2014 Course Report Alumni Outcomes & Demographics Study


Liz Eggleston

Written By Liz Eggleston

Last updated on October 23, 2020

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We're excited to present the results of our 2014 survey of graduates in the bootcamp space. We surveyed graduates from 48 qualifying programming schools and received 432 responses from graduates that met the criteria.

The majority of graduates of coding bootcamps are finding full-time employment, and 75% of graduates surveyed report being employed in a full-time job requiring the skills learned at bootcamp, with an average salary increase of 44%.

Thanks to Launch Academy for creating the following infographic to further explain these findings:

Thanks so much to the schools who participated in this study and helped distribute it to their alumni networks! Read the full report as a PDF, which includes additional data and details on our methodology.

Key Findings

In our first graduate survey, and the first cross-school study of its kind in the programming bootcamp industry, we find strong evidence of salary growth, with respondents reporting a $25k average increase in their first job after attending a programming bootcamp.

Key Finding 1. Avg Salary Change

Change in Salary Before After Percent
All Respondents $52,809 $75,965 44%
Employed Full-Time $55,837 $80,607 44%


In addition, bootcamp attendees are more likely to work full-time after school.

Key Finding 2. Post Bootcamp Employment Status

 Post Camp Employment Status Before After
Employed full-time 48% 63%
Employed part-time 7% 4%
Employed freelance 10% 9%
Self-Employed 8% 6%
Student 7% 1%
Other 17% 2%
Unemployed 2% 14%

The report also finds:

  • 75% report working in a job requiring the skills learned at bootcamp, compared to 5% working as full-time programmers beforehand.
  • The average student paid $10k in tuition.
  • The typical attendee is 29, has 6 years of work experience, and has never worked as a programmer.
  • 38% of bootcamp attendees are female.


Student Demographic Profile

Respondents self-reported demographic information such as age, gender, and race. The student profile is summarized below in Table 1.

Table 1. Demographics

 Age Mean Standard Error
 Mean Age 29 0.7
 Gender % Standard Error
Female 38% 4%
Male 62% 4%
 Ethnicity % Standard Error
American Indian 0% 0%
Asian American 18% 3%
Black 1% 0%
Other 17% 4%
White 63% 4%
 Citizenship % Standard Error
Yes, born in the US 76% 4%
Yes, naturalized. 10% 3%
No 14% 3%
 Education % Standard Error
High school 0% 0%
Some college 10% 2%
Associate's degree 1% 0%
Bachelor's degree 71% 4%
Master's degree 15% 3%
Professional degree 2% 1%
Doctorate degree 1% 0%


Many programming bootcamps offer scholarships for women, so we compare our findings on gender enrollment to the 2013 Taulbee Survey, an annual survey of computer science programs at accredited universities. The Taulbee study estimated that 14.5% of 2013 bachelor degrees were awarded to females. Our study suggests that bootcamps compare favorably to traditional computer science departments (as well as masters programs) on gender diversity.

Pre-Bootcamp Work Experience

Most respondents were not employed as software developers prior to attending bootcamp, with an estimated 18% reporting developing software at work, and only 5% programming full-time prior to enrolling.

Table 2. Programming Experience

 Programming Background % Standard Error
 Full-time at work 5% 2%
Some at work 13% 4%
Some in my free time 41% 4%
None 37% 4%
Other 5% 2%


The average work experience among students is 6.3 years, although 17% report being unemployed prior to bootcamp enrollment.

Table 3. Work Experience and Salary

 Work Experience Mean Standard Error
 Years 6.3 0.7
 Salary Mean (USD) Standard Error
All respondents $52,809 $3,022
Those working full-time $55,837 $4,140
 Pre-Camp Employment Status % Standard Error
Employed full-time 48% 4%
Employed part-time 7% 1%
Employed freelance 10% 3%
Self-employed 8% 2%
Student 7% 3%
Unemployed 17% 4%
Other 2% 1%

Applications + Tuition

Most graduates report applying to gain a job as a programmer (74%), although 8% report attending in order to start their own business as a technical cofounder. Less than 1% report attending bootcamp to get a promotion or change jobs with their current employer.

Table 4. Applications

 Number of Applications Mean Standard Error
 Number of schools applied 1.6 0.1
Number of acceptance 1.3 0.1
 Reason for Attending a Bootcamp % Standard Error
Getting a Programming Job 74% 4%
Starting a Company 8% 2%
Getting a non-technical job 7% 3%
Other 7% 2%
Freelancing/contracting 2% 2%
Getting a promotion 1% 0%


Average tuition is $10k, with most students paying for school themselves or with the help of family (79%). Some schools offer tuition reimbursement for students who receive job placement through the school, and 15% of students report receiving such reimbursements.

Table 5. Tuition & Funding

 Tuition Mean Standard Error
 Tuition $10,267 $423
 Source of Funding % Standard Error
Self 64% 4%
Family 25% 3%
External Loan 3% 1%
School (Scholarship) 3% 2%
Employer 1% 1%
 Tuition Refund for Job Placement % Standard Error
Yes* 15% 3%
No 85% 3%

School Services, and Satisfaction

Career Services

Many schools offer services to help prepare students for the job market. Almost all students report receiving some form of assistance.

Table 6. Career Services

 Resume Preparation Assistance % Standard Error
 Yes 87% 3%
No 13% 3%
 Apprenticeship/Internship Placement % Standard Error
Yes 60% 4%
No 40% 4%
On-Site Interviews % Standard Error
Yes 42% 3%
No 58% 3%
 Job Placement Assistance % Standard Error
Yes 58% 3%
No 42% 3%

School Satisfaction

Graduates report an average satisfaction rating of 8.1/10 and would recommend their coding bootcamp to a friend 7.9/10.

Table 7. School Satisfaction

Overall Program Satisfaction   Standard Error
Satisfaction (1-10) 8.1 0.2
Recommended (1-10) 7.9 0.2

Post-Bootcamp Employment

Overall, 75% of graduates report being employed full-time in a job requiring the skills learned at bootcamp. Among those, most (63%) are in salaried position, with others reporting working as an independent contractor or running their own business.

Table 8. Post Bootcamp Employment Status

 Post Camp Employment Status % Standard Error
Employed full-time 63% 4%
Employed part-time 4% 2%
Employed freelance 9% 3%
Self-Employed 6% 3%
Student 1% 1%
Other 2% 1%
Unemployed 14% 3%
 Employed in a Programming Job % Standard Error
Yes 75% 4%
No 25% 4%
 Salary (USD) Standard Error
All Respondents $75,965 $9,892
Employed Full-Time $80,607 $13,425

Participating Schools

Not disclosed in this report. Here is an updated version of the Graduate Outcomes + Demographics Study, which includes participating schools.


We surveyed graduates from 48 qualifying programming schools, commonly referred to as bootcamps. We received 432 responses from graduates that met the criteria described below. The surveys were sent to graduates and all figures are self-reported by the respondents.

Inclusion Criteria

Programming bootcamps: to qualify for inclusion in the survey, a school must (a) offer full-time, in-person instruction of 40 or more hours of classroom time per week, (b) not be associated with an accredited college or university, (c) provide programming-specific curriculum (schools specializing in product development, design, or marketing were excluded), and (d) be based in the United States or Canada. Many schools offer courses at multiple campuses across a wide range of curriculum.


To qualify for inclusion in the survey, individuals must have completed a course offered by a programming bootcamp (as defined above) prior to June 1, 2014.


Because bootcamps likely varied in the extent to which they distributed and advertised the survey to students, it is unlikely that our raw sample is representative of the overall population of students. To adjust for varying sampling probabilities across schools, we post-stratify the sample on school using the known (2013-2014) bootcamp sizes from a recent Course Report survey. Respondents are weighted such that the in-sample distribution of respondents across camps matches as closely as possible the known distribution of bootcamp sizes. Therefore, our estimates rely on a much weaker assumption than random sampling—we only need to assume that respondents are effectively randomly sampled within school strata.

Missing Data

Some respondents elected not to respond to certain questions (such as salary). Unless this non-response is completely random, dropping these respondents when calculating means would induce bias in the estimates. The current best practice for dealing with missing data is to impute multiple estimates of the missing values using a statistical model and the observed data. We use the multiple imputation algorithm developed in King, Honaker, Joseph and Scheve (2001) and implemented in the Amelia software package for this purpose.


Course Report, founded in 2013 by Adam Lovallo and Liz Eggleston, operates https://www.coursereport.com/, which helps potential students find and research coding bootcamp programs. Course Report offers a directory of schools, course schedules, thousands of reviews, and interviews with teachers, founders, students, and alumni.

About The Author

Liz Eggleston

Liz Eggleston

Liz Eggleston is co-founder of Course Report, the most complete resource for students choosing a coding bootcamp. Liz has dedicated her career to empowering passionate career changers to break into tech, providing valuable insights and guidance in the rapidly evolving field of tech education.  At Course Report, Liz has built a trusted platform that helps thousands of students navigate the complex landscape of coding bootcamps.

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