Can You Really Become a Data Professional in 10 Months?

Changing careers may seem time-consuming, but the truth is that starting a career in tech in just 10 months really is possible. Data Science is among the top 20 fastest-growing occupations in the U.S. and current trends show that job openings will continue to increase.

Individual using laptop to analyze marketing materials.

Data scientists and analysts are experts that excel in gathering and analyzing data, utilizing both tech-based and business-based skills to solve problems, identify trends, and make data-driven decisions on company direction and choices. 

For these reasons and more, data professionals are highly sought-after and heavily relied on by many different companies and organizations alike.  

What is Data Science?

Simply put, Data Science is the act of studying and organizing data and interpreting that data to inform an organization’s decisions. 

For example, food delivery apps utilize data from weather, traffic, and peak restaurant hours to provide an accurate estimation of how long it will take to deliver your order. It can go even further when the data from your order can then be used to recommend similar restaurants based on data such as distance and how you rated it through their app. 

Data professionals then structure the data from these sources into data sets and use them to help their team make confident decisions. For these reasons and more, data professionals are highly sought-after and relied on by many different companies and organizations alike.

Is a Degree Necessary to Enter the Data Science field?

No. While you certainly can receive a bachelor’s and master’s degree in Data Science, it is not a firm requirement to enter the field. 

Last year employers posted more than 365,000 openings in the industry, and many of them went unfilled. In fact, the number of openings is expected to continue growing by 28% in the next 10 years. 

What does this mean for you?

Since the demand for data scientists is so high and will only continue to grow, many companies no longer state a college degree is required on their job postings. This includes top companies such as Google, Apple, and IBM. This means that you learn the skill set, receive industry certifications, and break into tech in less than a year.

Where Do I Start?

You don’t need to be a computer expert to pursue a career in data science. Many people who pivot to a career in tech begin in non-tech sectors such as customer service or hospitality. The first step toward starting a career in data science is to receive proper training. 

Here are some of the different paths available to getting your foot in the door. 

The traditional route of a four-year degree can be a great way to network and learn computer science fundamentals. However, many individuals may find that a traditional degree can be a difficult route to take due to other financial or familial commitments. 

Self-training can potentially allow you to learn several concepts and skills at a fraction of the cost. Learners can find online classes, networking and internship opportunities, and study the subject on their schedule. With enough self-training you may be able to achieve industry certifications; however, the learning curve can be difficult if you have no previous exposure.   

Accelerated career-prep programs are an excellent option if you’re looking for hands-on training based on your level of experience, all with a more flexible schedule. This route of training is usually favored by many thanks to its flexibility, price tag, and fast pace.

If you’re unsure if this is the right move for you or you just want to learn more about the industry, The College of Professional and Continuing Education at California State University, Long Beach offers a free online course in data science and analytics to help you learn what data science is, why data professionals are in high demand, how it plays a role in the modern world, and more.

What Career Path is Right for Me?

Top view of paper man on career ladder on blue

There are several in-demand roles available to you in the data science industry, each with different specializations. Because of this, it’s worth doing some research to figure out which position appeals to you and best uses your current talents.

Here are a few entry-level career paths to consider:

  • Data Scientists utilize programming skills, coding, and other disciplines to sort and manage large data sets to be used by the organization to help make informed decisions.
  • Data Analysts study data sets to ensure that the information can be used to meet the needs of the business and simplify the facts found within those data sets.
  • Data Engineers primarily build and structure data into easily used formats that data scientists can then use in their respective position. 
  • Machine Learning Experts primarily utilize artificial intelligence (AI) to allow other programs to predict trends based on different algorithms. These experts will create and utilize these algorithms to get ahead of the curve.

What Skills Do I Need?

While a doctorate or other traditional degree is not necessary to break into the industry, learning some specific skills will greatly increase your chances for success. 

These can be broken down into hard skills and soft skills. Hard skills are technical competencies specific to the field, soft skills are interpersonal abilities that can apply in a variety of social and professional settings. 

Chances are that you likely already have some of these skills but we still recommend participating in a data science and analytics training program to develop and refine them.

Here are a few examples of both.

Hard Skills for Data Professionals

  • IT infrastructure
  • Business intelligence
  • Database knowledge (SQL)
  • Stats and probability
  • Proficiency in a programming language (Python)
  • Machine learning

Soft Skills for Data Professionals

  • Communication 
  • Taking initiative 
  • Public speaking
  • Curiosity
  • Time management
  • Creativity

How Do I Showcase My Data Knowledge?

As we previously stated, having a degree is not necessary to start a career in data science, but you will need a way to display your knowledge and skill set to potential employers. 

  • E-portfolios are an excellent way to share real-world, practical examples of your work and showcase what you can do. They also allow you to examine your own strengths as a data professional and can exhibit what skills you could acquire next as you break into the industry.
  • Industry certifications are extremely valuable for many reasons. Not only are they a learning opportunity, but they can also allow you to potentially increase your earning potential and establish professional credibility in the field. 
  • Networking with other professionals and ensuring that you are active on sites like LinkedIn is also a great way to display your knowledge. Sharing your own experiences and interacting with others helps demonstrate your willingness to grow and be a lifelong learner.

With the Data Science & Analytics Bootcamp coming soon to the College of Professional and Continuing education at CSULB, you can develop an e-portfolio through our project-based learning and prepare for recognized industry certifications. Our career services team is dedicated to assisting you with LinkedIn profile optimization, job placement assistance, networking opportunities, and so much more.   

Become a Data Professional with the Data Science & Analytics Bootcamp at CSULB

Letter board stating make yourself proud.

So, can you begin a new, fulfilling career in tech in less than a year? Absolutely! 

The Data Science & Analytics Bootcamp offers fully online courses led by active data science experts. In just 10 months you can enter one of the most rapidly growing industries with the knowledge and in-demand skill set that employers are hiring for. 

If you’re looking to enroll today or if you have a few questions we’re here to help! Feel free to check our FAQ on the bootcamp or get in touch with our admissions advisors by calling 562-359-4787 or filling out the form below. 


Skip to content