Frequently asked questions, answered plainly.

A five-day, 40-hour program covering twelve modules, taking you from transformer internals to a secure, governed multi-agent application you deploy and keep. Available in Seattle or live online.

Tuition and any active discount code are listed on the LLM bootcamp page. Pricing changes with promotions and cohort, so please check the page for the current figure. The price is the same whether you attend in person or online.

Cohorts run several times a year in Seattle and live online. Upcoming dates are listed in the “Pick a cohort” section of the LLM bootcamp page, so please check there for the current schedule.

Monday to Friday, 9 AM to 5 PM Pacific.

At Data Science Dojo, 5010 148th Ave NE, Suite 200A, Redmond, WA 98052, in the Seattle metropolitan area.

Yes. Online sessions run at the same time, with the same instructors, as the in-person session, and are designed to be highly interactive.

Twelve modules across five stages: foundations, context and retrieval, core agent mechanics, trustworthy AI, and deployment. Topics include tokenization and embeddings, attention and transformer architecture, vector databases, context-aware applications, LangChain, LangGraph, Model Context Protocol, evaluation, observability, fine-tuning, reference architectures, and a multi-agent capstone.

You start from a boilerplate repository that only calls a model and add one layer at a time until it becomes an agent: memory, retrieval, context through MCP, reasoning, then guardrails. The finished application lives in your own GitHub account and is deployed to a dedicated cloud URL you can share.

Live sessions with industry experts, hands-on learning, access to dedicated learner and coding sandboxes, LLM tokens and GPU clusters, industry-spanning datasets, and a verified certificate of completion. Inclusions are itemized in the tuition section of the bootcamp page, which is the place to check for the current list.

You need a very basic level of Python. Preparatory material is provided to help you get started.

Yes. A short introductory course is offered to get you comfortable with Python, and all code is provided in Jupyter Notebooks so you focus on understanding rather than writing code from scratch.

Yes. The bootcamp has been attended by many people from non-technical backgrounds, including business consulting and strategy roles. It is designed to make generative AI concepts accessible regardless of technical expertise.

Recordings of the live sessions are shared with cohort participants, so you can catch up on anything you miss. All key topics and content covered in class are also available in the companion courses as structured lesson clips you can review at your convenience.

Free courses are recordings. This is five days of live instruction with practitioners who build these systems in production, and you can interrupt them. It also includes sandbox access, LLM tokens, GPU clusters, and a working multi-agent application you build and keep.

The bootcamp is taught by practitioners who build and run these systems in production at their own companies, alongside guest speakers from across the industry. The guest lineup varies by cohort depending on availability, so please check the instructors section of the bootcamp page for who is confirmed for the cohort you are considering.

The LLM bootcamp takes you from transformer internals through RAG and fine-tuning to your first agent. The Agentic AI bootcamp assumes that foundation and goes deep on multi-agent orchestration. Start with the LLM bootcamp if you are new to building on LLMs, and with the Agentic AI bootcamp if you already have a RAG application in production.

A ten-week, 30-hour online program that takes you from reasoning models to a production-ready multi-agent application you build and keep.

Tuition and any active discount code are listed on the Agentic AI bootcamp page. Pricing changes with promotions and cohort, so please check the page for the current figure.

Cohorts run several times a year, live online. Upcoming dates are listed in the “Pick a cohort” section of the Agentic AI bootcamp page, so please check there for the current schedule.

Three hours every Tuesday from 9 AM to 12 PM PST, for ten weeks.

No. The Agentic AI bootcamp is live online only.

Yes, live and designed to be highly interactive.

Ten modules: introduction to agentic AI, transformers and attention mechanism, mastering LangChain, vector databases and agentic RAG, context engineering, agentic design patterns, agentic AI protocols, Model Context Protocol, evaluation of agents, and a multi-agent capstone project.

Four options: conversational workflow orchestration, knowledge-enhanced agent, document-aware action agent, and orchestrated collaboration using MCP. Comprehensive datasets, step-by-step implementation guides, and ready-to-use code templates in the Data Science Dojo sandbox are provided.

Live sessions with industry experts, access to dedicated learner sandboxes, exclusive access to the Agentic AI coding labs, access to companion course content for review at your convenience, and a verified certificate upon completion. Inclusions are itemized in the tuition section of the bootcamp page, which is the place to check for the current list.

No. Cloud subscriptions are not included, so participants use their own accounts.

You need a very basic level of Python. Preparatory material is provided covering LLM fundamentals: LLM architectures including foundation models, prompts, embeddings and fine-tuning; challenges and risks such as prompt brittleness, context limits, security and cost; and transformers and attention including self-attention, multi-head attention and tokenization.

About one week before the bootcamp starts. You will get an email with access details and instructions closer to the start date.

Both technical and non-technical professionals, including data and AI professionals, engineers and developers, and product leaders and technical founders. It includes high-level modules on AI fundamentals, prompt engineering, and strategic deployment alongside deep technical components for developers.

Job placement is not a specific focus. Networking with partners, attendees, and the alumni network is actively promoted, and the team is happy to assist with introductions once you register if you are looking to connect with professionals in your field.

The conference runs annually as part of the Future of Data and AI series. Dates and the full programme are announced on the conference page, so please check there for the current edition.

Panels and tutorials are virtual and free. The hands-on workshops are optional paid sessions you can add after registering.

Fully virtual, so you can join from anywhere. Daily hours are confirmed with each edition’s programme on the conference page.

The conference runs across several days in three formats: panels, tutorials, and hands-on workshops. The day-by-day breakdown is published on the conference page with each edition, so please check there for the current agenda.

After registering you receive your Zoom link by email. A free Zoom account is all you need, and you should sign up with the same email address you registered with.

Yes. Every session is recorded and available to watch at your convenience after the event.

Live instructor-led training, personalized Q&A with the expert, recordings and slides to review later, free bonus courses, and discounts on future bootcamps.

Yes. A complete workshop bundle gives full access to every workshop plus recordings and slides. Bundle contents and pricing are on the academy, so please check there for what is currently included.

It draws tens of thousands of attendees from across the world. Current attendance and reach figures are published on the conference page.

Registering gets you an invite to the exclusive LinkedIn group. The Discord community also connects you with speakers and attendees year-round.

Yes. Free webinars run regularly, alongside virtual workshops and occasional in-person workshops. Upcoming and on-demand sessions are listed on the events page, so please check there for what is scheduled.

Submit an application through the Become a speaker page describing your expertise, proposed topic, and the audience you want to reach. The team responds within five business days.

Yes. Apply through the Become a presenter page to host a webinar, a hands-on tutorial, or a workshop. Data Science Dojo handles the marketing and logistics so you can focus on the content.

A Discord community, a discussion forum at discuss.datasciencedojo.com, a newsletter, a podcast, a tutorials library of past session recordings, and regional Meetup groups.

We do not accept guest posts. All content on the Data Science Dojo blog is produced in-house by our own team and instructors, and we are not currently taking external contributions or pitches. If you would like to share your expertise with our community, speaking at an event or presenting a webinar is the best route.

No. We do not publish sponsored articles, paid placements, or promotional content on the blog.

No. We do not take requests for link insertions into published articles.

No. We do not participate in link exchanges, reciprocal linking arrangements, or backlink swaps.

Not without written permission. Our blog content is copyrighted. If you would like to request permission for republication or translation, contact us before using any of it.

Yes. You are welcome to quote a short excerpt or cite our work with clear attribution to Data Science Dojo and a link back to the original article.

Through speaking at our events, presenting a webinar, or a formal partnership.

Go to the programme page, choose your cohort in the “Reserve your spot” or “Pick a cohort” section, and follow the registration link for your chosen format.

Discount codes run periodically and are displayed directly on the programme page when active. Enter the code at checkout. Please check the programme page for any code currently available, since these change with promotions.

Your registration fee is refunded in full if you notify Data Science Dojo at least five business days before the training starts. Refunds cannot be processed if you have already transferred to a different cohort after registering. Once you have been added to the learning platform and accessed the course materials, a refund is not possible, since digital content access counts as programme participation. The current policy is published in the FAQ section of each programme page.

Transfers are allowed once with no penalty. Transfers requested after the first incur a processing fee. The current fee is listed in the FAQ section of each programme page.

Yes. Tuition benefits are accepted. Many employers and organizations offer tuition assistance or professional development budgets that can be applied to these programmes, which may mean you attend free. Fill out the contact form or speak to an advisor to check eligibility.

Yes. Corporate cohorts, private training, and volume pricing are available for teams of five or more. Team pricing is not published, so it is quoted on request. Fill out the form on the corporate training page or speak to an advisor and the team will put a quote together.

No. For the LLM bootcamp the tuition is the same in both formats.

Yes. Book a one-on-one call with a bootcamp advisor through the scheduling link on any programme page. Advisors can walk you through curriculum, format, pricing, and programme fit.

Register free through the registration section of the conference page. You will receive your Zoom link by email, along with lineup updates as the programme is announced.

Visit the course page on the academy and click Enroll or Start Learning Path. You create an account, or sign in if you already have one, and get immediate access to your course materials upon purchase.

Yes. Several learning paths on the academy are entirely free. The current free paths are listed in the academy learning catalogue, so please check there for what is available right now.

Yes. Free individual courses are marked as free in the academy learning catalogue. Please browse the catalogue for the current selection.

The tutorials library, the blog, the podcast, the newsletter, the discussion forum, the Discord community, and our regular webinars. Conference panels and tutorials are free to attend as well.

Certificates of completion are unlocked when you complete all courses in a learning path or bootcamp on the academy. The certificate can be shared on LinkedIn or added to your professional portfolio.

Free courses are recorded material. Paid bootcamps add live instruction from practitioners you can question in real time, plus sandbox access, LLM tokens and GPU clusters, datasets, and a working application you build and keep.

Possibly. The LLM and Agentic AI bootcamps are designed for professionals who already understand the basics of LLMs. Beginners may want to start with a foundational course or workshop first, and the learning catalogue has options for all skill levels.

Pricing varies by programme and is listed on each course page in the academy. Please check the academy for current webinar and workshop pricing. All programmes include course materials, hands-on labs, and a certificate of completion.

Yes. All courses on the academy are delivered remotely and can be taken at your own pace, so you can fit them around a full-time job or study full-time.

On the Data Science Dojo academy at academy.datasciencedojo.com. Sign in with the account created at registration or purchase.

Once you are registered for a programme you receive a series of emails. One of them contains the steps to create your learning portal account and access the programme content.

Hands-on coding environments available directly through the academy. They let you practice and experiment with real tools and code without setting up your own environment.

Sandbox access is included with the LLM and Agentic AI bootcamps for a set period after the programme. The current access term is listed in the tuition section of each bootcamp page.

Yes. All academy courses are delivered remotely and can be taken at your own pace.

There is a dedicated Discord community where you can get help from instructors and connect with fellow students. The academy also has its own contact page.

By email at [email protected], by phone at +1 (877) 360-3442, or through the contact form.

Machine learning demos are published under the consulting section of the website, and recordings of past webinars and workshops are on the tutorials page.

Open roles are listed on the careers page and change as positions open and close. Please check the careers page for what is currently available.

Through the apply page linked from careers, or directly from an individual job listing.

Make a positive impact, celebrate diversity, enable growth, pursue excellence, and bias for action.

Benefits span health coverage, wellbeing support, learning-based increments, allowances, paid time off, bonuses, and team events. The full current list is published on the careers benefits page.

There is a community job board listing data and AI roles, and a hiring partnerships programme for organizations looking to recruit from the alumni network.

The careers page directs all applications through the apply form. Submit there and note the area you are interested in.

A six-month internship programme combining instructor-led training in data science, analytics and generative AI with real-world project experience. It includes the LLM bootcamp and Data science bootcamp curriculum alongside the internship.

Yes. It is a full-time commitment of approximately 40 hours per week. There is no part-time option.

Primarily remote. An in-person office option is available for those in the Redmond, WA area.

Enrollment is rolling with flexible start dates. There are no fixed cohort schedules.

Financing options include upfront payment, loan programmes, and income share agreements for eligible U.S. citizens with a valid SSN. Current programme cost and financing terms are confirmed by the team, so please submit the enquiry form on the practicum page or speak to an advisor.

Six steps: submit an application form, succeed in a competitive selection interview, begin the six-month full-time internship embedded with the Data Science Dojo team, complete the LLM and Data Science bootcamp curriculum concurrently, receive interview preparation, mentoring and portfolio development, and enter the job market with real-world experience.

Participants are encouraged to focus on a single track initially. You may eventually work across multiple tracks, but starting with one is strongly recommended. The available tracks span analytics translator, consumer understanding, marketing analytics, sales analytics, web analytics, social media analytics, customer feedback analytics, email campaigns analytics, advertising campaigns analytics, and ETL and log mining.

Not just yet. The bootcamp is currently discontinued in its old form while we rebuild it as a self-paced programme, and we expect to have that version available soon. This has been our longest-running bootcamp, with more than ten years of learners behind it, so we want to take the time to get the new format right. Keep an eye on the bootcamp page for the announcement, and in the meantime an advisor would be glad to help you find something that fits what you are looking for.

Self-paced and fully online, so you can work through it around your own schedule instead of committing to fixed class times. It will not be offered in person.

Around 40 hours of material in total. If you went at it full time that is roughly eight hours a day across a week, but the whole point of the self-paced format is that you can spread it out over whatever timeline works for you.

We have not announced pricing for the self-paced version yet. It will go up on the bootcamp page as soon as it is confirmed. If you would like to talk through your options in the meantime, our advisors are happy to help.

Both, and you can work in whichever you prefer. We are technology-neutral and vendor-agnostic, so code samples are shared in both languages.

Sixteen modules taking you from the fundamentals through to production-scale work: getting ready for the bootcamp, exploratory data analysis, storytelling with data, predictive modeling for real world problems, decision tree learning, evaluation of classification models, tuning of model hyperparameters, ensemble methods and random forest, boosting, online experimentation and A/B testing, text analytics fundamentals, unsupervised learning with K-means clustering, linear models for regression, regularization and tuning of linear models, ranking and recommendation systems, and big data engineering with distributed systems. You will find the full module detail on the bootcamp page.

All sorts, which is one of the nicest things about it. Past cohorts have included software engineers, students, product and program managers, physicists, financial analysts, and even medical doctors and veterinarians. If you are curious about data science and want to explore, segment, analyze, and understand your data to make better decisions, you will be in good company.

Data scientist, data engineer, machine learning engineer, data analyst, and business or product analyst.

It is offered as private training, available on demand, in the same way as corporate training. Public cohort availability, if any, would be listed on the programme page. Schedule a call to request the training or get more information.

It is taught with a no-code approach, from a business and product development perspective, to help managers and business leaders understand data science concepts and work more effectively with their data science teams. The Data science bootcamp is highly technical and focuses on practicing each concept taught.

Taught live over five days, three hours per day, conducted remotely, with an additional one to two hours of assignments outside class each day. Cohorts are kept small, with a minimum of three instructors or TAs available and one lecturer leading each module. Office hours are offered between sessions. Curriculum covers digital transformation, building data science products, defining metrics of success, introduction to machine learning, data governance, and modern big data tools. A verified certificate is issued subject to meeting the attendance criteria.

Not at the moment. Like the Data science bootcamp, this programme is being rebuilt as a self-paced course and we expect to have it available soon. Availability, launch timing, and pricing will all go up on the programme page, so that is the place to watch.

Fifteen hours in total, across five modules. That works out to about three hours a day over five days if you want to move quickly, though the self-paced format lets you go at whatever speed suits you.

None at all. There is optional pre-course material covering the fundamentals of data science and Python programming if you would like a running start.

Five modules: data handling and formats, data wrangling and transformation, data exploration and visualization, data pipelines and data engineering, and machine learning in Python.

Qualification is based on attendance at live lectures. Students who do not meet the attendance threshold still receive a Data Science Dojo certificate of achievement, but it will not be a verified certificate. The current threshold is published on the certificates page.

Yes. You can join another cohort during a lecture you missed.

At the scheduled end of your training programme, you receive an email with your certificate included.

Each certificate has its own unique URL which does not expire. There are no additional fees associated with the verified certificate. If your certificate is lost, email [email protected] to request recovery.