Full Stack Deep Learning
Full Stack Deep Learning is a private educational initiative founded in 2018 that offers free online courses and in-person bootcamps teaching ML engineers how to build and deploy production deep learning systems, including a dedicated LLM Bootcamp launched in 2023.
- Company typePrivate
- Founded2018
- HeadquartersSan Francisco, United States
- Headcount1–10
- GTM typeB2B and B2C
- OfferingServices
What Full Stack Deep Learning does
Full Stack Deep Learning is a private educational initiative founded in 2018, headquartered in San Francisco, that produces open course content and in-person bootcamps teaching practitioners how to build and deploy production-grade deep learning systems. Its core product is the FSDL Deep Learning Course, a free, multi-module curriculum covering the full ML lifecycle — problem formulation, data management, infrastructure and tooling, experiment management, troubleshooting, testing, deployment, monitoring, continual learning, ML team management, and ethics — delivered through video lectures, a structured lab series, and a capstone project. A second core offering, the LLM Bootcamp launched in 2023, focuses specifically on building applications powered by large language models, including prompt engineering, LLMOps, augmented language models, and UX for language interfaces.
The business operates a hybrid monetization model. The flagship online course is offered free of charge, functioning as a top-of-funnel community and brand-building asset distributed globally via the company website, YouTube, GitHub, and a Gitter community. Paid monetization is concentrated in two streams: in-person bootcamps (the August 2018 UC Berkeley bootcamp was priced at $2,450 per attendee with a 150-attendee cap) and quote-based corporate training and certification programs for enterprise ML teams. The curriculum has been adopted as an official course at UC Berkeley (Spring 2021) and the University of Washington Professional Master's Program (Spring 2020), and the 2023 LLM Bootcamp is delivered in partnership with the Scale By the Bay conference.
The instructor and contributor roster is a defining feature of the offering: Pieter Abbeel (UC Berkeley/Covariant.AI), Sergey Karayev (Gradescope), and Josh Tobin (OpenAI) anchor the course, with guest lectures from Andrej Karpathy (Tesla), Richard Socher (Salesforce), Raquel Urtasun (Uber ATG), and other senior practitioners. No venture funding, headcount, or revenue figures have been disclosed, and the organization appears to operate as an independent educational project rather than a scaled enterprise.
Full Stack Deep Learning firmographics
Firmographics- Name
- Full Stack Deep Learning
- Legal name
- Full Stack Deep Learning
- Website
- https://fullstackdeeplearning.com
- Company type
- Private
- Founded year
- 2018
- Operating status
- Operating
- Headcount range
- 1–10 employees
- Short description
- Full Stack Deep Learning is a private educational initiative founded in 2018 that offers free online courses and in-person bootcamps teaching ML engineers how to build and deploy production deep learning systems, including a dedicated LLM Bootcamp launched in 2023.
- Ownership category
- akta.pro rank
Full Stack Deep Learning industry classification
Industry- Product category
- AI/ML Education and Training
- NAICS
- Computer Training (61142), Computer Training (611420), Business Schools and Computer and Management Training (6114)
- SIC
- Services-Educational Services (8200)
- akta.pro primary industry
- AI/ML Learning Platforms for Students (EDAFANAE)
- akta.pro secondary industries
- Technical Bootcamps & Accelerated Reskilling (Full-time/Part-time) (BPAEANAE), Core Digital Curriculum & Courseware (Full Programs & Units) (EDAFACAA)
Keywords
Where Full Stack Deep Learning is headquartered
LocationHeadquarters
- HQ city
- San Francisco
- HQ country
- United States
- HQ region
- North America
Offices2 records
Markets served
Full Stack Deep Learning business model
Business model- GTM type
- B2B and B2C
- Offering type
- Services
- Cost components
- Personnel, Technology or R&D, Operations, Marketing or Sales
Revenue model
- Free Online Course Content: The core deep learning course and LLM Bootcamp are offered for free online. The company provides free access to lectures, labs, and educational materials, likely monetized through brand building, community growth, and enterprise pipeline development.
- In-Person Bootcamp Registration: Three-day intensive bootcamps at university campuses. The August 2018 bootcamp was priced at $2450 with student discounts available. At most 150 people admitted per bootcamp.
- Corporate Training and Certification: Enterprise organizations can arrange group training sessions and certification exams for their ML teams. Contact via [email protected]. Certification exam aimed at deep learning engineer technical interviews.
Pricing tiers
| Model | Billing | Price |
|---|---|---|
| Freemium | Monthly | Free online courses for individual learners |
| One time/ perpetual license | Pay-as-you-go | Three-day in-person bootcamp (2018 pricing) |
| Other | Multi-year contract | Corporate training and certification |
Go-to-market motion3 records
Distribution channels4 records
Marketing channels6 records
Full Stack Deep Learning product offering
Product offeringCore offering
Full Stack Deep Learning provides educational courses, bootcamps, and certification programs that teach practitioners the complete lifecycle of building production-grade AI and deep learning systems. Core offerings include a free online Deep Learning Course (FSDL), an in-person LLM Bootcamp covering large language model applications, corporate training for enterprise ML teams, and a certification exam for deep learning engineer roles.
Product overview
Full Stack Deep Learning is an educational platform offering free and paid learning resources for AI practitioners. The core offerings include the Deep Learning Course (FSDL), a comprehensive free course covering the full lifecycle of production ML systems, and the LLM Bootcamp, an in-person course focused on Large Language Model applications. Additional offerings include a Blog for ongoing education, Cloud GPUs resources, and paid Corporate Training and Certification programs for organizations and job-seeking professionals. The platform has delivered courses from 2018-present, including offerings at UC Berkeley and University of Washington.
Differentiator
Problem solved
Functional benefit
Brands
- LLM Bootcamp: Large Language Models Bootcamp covering prompt engineering, LLMOps, augmented language models, and UX for Language User Interfaces.
- Deep Learning Course
- FSDL
Products and services
- Deep Learning Course (FSDL) A comprehensive free course covering the full-stack production deep learning lifecycle, from problem formulation and data management to model training, deployment, monitoring, and ML team building. Includes video lectures, hands-on labs, and a capstone project (text recognizer). Targeted at ML engineers with at least 1 year of Python experience and prior deep learning exposure.
- LLM Bootcamp An in-person course focused on building applications powered by Large Language Models, covering prompt engineering, LLMOps, augmented language models, UX design for language user interfaces, and agents. Offered through partnership with Scale By the Bay conference.
- Corporate Training Group training sessions for organizations looking to upskill their engineering teams on full-stack production deep learning practices and ML production workflows. Arranged on a quote-based basis via [email protected].
- Certification Exam An optional certification exam covering course prerequisites and full-stack deep learning content, designed to assess candidates for deep learning engineer technical interviews and demonstrate requisite knowledge for ML engineering positions.
- In-Person Bootcamp Three-day intensive in-person bootcamp at UC Berkeley covering computer vision and NLP systems deployment with hands-on labs. Application-based admission with rolling review process. Targeted at ML practitioners seeking immersive production ML training.
Companies that use Full Stack Deep Learning
Customer profileNamed customers2 records
Segments3 records
Ideal customer profiles2 records
Full Stack Deep Learning technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- No
- API docs
- API detail
Core technology
AI maturity
App detail
Feature4 records
Full Stack Deep Learning partnerships and signals
Strategic signalPartnerships
Three partnerships are on record, tiered minor and core.
- Scale By the BayminorPartnership for the LLM Bootcamp launch. Scale By the Bay serves as the hosting platform for the in-person LLM workshop course offering.
- UC BerkeleycoreFull Stack Deep Learning was taught as an official UC Berkeley course in Spring 2021. The course is delivered as part of the university's curriculum, providing academic credibility and access to Berkeley students.
- University of WashingtoncoreThe course was taught as a University of Washington Computer Science Professional Master's Program course in Spring 2020, expanding reach to graduate-level students in the Pacific Northwest.
Scale indicators3 records
Recent moves6 records
Expansion highlights5 records
Full Stack Deep Learning competitors and assessment
Company assessmentEmerging players
- Hugging Face: Hugging Face runs the 'Hugging Face NLP Course' and a broader 'Education Hub' for transformer and LLM practitioners. It is an emerging peer because it provides free AI/NLP education overlapping FSDL's LLM Bootcamp audience and content.
- Weights & Biases: Weights & Biases is an MLOps tooling company that runs the 'Fully Connected' education/community series and training content for ML practitioners. It is an emerging peer because it trains the same ML engineer audience with content adjacent to MLOps, a domain FSDL explicitly covers.
- MLOps Community: The MLOps Community is a community-led education and events organization focused on productionizing machine learning. It is an emerging peer because it runs community content and events for the same production ML practitioner audience FSDL serves.
- Made With ML: Made With ML (by Goku Mohandas) delivers free and paid MLOps courses focused on building and deploying production ML systems. It is an emerging peer because its curriculum directly overlaps FSDL's 'full-stack production ML' positioning.
Direct peers
- Udacity: Udacity runs paid 'Nanodegree' programs in AI, Machine Learning, and Deep Learning, combining self-paced content with project-based learning. It is a direct peer because it monetizes career-focused AI education through cohort and self-paced formats targeting the same engineer and career-changer segments.
- DeepLearning.AI: Founded by Andrew Ng, DeepLearning.AI offers AI/machine learning courses, specializations, and the Deep Learning Specialization on Coursera. It is a direct peer because both companies target practitioners with self-paced and cohort-based AI education, with significant content overlap on deep learning fundamentals and production ML.
- fast.ai: fast.ai offers free, practitioner-focused deep learning courses taught by Jeremy Howard (who is also a FSDL guest lecturer). It is a direct peer because both deliver free online AI courses to the same ML practitioner audience with similar open educational content strategies.
- Springboard: Springboard offers mentor-led career-focused bootcamps in data science, AI, and machine learning engineering. It is a direct peer because it monetizes online + cohort-based AI/ML education for career changers, the same secondary persona FSDL targets.
Broad incumbents
- DataCamp: DataCamp is an incumbent online learning platform for data science and AI, offering self-paced courses in Python, ML, and deep learning. It is a broad incumbent peer because it serves overlapping practitioner learners with subscription-based AI/ML education.
- Coursera: Coursera is a broad incumbent MOOC platform hosting AI/ML specializations from universities and companies including DeepLearning.AI and Stanford. It is a peer because it is a major distribution channel for AI education and a competing destination for self-paced learners.
Market position
Strengths4 records
Weaknesses4 records
Competitive moat4 records
Key risks7 records
Key highlights7 records
Customer concentration
Full Stack Deep Learning social profiles
Digital presenceFull Stack Deep Learning financial estimates
Financial estimateRevenue estimate
Valuation estimate
Full Stack Deep Learning leadership team
Management profileNumber of profiles
Profiles3 records
Full Stack Deep Learning funding detail
Funding detailFunding overview
Funding rounds
Investors
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
Full Stack Deep Learning M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about Full Stack Deep Learning
What does Full Stack Deep Learning do?
Full Stack Deep Learning provides educational courses, bootcamps, and certification programs that teach practitioners the complete lifecycle of building production-grade AI and deep learning systems. Core offerings include a free online Deep Learning Course (FSDL), an in-person LLM Bootcamp covering large language model applications, corporate training for enterprise ML teams, and a certification exam for deep learning engineer roles.
Is Full Stack Deep Learning a public or private company?
Full Stack Deep Learning is a private company. It is classified as unknown and is currently operating.
When was Full Stack Deep Learning founded?
Full Stack Deep Learning was founded in 2018. It employs 1 to 10 people.
Where is Full Stack Deep Learning based?
Full Stack Deep Learning is headquartered in San Francisco, United States, in the North America region.
How does Full Stack Deep Learning make money?
Three revenue lines are on record. Free Online Course Content is the primary driver. The others are in-Person Bootcamp Registration and corporate Training and Certification.
Who are Full Stack Deep Learning's main competitors?
Emerging players on record are Hugging Face, Weights & Biases, MLOps Community and Made With ML. Direct peers are Udacity, DeepLearning.AI, fast.ai and Springboard. Broad incumbents are DataCamp and Coursera.
Does Full Stack Deep Learning have an API?
No public API is recorded for Full Stack Deep Learning.
What industry is Full Stack Deep Learning in?
Full Stack Deep Learning's product category is AI/ML Education and Training. Its primary akta.pro industry code is EDAFANAE, AI/ML Learning Platforms for Students, with a secondary code of BPAEANAE, Technical Bootcamps & Accelerated Reskilling (Full-time/Part-time). Its NAICS code is 61142 and its SIC code is 8200.