in this How to Become a Data Scientist Without a Degree in 2022.
1. Can you become a Data Scientist without a Computer Science degree?
You can become a data scientist without any formal degree. For this, you can gain basic knowledge in data science through online resources, enroll in the best data science certification courses and boot camps, so that many people from non-technical backgrounds also make use of the vast opportunities in Data science as a career.
2. What should I learn in order to become a Data Scientist?
To become a data scientist, you need to be well versed in both technical and communication skills. R Programming, Python, Hadoop, SQL Coding, Spark, AI, Data Visualization, and Machine Learning, are the core technical skills you should be equipped with, and business acumen, strong communication skills, intellectual skills, teamwork, are the basic non-technical skills in demand.
3. Can I become a Data Scientist after passing 12th or Intermediate?
Yes, you can join a data science course after completing your 12th education. With online courses and certification courses, you can easily get into a data science career post successful completion. Students from computer or science backgrounds are preferable and can apply for any of the above-recommended data science courses even without a degree.
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