How to Choose a Data Science Boot Camp

Key takeaways

• To choose a data science boot camp, start by outlining your career goals, researching job requirements and programs, determining your current skill level, and considering the program structure.

• Taking a data science boot camp online can offer benefits such as flexible, self-paced learning from anywhere. However, it may offer fewer networking and team-building opportunities than in-person programs.

• A data science boot camp can be worth it if you want affordable, practical education that can potentially improve your salary, expand your network, and advance your job prospects.

A data science boot camp might cover topics like data visualization, data analytics, data modeling, Python, SQL, artificial intelligence, and Hadoop. Discover the difference between a data science boot camp and a data science degree, as well as how to pick the right boot camp for you, in the following article.

Afterward, if you’re ready to build your data science skills, consider enrolling in the IBM Data Science Professional Certificate as an alternative to a boot camp or to reinforce what you learn in one. You’ll have the opportunity to gain experience with the tools, languages, and libraries used by professional data scientists, including Python and SQL, as well as learn how to import and clean data sets, analyze and visualize data, and build machine learning models and pipelines in as little as four months. You’ll also earn a shareable credential upon completion.

What is covered in a data science boot camp?

Data science boot camps cover advanced data science skills through intensive and immersive courses. Offering a crash course in everything from Python, SQL, and data visualization to Hadoop and Spark, data science boot camps can equip you with a deep knowledge of the fundamental concepts and advanced techniques you’ll need to pursue a career in the field. You will also learn about statistics, artificial intelligence, machine learning, and data analytics and modeling, and you might even receive interview preparation and resume tips.

Data science boot camp vs. data science degree

Data science boot camps and degree programs can both prepare you for careers in the field. If you already have an undergraduate degree in an unrelated field, however, then a boot camp could be a great way to gain the skills you need.

Many people who enroll in data science boot camps hold undergraduate degrees in unrelated fields and seek formal certification in data science to pursue a career in the field. Since data science boot camps provide the essential skills you’ll need to start a data science career, many professionals transitioning into this field prefer a boot camp over a degree.

You can also earn a data science degree, but you’ll find considerable differences between the two. Boot camps are a cost-effective and faster alternative to degree programs, whereby you’ll obtain targeted, practice-oriented training for relevant jobs; have the chance to build a portfolio of projects; and prepare for entry- to mid-level roles like data analyst, machine learning engineer, and business intelligence analyst. However, if you’re seeking in-depth data science knowledge along with practical experience and want to move into senior or specialized data science positions, a degree program might be the better choice. Explore a detailed comparison of their differences below:

Read more: Data Science Major: What You Need to Know Before Declaring

How to choose the right data science boot camp for you

The right boot camp is the one that helps you reach your career goals, builds the appropriate skills you need to land a job, fits your current budget, and works with your personal time frame. Review each step below to pick the right boot camp for you.

1. Outline your career goals.

While many data science boot camps cover similar material, each also has its own focus that can make a difference when you are pursuing a specialized career in the field.

To choose the right boot camp for yourself, you need to identify and outline your career goals so that you can match a program to your own professional interests. Some questions that you might ask yourself include:

• Where do you want your career to be in five years?

• Are you seeking an entry-level position or an upper-level position?

• Are you already employed and want a promotion, or are you starting your career?

• What skills does your career goal require?

By answering these questions, you’ll gain greater clarity on the kind of program you can use to help reach your career goals.

2. Research job requirements.

Once you’ve outlined your career goals, you can now research the skills and qualifications you will need to perform the job. Many data science jobs require you to possess a skill set specific to that particular position, which may differ somewhat from those that you already possess. A few of the most common technical and workplace skills you may find in the field of data science include:

• Communication

• Teamwork

• Creativity

• Perseverance

• Problem-solving

• Knowledge of programming languages, such as Python or R

• Databases

• Machine learning

• Data visualization

• Big data frameworks

Research postings for desirable jobs and read the descriptions to get a good idea of what skills you’ll need before applying.

Popular data science careers

Data science is a broad field that includes artificial intelligence, cybersecurity, machine learning, and more. As a result, you’ll find many careers that you can pursue in the field. Some of the most popular data science careers include:

• Data engineer

• Statistician

• Data analyst

• Machine learning engineer

• Data scientist

3. Assess your current skills.

You’ll have a higher chance of benefiting from data science boot camps if you already have some core foundational data science knowledge. Boot camp instructors move fast, and you’ll likely be completing projects that require some background knowledge. Classes are usually limited to mastering key high-level skills and building your career toolbox.

The boot camp may offer limited time for reviewing basic concepts, so assess your skills to know what type of boot camp would be the best fit for you based on your skills. Consider your level of expertise in areas such as programming, statistical and quantitative reasoning, and maths, which are fundamental to data science. If you need to focus more on the basics, look for a data science boot camp for beginners or consider taking an online course to either build or expand your current skills, such as the University of Michigan’s Python for Everybody Specialization.

4. Research programs.

Most data science boot camp programs last three to six months, and costs vary by location and institution.

When researching programs, consider what class structure works best for your schedule, what skills you need to learn based on your career goals, and the integrity of the institution or organization offering the boot camp. Make sure to check for any prerequisites before applying for a program as well.

5. Consider structure and location.

One of the key questions you will face when comparing different data science boot camps is whether you want an online, in-person, or hybrid program. Each of these different educational approaches has its own benefits, depending on your goals, available resources, and personal circumstances.

In-person classes

Typically, in-person boot camps provide more structure in an active-participation environment, with an instructor ready to help you as needed.

In-person classes can also be a networking opportunity and a chance to build people skills like teamwork and collaboration. However, if you want to enroll in a boot camp that isn’t local or you have a busy schedule, you may find that an online option is more flexible for you.

Online courses

Online programs can be a convenient way to join a data science boot camp without sacrificing a comprehensive education. You can complete online boot camps from anywhere with an internet connection, and you can often work at your own pace. While some may have an instructor on call when you need help, others may be more self-directed and independent. However, online courses may not provide as many opportunities for networking and team-building practice as in-person programs.

Hybrid courses

Hybrid courses offer the pros of both online and in-person courses. With a hybrid-style data science boot camp, you can experience the immersion of in-person learning along with the convenience of online learning. This is an excellent option if you live near an institution but have a busy schedule, or if you want the flexibility of online learning alongside in-person classes.

6. Take note of relevant topics.

Some boot camps specialize in a specific field of data science or focus on a particular set of skills. However, you can generally expect to see a few of these topics in the coursework:

• Python programming

• Machine learning

• Coding

• Statistics

• A/B testing

• Intermediate Excel

• Linear regression

• Databases (MySQL, MongoDB, etc.)

You likely won’t be taking notes all day in these boot camps. Most are project-based, practical programs that offer you valuable skills to take into the workforce. Review the course content thoroughly to be sure it aligns with your career goals.

7. Know the cost.

Data science boot camps cost around $7,000 to $18,000, depending on the school or organization [1].

While you can’t use FAFSA to apply for financial aid as you can when earning a college degree, financial aid opportunities are available for some boot camps. These include deferred tuition, income-share agreements, and school financing. Some employers may also offer tuition reimbursement if you’re already employed but looking to move into a more senior role.

8. Research institution reputation.

Make sure that you choose a boot camp from a reputable institution or university. Characteristics of a quality program are likely to include:

• Alumni and student reviews

• Well-established (program offered for 3+ years)

• Published CIRR (Council on Integrity in Results Reporting) outcomes within the past year

• Variety of financing options

• Vetted lending partnerships

• Other factors, like the level of career support and the selectivity of the application process

Those requirements might sound like a lot to consider, but you can find free online resources that rank data science boot camps. Combine those resources with your own research to track down the top programs that align with your interests.

It’s also worth mentioning that employers or individuals already working in the industry may have recommendations for reputable boot camps that they could share with you.

9. Decide if a data science boot camp is right for you.

Data science boot camps offer many benefits, but it’s important to know if this learning style is right for your overall career goals. Consider these common benefits and drawbacks to data science boot camps:

• Limited financial aid: Boot camps are typically much less expensive than earning a degree, but be aware that it’s rare to find financial aid opportunities to help you cover the cost of a boot camp program. You may find success with school financing options or staggered payment plans.

• Efficient but intensive: If you want to get into the field of data science fast, boot camps can help you achieve that. Though the program is just a few months long, it will immerse you in all things data science. This can be challenging if you already have a full-time job.

• Career-focused: When you enroll in a data science boot camp, you’ll learn alongside like-minded individuals who are likely just as career-focused as you. You may also find career services and job assistance built into these programs.

10. Apply.

When you find a program that’s right for you and matches up with your career goals, it’s time to apply!

Depending on the program, the enrollment process may include a call with a program representative, an application, and an assessment prior to acceptance. Some data science boot camps to consider include:

• NYC Data Science Academy Data Science with Machine Learning boot camp

• The University of Chicago Data Science Bootcamp

• Johns Hopkins University Data Science Online Bootcamp

• 4Geeks Academy Data Science and Machine Learning boot camp

• Springboard Data Science Bootcamp

• Dallas Data Science Academy Gen AI Data Science Bootcamp

Is a data science boot camp worth it?

Enrolling in a data science boot camp can be a worthwhile investment in your career. Boot camps cost far less than earning a degree, and the initial cost can offer a strong return on investment, potentially boosting your salary after you complete the program. Data science boot camps frequently offer career placement assistance and networking opportunities. Additionally, many employers look for the skills and practical education you gain in a boot camp.

Alternative options to data science boot camps

If you decide a data science boot camp isn’t right for your goals, you have options. The list below outlines a few similar offerings from industry leaders in technology:

• IBM Data Science Professional Certificate: This 100-percent online, self-paced program covers all the latest job-ready skills and tools. Using real-world data sets, you’ll have the opportunity to work with open-source tools and libraries, databases, and the IBM Cloud. By the end, you’ll not only have had the chance to build a portfolio of projects but also earned a Professional Certificate from IBM.

I had never really thought of myself as a data-oriented person, but the way that the program was taught was easy to understand.

— Emma S., on taking the IBM Data Science Professional Certificate

• Johns Hopkins' Data Science Specialization: In this 10-part Specialization from Johns Hopkins University, you'll have the opportunity to learn critical data science concepts and tools needed to enter the field. You’ll have the chance to gain experience with using R to clean, analyze, and visualize data and perform regression analysis, least squares, and inference using regression models.

Build in-demand data skills with these practical resources

Subscribe to our Career Chat newsletter on LinkedIn to receive career insights, resume-building skills, and job search tips right to your inbox. Supplement your learning with our free resources for data science professionals:

• Watch on YouTube: 7 Must-Have Skills for Becoming a Data Science Rockstar

• Explore key concepts: Data Science Terminology and Definitions

• Structure your learning: Data Science Learning Roadmap: Beginner to Expert

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