How to Choose a Data Science Bootcamp

Data science bootcamps are intensive and immersive courses that teach advanced data science skills to individuals pursuing a career in the field. Offering a crash course in everything from Python to SQL, data visualisation, Hadoop, and more, these bootcamps can equip course takers with a deep knowledge of fundamental concepts and advanced techniques.

Learn more about the various data science bootcamps and how to consider which is right for you.  Explore the difference between a data science bootcamp and a degree, and the different ways to engage in a bootcamp.

Data science bootcamp vs data science degree 

Data science bootcamps and degree programmes both help prepare people for careers in the field. But, if you already have an undergraduate degree in an unrelated field, then a bootcamp could be a great way to gain the skills you need to start in data science.

Many people who enroll in a bootcamp hold an undergraduate degree in an unrelated field and want to get formally certified in data science so that they can pursue a career in the field. You can also earn a data science degree, but you’ll find considerable differences. These differences include:

How to choose the right data science bootcamp for you

The right bootcamp is the one that helps you reach your career goals and build the appropriate skills you need to land a job, fits your current budget, and works with your personal time frame. Use the steps below to pick the right bootcamp for you.

1. Outline your career goals. 

While many data science bootcamps cover similar material, each has its focus that can be important when pursuing a specialised career.

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

• Where do you want 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?

Answering these questions will help you gain greater clarity on the programme you can use to reach your career goals.

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 

2. Research job requirements. 

Once you've outlined your career goals, you should research the skills and qualifications you need to obtain to perform the job. Many data science jobs require you to possess a specific skill set to that particular position, which may differ somewhat from those 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 visualisation 

• 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. 

3. Assess your current skills. 

You’ll succeed most with data science bootcamps if you already have some core foundational data science knowledge. Bootcamp instructors move fast, and you’ll likely complete projects requiring background knowledge. Classes are usually limited to mastering key high-level skills and building your career toolbox. 

There won’t be much time to review basic concepts, so assess your skills to learn what type of bootcamp would best fit you. If you need to focus more on the basics, look for a data science bootcamp for beginners or consider taking an online course to improve or expand your skills, such as the University of Michigan's Python for Everybody Specialisation. 

4. Research programmes. 

Most data science bootcamp programmes last three to six months, and the cost will vary by location and institution.

When researching programmes, 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 organisation offering the bootcamp. Also, check for any prerequisites before applying for a programme.

5. Consider structure and location.

One of the key questions you will face when comparing different data science bootcamps is whether you want an online, in-person, or hybrid programme. 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 bootcamps provide more structure in a hands-on environment, with an instructor ready to help.

In-person classes can also be a networking opportunity to build people skills like teamwork and collaboration. However, if you want to enroll in a bootcamp that isn’t local or have a busy schedule, this option may not be flexible enough for you.

Online courses

Online programmes can be convenient for joining a bootcamp without sacrificing a comprehensive education. Capable of being completed anywhere with an internet connection, you can often do an online bootcamp 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 programmes.

Hybrid courses

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

6. Take note of relevant topics.

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

• Python programming 

• Machine learning

• Coding

• Statistics 

• A/B testing

• Intermediate Excel 

• Linear regression

• Databases (MySQL, MongoDB, etc.) 

Don’t expect to be taking notes all day in these bootcamps. Most are project-based, hands-on programmes offering 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 bootcamps can cost between 300 USD and 16,500 USD, depending on the school or organisation [1, 3]. While you have to consider these costs yourself, Indian employers are showing a keen interest in learning and development and upskilling staff. 

8. Research institution reputation. 

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

• Alumni and student reviews

• Well-established (programme 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 selectivity of the application process 

These requirements might sound like a lot to consider, but you’ll find free online resources that rank data science bootcamps. Combine these resources with your own research to track down the top programmes relevant to your interests. 

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

9. Decide if a data science bootcamp is right for you.

You’ll find many benefits to data science bootcamps, but knowing if this learning style is right for your overall career goals is essential. Consider these common benefits and drawbacks to data science bootcamps:

• Limited financial aid: Bootcamps 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 bootcamp programme. 

• Efficient but intensive: If you want to get into data science fast, bootcamps can be your fast rack in the door. Though the entire programme runs for just a few months, expect to be immersed in data science. This can be a problem if you already hold a full-time job.

• Career-focused: When you enroll in a data science bootcamp, 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 programmes. 

10. Apply.

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

Depending on the programme, the enrollment process may include a call with a programme representative, an application, and an assessment before acceptance.

Alternative options to data science bootcamps

You have options if you decide a data science bootcamp isn't right for your goals. The list below outlines a few similar offerings from industry leaders in technology:

• IBM Data Science Professional Certificate: This 100 percent online, self-paced programme is designed to cover all the latest job-ready skills and tools. Using real-world data sets, you'll work with open-source tools and libraries, databases, and the IBM Cloud. By the end, you'll have built a portfolio of projects and earned a Professional Certificate from IBM.

•  Google Data Analytics Professional Certificate: Seventy-five percent of Google Career Certificate Graduates in the US report an improvement in their career trajectory within six months of completion. In this programme, you'll gain data cleaning, ethics, and visualisation skills while working with industry tools and platforms like SQL, Tableau, and R programming. You'll earn a Professional Certificate from Google for your resume upon completion.

Start learning data science today

Bootcamps are a great option and alternative to a degree if you want to save money and complete a course faster. Depending on your budget, career choices, and experience level, you'll find various options. 

When you're ready to advance your data science career, consider enrolling in the first course, What is Data Science?, of the 10-part series in IBM's Data Science Professional Certificate. All you need to make a start is basic computer literacy and the willingness to learn online.