If the numbers are any indication, opportunities to learn data science are not slowing down anytime soon. IBM predicts that demand for data science professionals will grow 28% by 2020, with up to 700,000 new job openings.
The trend has prompted many prospective bootcamp students to wonder what they need to break into the field. The good news is that companies are increasingly looking to non-degree programs like bootcamps to discover talent, and there is more opportunity than ever for junior data scientists who come from different backgrounds.
At SwitchUp, we help students around the world discover the perfect data science bootcamp. We’ve found that the four tips below can help any student, regardless of background or skillset, to get the most out of a data science bootcamp.
1. Weigh your options
There is no “one size fits all” for becoming a data scientist: prospective students can choose from online and offline programs that vary in length, price, and curriculum. Students can also pick from a range of master’s programs and intensive bootcamp options.
To identify the best option for you, take a closer look at your own learning needs, and potential barriers like financing. Consider the following during your research:
- How important is flexibility? For some, it is simply not an option to drop everything to attend an immersive bootcamp. Think carefully about your finances and commitments to decide if this type of program is your best option. You may find that an online or part-time program is the better fit for your needs.
- How quickly will you land a job? Most data science master’s programs require between 18 months and two years to complete. A bootcamp, on the other hand, typically lasts 10.8 weeks, according to SwitchUp’s research. Depending on how quickly you will need to land a job, your timeline will make all the difference.
Be sure to review your school’s job placement rates, as they can help you plan a job search timeline. Many bootcamps publish outcomes reports with the percentage of alums who land jobs in their field, and the average amount of time that they spend searching.
A bootcamp can yield immediate results for some students. At Springboard, for example, the average career track data science student receives a job offer before the program even ends!
- Learning style: A bootcamp is an intense experience, and even part-time or flexible programs require a huge amount of time and effort. If you are choosing to switch careers with a bootcamp, you’ll want to make sure that you can completely focus on the commitment.
2. Check out online reviews
Once you’ve decided on the ideal format for your data science education, you’ll want to read through reviews to make sure that prospective programs live up to expectations. To get started, check out a site like SwitchUp.org, where you’ll likely find verified alumni reviews for data science bootcamps like Springboard.
Reviews can give you a first-hand look at a bootcamp outside of marketing claims or statistics. They can also shed light on post-bootcamp life at a variety of stages; from the first job search right after graduation, to an alum’s outlook once they are settled in new tech career.
3. Prepare with free resources
Data science covers some complex topics, and it’s important that you have a few core competencies under your belt. Bootcamp students should have an understanding of statistics and a programming language like Python, as well as core math subjects like linear algebra and calculus.
Naturally, these requirements can sound daunting if you are making the transition from a less technical background. Fortunately, there are many free or low-cost resources to help you get started. We recommend the following:
- Learn Python the hard way: Python is a common language in the world of data science, and this book is often cited as the most complete introduction. Even if you focus your education on a different language, like R, the book will help you begin to think like a data scientist.
- Edx data analysis and statistics classes: For those looking to brush up on statistics, free online classes and MOOCs can be a great place to get started. Edx offers a complete roundup of data analysis and statistics courses. Take a look here.
- Springboard’s Introduction to Data Science course: Prepare for a data science intensive with this excellent introductory course from Springboard, where you’ll build a foundation in R programming and statistics with the help of 1:1 mentor support.
4. Put your career plan in place
Data science can prepare you for a range of job responsibilities and titles. While it can be tempting to learn a little bit of every skill and language, we encourage students to stay focused on a plan.
Before the bootcamp starts, jot down your career goals. Are you more interested in analyzing large data sets, or writing software? Do you envision yourself at a large company or a startup?
Next, think about your ideal job market. Research a few common roles, like data analyst, data scientist, and data engineer, and use a job search site like Indeed.com to research demand, job descriptions, and salary data for your desired area.
A clear roadmap will help you navigate your career change, and set you up for success in a new data scientist role.
To get your career change started, check out what students have to say on SwitchUp’s Springboard reviews page.