Overview Leaderboard Methodology
Industry Report

Specialized Engineering Bootcamps

Bootcamps focused on specific technical tracks such as data science, UX/UI, cybersecurity, or mobile development that provide targeted, job-ready skills.

Brands tracked: 39
Brands analyzed: 39
Last updated: 2026-04-23
Model: OpenAI GPT-5
Prompts: 299
Total responses: 1,540
Top Brand Overall?
Springboard
67/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
GitHub
100

Highest score on the LBA metric in this industry.

Authority Leader?
Springboard
43

Highest score on the Authority metric in this industry.

TOM Leader?
Springboard
90

Highest score on the TOM metric in this industry.

Specialized Engineering Bootcamps has no dominant brand in AI responses

Springboard is the top-ranked brand here, but its overall score of 67 reflects a competitive field rather than a dominant player. AI assistants answer category questions about Specialized Engineering Bootcamps with varied recommendations from query to query - users get a different set of suggestions each time. This is the kind of category where mid-tier brands still have room to move up.

Brand Leaderboard All 39 Specialized Engineering Bootcamps brands ranked

Ranked by overall AI Visibility Score (smoothed geometric mean of LBA, Authority, and TOM with an LBA-based floor on Authority and TOM, see methodology). Click any brand for the full report.

# Brand LBA Authority TOM Overall
1
Springboard
springboard.com
 78
43
90
67
2
General Assembly
generalassemb.ly
 75
36
64
56
3
Fullstack Academy
fullstackacademy.com
 74
26
43
44
4
Flatiron School
flatironschool.com
 74
13
48
37
5
App Academy
appacademy.io
 68
13
39
34
6
Hack Reactor
hackreactor.com
 76
15
30
33
7
CareerFoundry
careerfoundry.com
 61
6
29
24
8
GitHub
github.com
 100
10
10
24
9
Thinkful
thinkful.com
 70
7
22
24
10
BrainStation
brainstation.io
 61
6
27
23
11
Le Wagon
lewagon.com
 82
8
15
23
12
A Cloud Guru
acloudguru.com
 77
8
14
22
13
Codesmith
codesmith.io
 77
8
13
22
14
DataCamp
datacamp.com
 78
8
13
22
15
Udacity
udacity.com
 84
8
13
22
16
DeepLearning.AI
deeplearning.ai
 82
8
11
21
17
KodeKloud
kodekloud.com
 78
8
12
21
18
NYC Data Science Academy
nycdatascience.com
 60
6
12
18
19
Coursera
coursera.org
 72
7
7
17
20
Coding Dojo
codingdojo.com
 65
7
7
16
21
edX
edx.org
 65
7
7
16
22
Ironhack
ironhack.com
 66
7
7
16
23
Lighthouse Labs
lighthouselabs.ca
 64
6
6
16
24
Evolve Security Academy
evolvesecurityacademy.com
 36
4
17
15
25
Nucamp
nucamp.co
 53
5
8
15
26
TripleTen
tripleten.com
 60
6
6
15
27
Designlab
designlab.com
 37
4
13
14
28
Devmountain
devmountain.com
 57
6
6
14
29
4Geeks Academy
4geeksacademy.com
 49
5
5
13
30
Metis
thisismetis.com
 27
3
20
13
31
Coder Academy
coderacademy.edu.au
 47
5
5
12
32
Sabio
sabio.la
 42
4
4
11
33
WBS CODING SCHOOL
wbscodingschool.com
 43
4
4
11
34
L
LearningFuze
learningfuze.com
 39
4
4
10
35
S
SecureSet Academy
secureset.com
 37
4
4
10
36
Turing College
turingcollege.com
 37
4
4
10
37
Codeworks
codeworks.me
 35
3
3
9
38
C
Constructor Academy
constructoracademy.com
 26
3
3
7
39
Jigsaw Labs
jigsawlabs.io
 0
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 299 shared Specialized Engineering Bootcamps prompts. The same prompts, same model, same iterations. So differences in scores reflect actual differences in AI visibility, not differences in measurement.

Overall AI Visibility Score
Smoothed geometric mean of LBA, Authority and TOM. Authority and TOM are floored at LBA × 0.1 before the geometric mean (the same floor used in the per-metric cards above, so brand cards and the composite tell the same story). Formula: composite = ((LBA + 5)(Authority + 5)(TOM + 5))^(1/3) - 5. The floor keeps brands the model clearly recognises but doesn't yet recommend from collapsing to zero, while a single genuinely weak metric still pulls the composite down. Full methodology.
Shared industry prompts
For Authority and TOM, all brands in the industry are scored against the same 299 category prompts (e.g. "best SEO tools for agencies"). This makes brand-to-brand comparisons valid - everyone faces identical inputs. LBA prompts are per-brand because they ask brand-specific questions.
Latent Brand Association (LBA)
5 brand probes + 1 control prompt, each run 5 times in recall mode (no web search). LBA = quality × meta × stability × share × recognition × 100. Read the full LBA methodology →
LLM Authority
50 organic category prompts (discovery, comparison, problem and transactional intents), each run once in recall mode and once in retrieval mode. Score = frequency × log-decayed prominence × intent weight, then 50/50 averaged across the two modes. Read the full Authority methodology →
Top of Mind (TOM)
15 high-volume discovery prompts (sourced from Keywords Everywhere search-volume data), each run 5 times in pure recall mode (no web). Score = frequency × (0.5 + 0.5 × log-prominence), volume-weighted. Read the full TOM methodology →