If you have a background in computer science or statistics, enrolling in a data science bootcamp might be the smartest choice you make to expand your skills and propel your career to new heights.
Data scientists boast a unique combination of experience in advanced programming and statistical analysis. As an emerging yet competitive industry, finding job applicants with the right set of skills is not an easy task.
Still, major companies need qualified data scientists to develop predictive machine learning systems and neural networks, make sense of Big Data, using predictive modeling techniques and much more. That’s why qualified data scientists are in high demand right now and jobs in the field are expected to grow 25% over the next ten years.
Data science bootcamps teach students the hands-on skills and experience they’ll need to land jobs. Most bootcamps run for about 12 intensive weeks, covering relevant projects and tools students will use on a regular basis throughout their career.
Not sure if data science bootcamp is the right choice for you? This guide answers questions and explains topics like:
A data science bootcamp prepares students for careers in the industry with relevant skills in Python programming, data analysis, machine learning, and more. Most bootcamps are immersive, covering several skills and concepts in a short amount of time.
As far as benefits go, a quality data science bootcamp can supply several opportunities that benefit students for years to come.
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The Benefits of Completing a Data Science Bootcamp |
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Building skills in data analysis and programming to seek work as a data scientist |
Curriculum based on industry standards from top companies |
Material regularly updated to meet the job’s latest demands |
Hands-on projects to build your experience portfolio and resume |
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Career assistance like expert resume reviews and interview preps |
Gain extensive knowledge and experience in a short amount of time |
Access to alumni network and insider data scientist communities |
Potential projects and internships with top companies |
Data science bootcamps often enlist industry hiring partners to help draft and update the curriculum and real-world data challenges. This ensures students learn the most applicable skills for existing job roles and prepare them for roles as data executives.
Plus, the hands-on projects mimic job tasks and expectations. Junior Data Scientist can enter the field prepared with a relevant portfolio, potentially with internship or project experience at leading companies.
Many data science bootcamps also offer extensive alumni networks and career assistance. Thanks to their corporate partnerships, many bootcamps can offer useful advice like industry-specific resume tips or mock interviews.
Data science bootcamps aren’t ideal for everyone. Quality bootcamps are intensive, designed to cover a wide range of material in just 12 weeks or so. Curriculums usually assume students have already mastered certain programming and statistical analysis skills.
If you meet the criteria below, you might be a good applicant for data science bootcamp.
Hold a Bachelor’s Degree or Master’s Degree in a Relevant Field
Degrees aren’t mandatory. However, students who lack college-level statistics or programming knowledge will struggle to complete the coursework.
A quarter of data scientists start their careers with bachelor’s degrees in mathematics, statistics, or computer science – the most relevant fields. Most data scientists, however, hold a master’s degree or Ph.D. in computer science or statistics.
Advanced Knowledge of Python and Statistics
Students should only enroll in data science bootcamp after they’ve mastered skills like Python, R programming, data analysis, and data visualization. If you’re lacking in one of those, take the bootcamp prep to build your skills.
Dedicated Time and Commitment to Complete the Bootcamp
Bootcamps cover extensive material in a short time – often 12 weeks. Part-time online bootcamps may only demand 20 or 30 hours of time each week, running 24 weeks.
Either way, make sure you’re prepared to devote your full-time energy and attention to the bootcamp coursework.
Prepared for the Job Role Demands of a Data Scientist
Data scientists use their advanced programming knowledge to help companies understand data and use it to make predictions.
Companies will use your work to guide major decisions relating to budgets, logistics, trends, sales, and operations. Data scientists lead a company’s future in many ways so understanding the gravity of the role is critical.
Completing a bootcamp will give you a beginner and intermediate level knowledge of data science with skills like data analytics in Python, machine learning, Big Data, and more.
A quality bootcamp should provide hands-on experience in the tools, data analysis, and programming you’ll use every day as a data scientist on the job. You’ll also learn about potential career paths and opportunities to develop specialized skills.
The chart below outlines the skills and knowledge you should have after completing a data science bootcamp.
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What Do You Learn in a Data Science Bootcamp? |
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SQL database |
Data analysis with Python and R |
Machine learning with Python and R |
Building statistical models |
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Linear regression |
Data classification and visualization |
Hadoop, Spark, and AWS |
Big Data |
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Deep Learning |
TensorFlow |
Natural Language Processing |
Shiny and iPython |
The bootcamp might break up these skills into different modules based on the overarching skill like this:
Most bootcamps operate either remote-live, in-person, or online with expert instructors. Quality bootcamps also provide mentors to guide you through the coursework as needed.
A data science bootcamp should provide some kind of certificate upon completion and hold a license to operate as a school within its state.
Data science bootcamps teach students to blend two separate disciplines: data analysis and programming. Students should enroll in a data science bootcamp once they’ve mastered both fields independently.
Most students who enroll in data science bootcamps hold a bachelor’s degree or master’s degree in computer science or statistics. These degrees give you the best leverage to complete the bootcamp coursework and projects efficiently.
Specifically, you’ll need these programming and analysis skills before jumping into a bootcamp.
Statistical Analysis
Math is guaranteed in data science. Make sure you have a college-level understanding of calculus, algebra, and statistics before enrolling in data science bootcamp.
Python Language
Bootcamps need students to understand Python as it relates to data wrangling: manipulating files so they’re prepared for analysis. You’ll also need to know how to use data structures in Python for analysis and visualization.
Some basics include:
Need an introduction to Python or R programming for data analysis? Take the data science bootcamp prep course.
R Programming
You’ll also need a comprehensive grasp of R for transforming data and completing various functions for data analysis. Some important R programming prerequisites include:
It depends on the bootcamp. A data science bootcamp is worth your investment if it teaches you how to use Python and R programming for data analysis, manipulation, and machine learning with relevant tools and projects.
A worthwhile bootcamp should prepare you for the daily demands of an entry-level data science job. To do that, you’ll need to learn how to apply advanced Python concepts to data analysis and visualization techniques, merging the two disciplines.
If a bootcamp covers basic data analysis, Excel, or an introduction to Python as standalone concepts, it’s probably not worth the time and money.
Use this chart as you research data science bootcamps to make sure they’re worth your time.
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How to Tell if a Data Science Bootcamp is Worth the Time and Money |
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Assessments to ensure your skills match the bootcamp prerequisites |
Hands-on projects that mimic job scenarios to build your portfolio |
Involves industry tools like Tableau, Hadoop, and TensorFlow |
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Denying enrollment to students who aren’t prepared |
Teaches how to apply R and Python to data analysis and visualizations |
Teaches how to use R and Python for machine learning processes |
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Partnering with leading companies for course and project development |
Offers career assistance and networking services |
Transparent application process, bootcamp outcomes, and curriculum |
Data science bootcamps can offer incredible skills and opportunities for the right students. However, they also pose plenty of challenges you should consider.
Pro: Build an Entire Skillset in Just a Few Weeks
Most data science bootcamps run between 12 and 24 weeks. During that short time, you’ll learn advanced programming, predictive analytics, data visualizations, machine learning, and more. You’ll complete the course with a full set of fresh skills.
Con: A Potentially Overwhelming Amount of Coursework
Learning an entirely new field within just a few weeks is incredibly intense and demanding. Make sure you’re prepared to give the bootcamp full-time attention and that you have the right Python skills before enrolling.
Pro: Create a Professional Network and Unlock Career Opportunities
You can connect with thousands of other bootcamp alumni, students, and professionals if the bootcamp offers a network. Many bootcamps also partner with companies for internships, projects, and job placement.
Con: No Guarantees of Landing a Job or Career Success
No bootcamp can guarantee you’ll get hired for a certain job or any job. They can only provide transparent information on what you’ll learn during the bootcamp to prepare you for job roles.
Pro: Complete the Bootcamp Prepared for an Entry-Level Data Science Job
Once you complete the bootcamp, you’ll have the skills and project experience you need to apply for real data scientist jobs at leading companies.
Research roles like data scientists are expected to grow 25% over the next ten years – making qualified data scientists a top demand for companies. Data scientist jobs also offer excellent salary opportunities with a median salary of $85 per year.
Con: Uncertainty You’ll Enjoy Data Science as a Long-Term Career Path
Data science is often a tedious and intensive job. It’s impossible to know whether you’ll feel satisfied with data science as a long-term career path from a bootcamp alone.
The unknown nature of predictive data means you’ll explore different solutions through trial and error – and explain the process to other non-data science departments so they can use it.
Yes. In fact, many companies partner with bootcamps for help with projects or finding talent – from startups to international corporations.
Students complete over 400 hours of training and experience so companies familiar with the bootcamp know applicants are prepared for demands of the job. Companies may also share projects with the bootcamp when they need help. Students can use to earn experience and get a foot in the door at leading companies.
However, a data science bootcamp cannot guarantee a job. They can only offer job placement assistance.
The chart below explains how a data science bootcamp might provide career assistance.
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What Kind of Job Placement Can a Data Science Bootcamp Provide? |
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Resume reviews and advice for LinkedIn improvements |
Real-world project opportunities from corporate partners |
Meetup events to network with peers of all levels |
Continuing education in advanced data science concepts |
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Mock technical interviews and interview workshops |
Corporate hiring partner events with presentations and networking parties |
Industry expert speakers |
Coding tasks and projects relevant to industry demands |
Not all data science bootcamps will provide every type of job placement assistance mentioned here.
Data science bootcamp is a huge commitment on multiple levels so you’ll want to ensure you’re prepared before enrolling. Preparation will give you the best chance of success. Use this checklist.
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Your Pre-Bootcamp Checklist |
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Programming skills |
Make sure you have the required level of Python and R experience to manipulate and transform datasets. |
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Mathematics |
Brush up on calculus, algebra, and statistics. |
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Data analysis skills |
Know the different data structures and visualization modules used in Python and R for data science. |
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Time commitment |
Check the bootcamp start dates and duration to clear your schedule of major commitments so you can devote your full attention to the coursework. |
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Financing |
Figure out how much the bootcamp costs to complete and what kind of financing or assistance the school offers. |
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Career path |
Think about your long-term career goals post-bootcamp and see how they compare to continuing education – like machine learning, big data, or deep learning. |
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Bootcamp prep |
See if the bootcamp offers a prep package and complete any relevant material to ensure you’re ready. |
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Application |
Look for any specific requirements before filling out and submitting your bootcamp application. |
With the right background skills and knowledge, you could start a fresh career in data science just three months from now.
NYC Data Science Bootcamp teaches students the full set of tools and hands-on experience they need to apply for entry-level job positions as data scientists at top companies: R, Python, Hadoop, Spark, machine learning, and much more.
Start your data science career journey now. Learn the skills you need in 12 weeks. Click the button and apply now.