TripleTen is a professional education platform with seven programs in 2026, grouped into two tracks by your starting point:
- Advanced programs for tech professionals: AI Systems Engineering, AI & Machine Learning.
- Tech programs for complete beginners: AI Software Engineering, Cybersecurity, Quality Assurance, Data Analytics, AI Automation.
Below, you'll find an in-depth look at all seven programs: who they're for, the full tech stack from the syllabi, every project, the roles you can target with typical salaries, and the skills that carry over from your current job.
TripleTen programs at a glance
TripleTen offers online part-time programs in two tracks for people with different backgrounds. Advanced programs for tech professionals help developers with 2+ years of production experience move into AI systems and ML roles in about 20–22 weeks. Tech programs for complete beginners help career switchers move into software engineering, cybersecurity, quality assurance, data analytics, or AI automation in 4–7 months.
Every program has a 14-day full-refund window.
How TripleTen programs work
Every TripleTen program combines project-based learning, reviews by working practitioners, and career support, but each track starts from a different point.
- Admission. Each track starts with a step that fits its audience.
- Programs for tech professionals start with a 3-minute skills audit and a call that turns the results into a personal study plan.
- Programs for complete beginners have no admission tests or extra requirements, so you start from the first lesson whatever your background.
- Projects. You learn through projects: 5 in the advanced programs and 4–13 in the beginner programs. Each one goes into your portfolio.
- Reviews. Practitioners review your projects. In the advanced programs, working engineers review all five projects live.
- Career support. Advanced programs start career coaching during the program and continue for up to 3 months after it. Beginner programs include a 6-week Career Sprint after graduation and an Active Job Search Period of up to 10 months.
- Updates. The curriculum is reviewed every two months against job posting requirements.
Advanced programs for tech professionals
TripleTen's two programs for tech professionals take engineers who already ship to production and teach them to build AI systems themselves. Neither program teaches coding from scratch, and entry starts with a 3-minute skills audit.
- Flexible pace. Plan for 10–15 hours a week: about 10 on projects, more if you take all the theory. At 10 hours a week, AI Systems Engineering takes 22 weeks and AI & Machine Learning 20 weeks on projects alone, or about 33 weeks with all theory. Theory is optional, so you skip what you already know.
- Projects built like real work. In AI Systems Engineering, all five projects run on one platform, Coldline. In AI & Machine Learning, you move from a model on live transit data to AI features in an existing healthcare product.
- Code in a production-style repository. You work in existing codebases with CI checks, and your instructor reads your repository before each review.
- Live project reviews. Each project gets a 30-minute check-in at about 70% completion and a 60-minute live review with a working engineer. If a review doesn't pass, you get written feedback and rebook.
- Weekly 1:1s. A 30-minute weekly session with an instructor, group office hours on evenings and weekends, and written feedback on every project.
- Included tools. A Claude Pro subscription on request and a model API allowance for the agent projects.
- Career support during the program. A career coach joins after the first project. You get a target role and transition plan, a résumé and LinkedIn rewritten for that role, up to 10 live mock interviews (screening, technical, recruiter, and behavioral), unlimited AI mock interview practice, and debriefs after real interviews. Support lasts up to 12 months: about 4 months of active job search, then up to 8 months of transition support.
- Lifelong access to the curriculum.
Instructors are working engineers whose profiles you can check, including Mohamed Cherif (20+ years at AMD, Microsoft, Amazon, and Skype), Ahmed Abouzeid (15+ years in distributed systems, platform infrastructure, and generative AI at Amazon, Morgan Stanley, and Ericsson), Tejashree Khot (8+ years in backend and distributed systems at Amazon, where she led LLM-powered API orchestration for Alexa+), and Gagandeep Singh (10+ years shipping production ML at Capital One, Walmart, and Chime). The programs’ authors are Dr. Gönen Eren (AI Systems Engineering; 20+ years of fault-tolerant distributed systems on AWS and Azure) and Amish Suchak (AI & Machine Learning; 10+ years as a data scientist and ML engineer).
AI Systems Engineering
AI Systems Engineering is an advanced program for engineers who run production systems and want to build AI on top of them. You join the platform team at a fictional company, TripleTen Medical, and take its cold-chain logistics platform, Coldline, through diagnostics, retrieval and service architecture, operations, security, and finally an agentic AI workflow deployed to AWS and defended at Demo Day. It includes about 220 hours of project work plus about 110 hours of optional theory, takes 22 weeks at 10 hours a week (33 weeks with all theory), and costs $12,600 upfront.
Who it's for
The program fits backend, full-stack, frontend, and mobile engineers, DevOps engineers, SREs, and cloud and platform engineers with 2+ years of hands-on production experience. Two years is a guide, not a hard cutoff: junior engineers, analysts, and CS graduates with a strong technical base also fit. If AI work in your company goes to another team or a vendor while you get the tickets, this program closes that gap: cloud and DevOps, service architecture, observability, security and compliance, scaling, and production LLM systems.
Projects and the tech stack
Projects 1–4 run on your laptop with a LocalStack license included; for the capstone, you connect the release to your own AWS account.
The sample project, Autonomous Incident Defense, is on TripleTen's GitHub.
Roles and salaries
Transition skills
Backend and infrastructure engineers already bring the foundation AI systems run on: services, databases, deployments, and on-call reliability. The program builds on that base and adds what AI system roles add to the job: production LLM integration, retrieval, evaluation pipelines, prompt-injection defense, and cost and latency control. In system-design rounds, you'll walk interviewers through a working system you built and reviewed with senior engineers.
AI & Machine Learning
AI & Machine Learning is an advanced program for engineers and data professionals who want to build, evaluate, and deploy models. You train a model on live transit data, ship it as a production service, fine-tune a clinical LLM, build a support agent, and add AI features to an existing healthcare product, with Claude Code as your engineering assistant. It includes about 200 hours of project work plus about 125 hours of optional theory, takes 20 weeks at 10 hours a week (33 weeks with all theory), and costs $12,600 upfront.
Who it's for
The program fits software, data, ML, DevOps, and QA engineers, analysts, data scientists, and quantitative professionals with 2+ years of shipping production code or working with data. You need working Python from the first project; if you don't code in Python yet, AI Systems Engineering is the better fit. It also fits analysts whose models stay in the notebook and developers who got handed an AI project at work. The gap it closes: classical ML, choosing what to build with AI and what without, LLM applications and agents, and MLOps.
Projects and the tech stack
The sample project, BriefBoard, is on TripleTen's GitHub.
You don't need a GPU or a cloud account: Project 5 trains on AWS GPUs through an included cloud lab.
Roles and salaries
Transition skills
Engineers bring the hard part already: reading an unfamiliar codebase, shipping to production, and debugging under pressure. Data analysts bring data intuition and modeling basics. The program adds the ML and LLM layer on top: model training and evaluation, serving and MLOps, fine-tuning, RAG, agents, and LLM security. The career team treats your existing experience as a qualification, so you move into higher-leverage work without starting over.
Tech programs for complete beginners
TripleTen's five tech programs for complete beginners take career switchers with no tech background into software engineering, cybersecurity, QA, data analytics, or AI automation. Each program runs 4–7 months at 15–20 hours a week, so you can keep your current job while you study.
When we interview our students about how they decided to switch, the same worries come up again and again. A recent TripleTen study puts numbers on them: financial risk (45%), uncertainty about job prospects (44%), and fear of not being technical enough (38%) nearly stopped career changers from moving into tech, and more than half (54%) made the decision without knowing anyone in the industry. Here's how the beginner programs address each of these worries:
- “I'm not technical enough.” The programs start from zero and move in two-week sprints. Each sprint ends with a project reviewed by working professionals, so you get feedback on your work every two weeks and build a portfolio as you go.
- “I don't know if I'll find a job.” After graduation, a 6-week Career Sprint prepares your résumé, LinkedIn profile, and job search strategy, and a career coach then guides your search for up to 10 months.
- “I don't know anyone in tech.” You join the TripleTen Community and at least two live career activities a month, such as workshops and Industry Experience projects, where you meet working professionals and other career switchers.
- “I can't afford to lose the money.” Every program has a 14-day full-refund window, and the beginner programs include a money-back guarantee: get your tuition back if you're not hired within 10 months. Conditions: complete the program, follow the job-search roadmap with your coach, meet the weekly application and networking minimums, and meet eligibility requirements such as US residency, work authorization, and age.
Data Analytics
Data Analytics prepares you for data analyst roles: you clean and analyze data with spreadsheets, SQL, and Python, build dashboards in Power BI, and turn the results into recommendations a manager can act on. It runs 4 months at about 20 hours a week, with the option to extend deadlines by up to 8 weeks in total, and costs $5,950 upfront.
Who it's for
The program is for career switchers with no tech experience. It suits people who already work with numbers, reports, or spreadsheets in finance, retail, admin, or operations roles and want to make data their main job.
What you'll learn and the tech stack
Projects
- NYC Parks inspections: clean a real dataset, define park-condition metrics, and present a KPI report built with pivot tables.
- Company outcomes with SQL: compare company results in a real database and summarize them with simple charts.
- E-commerce analysis with Python: clean an e-commerce dataset and answer business questions with exploratory analysis.
- Customer behavior in Google Colab: query and load data with Python and SQL, profile it, and summarize how customers engage.
- Shopify app ecosystem: a Power BI report with a data model, key metrics, and dashboard pages on what drives app performance.
- Bank customer churn: build and validate models that predict which customers will leave and the factors behind it.
- Executive business review: a Power BI review of retention, cohorts, forecasts, and finances, with a narrative leadership could act on.
- Capstone: an end-to-end analytics project in a domain you choose, with a dashboard and a complete project repository.
Roles and salaries
These figures cover all experience levels. Entry-level analyst roles usually start below them.
Transition skills
If you've built reports, tracked budgets, or answered “why did this number change?” at work, you already have the core of the job: curiosity about data and the ability to explain it to non-technical colleagues. The program adds the technical layer: SQL, Python, Power BI dashboards, statistics, and basic machine learning.
AI Automation
AI Automation prepares you for AI automation specialist roles: you work with LLMs and AI tools, build chatbots and AI agents, automate workflows with Zapier and UiPath, and connect them to business systems through APIs and webhooks. It runs 4 months at 15–20 hours a week and costs $5,950 upfront.
Who it's for
The program is for career switchers with no tech experience. It suits people from operations, admin, customer support, and sales roles who keep seeing repetitive work that could run on its own and want to be the one who automates it.
What you'll learn and the tech stack
Projects
- A business case solved with prompt engineering for an industry-specific challenge.
- An AI-powered chatbot or app for a real-world scenario.
- An AI-driven automation that streamlines a business operation.
- An AI agent that performs a business-specific task.
- An integrated AI solution connected to existing business systems.
- An RPA bot that automates a repetitive business task.
- Capstone: a complete AI solution for a real business challenge, built and presented.
Roles and salaries
These figures cover all experience levels. Entry-level automation roles usually start below them.
Transition skills
Knowing how a business process really runs, where it breaks, and who it affects is the hardest part of automation to teach, and operations and support roles build it every day. The program adds the technical layer: prompt engineering, LLM apps, AI agents, Zapier workflows, API and webhook integrations, and RPA with UiPath.
Quality Assurance
Quality Assurance prepares you for QA Analyst and QA Engineer roles: you test web apps, APIs, and mobile apps in a structured way and automate the repetitive checks with Python and Selenium. It runs 5 months at 15–20 hours a week and costs $4,935 upfront.
Who it's for
The program is designed for career switchers with little or no knowledge of software testing. It suits detail-oriented professionals from service, admin, and operations roles who like finding what's broken and explaining it clearly.
What you'll learn and the tech stack
Projects
- Urban Routes: exploratory testing of a web app, then test design and documentation, then web app testing with DevTools.
- Urban Grocers API: validating and testing an API with Postman.
- Database testing: SQL queries to check data in a relational database.
- Testing an Android app: finding bugs with the Android Studio emulator and logs.
- Python foundations and automated testing with Python and Selenium: your first test scripts and browser automation.
- Final project: testing a mobile app, a web app, and an API, with bug reports for your findings.
Roles and salaries
These figures cover all experience levels. Entry-level QA roles, such as QA analyst or manual tester, usually start below them, and automation skills move you toward the higher end.
Transition skills
QA rewards skills career switchers often bring from service, admin, and operations jobs: attention to detail, following and documenting a process, and explaining a problem so a developer can fix it. The program adds the technical side: how web apps and APIs work, SQL, mobile testing, Python, and test automation.
From the TripleTen alumni community: Michael Allen worked as an indoor air quality manager before TripleTen and is now a QA Specialist at Tamman.
Networking and using the tools and recommendations my tutors and career coach gave me to better market myself. Michael Allen, TripleTen Student
Cybersecurity
Cybersecurity prepares you for security analyst roles: you secure networks, respond to incidents, find and fix vulnerabilities, and investigate attacks in a SIEM. It runs 7 months at 15–20 hours a week, ends with the CompTIA Security+ exam, and costs $9,800 upfront.
Who it's for
The program is built for career switchers, and it suits IT support specialists, system administrators, and professionals from risk, compliance, and operations roles who want to move into security.
What you'll learn and the tech stack
Projects
You complete 13 projects that follow the work of a security team at a managed security service provider. They include analyzing a network for security flaws, building an asset inventory (CMDB) from scan results, assessing a business against the NIST CSF, threat modeling a company, rewriting a ransomware victim's incident response plan, modernizing an outdated network with virtualization and presenting the plan to executives, a vulnerability assessment, a penetration test, remediation, setting up continuous monitoring, triaging alerts in Splunk, and two major incident investigations mapped to MITRE ATT&CK.
Roles and salaries
These figures cover all experience levels. First security roles are usually SOC analyst, IT security, or incident response positions; security engineering and penetration testing typically come with experience.
Transition skills
IT support and admin experience carries over directly: you already know networks, users, and systems. From any background, the program builds on risk thinking, prioritization, and communication, since security analysts explain technical issues to executives and legal teams. The program adds networking security, incident response, vulnerability management, SIEM investigations, and AI security.
From the TripleTen alumni community: Ora Hall worked as a psychometrician before TripleTen and is now a Cybersecurity Specialist at ThreatLocker.
Networking with the company on LinkedIn was definitely the biggest thing that landed me the job. Ora Hall, TripleTen student
AI Software Engineering
AI Software Engineering prepares you for software engineer and full-stack developer roles: you build web apps on the MERN stack (MongoDB, Express, React, Node.js), deploy them to AWS, and work with AI coding assistants on an existing TypeScript codebase. It runs 7 months at 20 hours a week, with the option to extend deadlines by up to 12 weeks in total, and costs $9,800 upfront.
Who it's for
The program is for career switchers from any background. No prior tech experience is required.
What you'll learn and the tech stack
Projects
- Project 1. Flashcard app: a web app built in nine parts, from layout and interactivity to a GitHub repository, a Figma-based responsive layout, form validation, and API requests.
- Project 2. A full-stack MERN app: an Express server with MongoDB, a React interface, authentication and authorization, and deployment to AWS in Docker.
- Project 3. A brownfield TypeScript app with AI assistance: extending an existing full-stack application with secure APIs, forms, testing, and deployment while working with AI coding tools.
- Project 4. Portfolio website: a TypeScript portfolio site that presents your work to employers.
Roles and salaries
These figures cover all experience levels. Junior developer roles usually start below them.
Transition skills
Problem-solving, persistence, and the ability to learn from documentation matter more in this program than a technical background. Teachers bring structured explanation, service workers bring speed under pressure, and admin roles bring organization. The program adds the full stack: frontend, backend, databases, deployment, and working with AI coding assistants.
From the TripleTen alumni community: Anna Eckman worked as a math teacher before TripleTen and is now a Software Engineer II at The Contingent.
How to choose the right TripleTen program
Pick the program that matches the experience you already have and the work you want to do next.
- You run backend, cloud, or platform systems and want to build AI systems on top: AI Systems Engineering.
- You ship code or work with data and want to build, fine-tune, and deploy models and agents: AI & Machine Learning.
- You're new to tech and want to build software: AI Software Engineering.
- You're new to tech or come from IT support and want to protect systems: Cybersecurity.
- You're new to tech and like finding what's broken: Quality Assurance.
- You're new to tech and like working with numbers: Data Analytics.
- You're new to tech and want to automate routine work with AI: AI Automation.
FAQ
Do I need to know how to code?
Not for the programs for complete beginners. AI Systems Engineering requires solid programming in any general-purpose language, and AI & Machine Learning requires working Python.
Is TripleTen accredited?
TripleTen isn't an accredited college and doesn't grant degrees. It's licensed by the Wyoming Department of Education and registered in California as an out-of-state institution. Graduates receive a certificate of completion. Cybersecurity graduates also earn the CompTIA Security+ certification.
Can I study while working full-time?
Yes. All seven programs are online and part-time. Programs for tech professionals take 10–15 hours a week with no fixed class times, and programs for complete beginners take 15–20 hours.
