School of AI

Everything AI

Build a Full-Stack AI Engineer Portfolio in 21 Days

Name

AI Instructor, School of AI

Most people watch AI videos. This shows what it actually takes to build and ship real AI apps—daily.

Stop Watching AI Demos. Start Building.

No projects, no proof. This program forces you to build 21 real systems—not tutorials.

Your AI Skills Mean Nothing Without Projects

You’ll move beyond prompts and actually build UIs, logic, and AI systems from scratch.

Become a Full-Stack AI Engineer, Not a Prompt User

We show you what's possible with AI, then take you there.

Founder | Meta/Amazon/Statsig/Tencent

Statsig

Amazon

Boston Consulting Group (BCG)

Tencent Games

Yuzheng Sun, PhD

Prev. Evangelist @ Statsig (Acq. by OpenAI), AI Director @ Tencent; Meta/Amazon

Applied Scientist | yage.ai

Yan Wang, PhD

Applied Scientist @ Samsara | Olympic Torchbearer | Ex Pinterest/Microsoft | Ex Tech blogger with 100k+ subscribers

Cohort 12

Cohort 13

Is this you?<ul><li>Chatting endlessly with an “AI intern” instead of designing the context with clear principles.</li><li>Blaming “hallucinations” when the real issue is poor orchestration.</li><li>Trying to run an entire project from a single, overloaded chat window.</li><li>Treating AI like witchcraft and prompt spells instead of engineering.</li></ul>AI gets better every day. But when it’s time to ship something serious, you don’t yet have a reliable way to make AI show up for you.The problem isn’t AI. It’s how you’re using it. This course exists for that exact gap.AI is a new computing paradigm. To use it well, you have to:<ul><li>Unlearn old patterns</li><li>Install new mindsets and habits</li><li>Build a meta-learning system that can carry your career for the next 20 years</li></ul>That's hard, and we take it seriously. This course is designed to teach you how to fish. On top of lessons and projects, we built two unique tools:<ol><li><a target="_blank" rel="noopener noreferrer nofollow" href="https://youtu.be/dXjcy6XSN_Y">A build platform</a> that consolidates key APIs and lets you deploy your projects with one command—so you can build fast, not fight boilerplate.</li><li><a target="_blank" rel="noopener noreferrer nofollow" href="https://www.superlinear.academy/c/share-your-projects/">A lifetime community</a> where you can share projects, ask questions, and get unstuck long after the course ends.</li></ol>The end of our course is the beginning of your learning, and we will be with you.

Learn AI for the Next 20 Years, Not the Next 20 Days

Engineer Robust Context to Eliminate Hallucinations

Curate "Sterile" Contexts for Peak AI Performance

Architect Multi-Agent Systems to Conquer Complexity

Define Success Criteria to Transmute from Operator to Manager

Build "White-Box" Evaluation Tools to Visualize Quality

Design Self-Healing Loops for Autonomous Optimization

Software Engineers &amp; Developers Ready to build reliable, scalable AI systems integrated into production workflows.

Technical Product Managers &amp; Strategists Seeking the hands-on knowledge to scope, architect, and guide AI initiatives with confidence.

Data Professionals &amp; Automation Experts Who want to transform proof-of-concept scripts into durable applications that multiply productivity.

By the end of this course, you’ll transition from a software engineer to a confident AI engineer—able to identify the right problems, design

AI Engineer & Consultant for F-500 firms

Qualcomm

Wipro

Sujeet Mishra

AI Engineer | Entrepreneur | AI Consultant & Trainer for Fortune-500

AI/ML | Search | Ex-Microsoft, Yahoo

Apple

Microsoft

Yahoo

Prasenjit Mukherjee

Adjunct Faculty | Quantum ML & Big Data | Ex-Microsoft, Yahoo | IIT Madras

Cohort 1

Cohort 2

For software engineers, moving into AI engineering is not just about learning new tools—it’s a mindset shift.Over the past year, we’ve worked with engineering teams, from Fortune 500 companies to unicorn startups, helping them adopt AI-native and agent-based systems. One pattern shows up repeatedly: engineers don’t struggle because they can’t build, but because AI systems behave very differently from deterministic software.⚙️ Engineers must learn how to design, evaluate, and operate probabilistic systems, reason about failures and trade-offs, and think end-to-end—from use-case identification to production and scale.Many engineers hesitate because they believe AI engineering requires deep ML or statistics expertise. In reality, modern AI engineering is about system design, evaluation, observability, and production readiness—skills engineers already have but need to apply in a new context.🚀 This course provides a practical 6-week roadmap to make that transition by building and extending a real, production-grade agentic system.By the end, you won’t just understand AI systems—you’ll think and operate like an AI engineer.For queries, write to us: ai-education@theseuslab.ai

A 6-week roadmap for software engineers to become production-ready AI engineers

Use LLMs to 10x day-to-day engineering productivity

Design and build agentic systems using LangChain/LangGraph

Build reliable agentic systems by designing for evaluation and observability

Take AI ideas from use-case discovery to production and scale

Apply everything you learn to a real, end-to-end capstone project

Basic understanding of SDLC concepts like databases, APIs, frontend/backend systems, and servers

Familiarity with Software Engineering Fundamentals

Some programming experience, even if not recent—or willingness to spend ~8 hours pre-course to learn Python (we will provide resources)

Prior Programming Exposure (or Willingness to Ramp Up)

Openness to learning, experimenting, and thinking differently

Curiosity and Willingness to Experiment

Software engineers looking to transition into AI engineering roles and build production-grade AI systems

AI engineers and data science professionals who want to get a hands-on experience of building, evaluating and scaling agentic AI applications

Product managers and Tech leaders seeking a practical, system-level view of how production-ready AI applications are designed and shipped

A designer is as good as their portfolio. Level up yours in a day

AI Design Leader | x-Uber/Google/Amazon

Stanford University

Google

Uber

Rupa Chaturvedi

If your portfolio is outdated, stuck as Figma screenshots, or fails to position you accurately, you're losing interviews before they start. Rebuilding feels like a project most designers push off for months.This workshop changes that. In one day, you'll shape your positioning, generate your case studies and visuals with Claude and Google AI Studio, and deploy a live portfolio to Vercel. You'll scope, build, and ship inside a four-hour session.You'll leave with a working portfolio on a live URL and Claude skills to keep building case studies as your career moves. NOTE: This is a handson workshop not a lecture series for passive content consumption. Expect to build and ship your portfolio site.

Designers in a job hunt. You need a polished, modern portfolio that signals credibility fast, not another stale case study PDF.

Designers with Figma case studies. Your work is strong, but the storytelling and format aren't landing. Time to level up.

Designers building AI fluency. You want hands-on vibe coding skills and a real portfolio project to show for it, not another tutorial.

Master the systems to stop micromanaging and transition from a referee to an orchestrator of a self-running team.

Founder at The Strength Hack

Daimler AG

Airbus

Audi

Toll Collect GmbH

Murk Creusen

Founder & Leadership Coach at Strength Hack

Founding Cohort

You cannot fix burnout by working harder. You have a matching problem.AI is making your team's hard technical skills obsolete faster than they can learn them. You cannot fix this "AI anxiety" or burnout by asking them to work harder. You don't have an effort problem; you have a matching problem.Most Engineering Managers spend 70% of their week trapped in the "Mediocrity Loop" - refereeing personality clashes, fixing broken handoffs, and watching their team's shared knowledge collapse as junior roles vanish. You're bleeding runway and morale.This 30-day accelerator gives you the system to break out. Using the Big Five (or CliftonStrengths) assessment, a proven framework, and the Strength Hack AI, you'll map your team's cognitive architecture and engineer the conditions for psychological safety - not just hope for it.In 4 weeks, you will:<ul><li>Stop Generalist Exhaustion: Identify energy leaks and delegate based on Cognitive Fit, not calendar space. </li><li>Engineer Swift Trust: Use the 6-dimension Matching Compass to translate friction into synergy.</li><li>Drive ROI: Transition from a reactive referee to a strategic orchestrator</li></ul>

Engineer Psychological Safety. Stop Refereeing Your Team.

Shortcut the "Storming" Phase to Engineer Swift Trust

Reclaim 70% of Your Week (Plug the Energy Leak)

Turn Personality Clashes into Solvable Data

Restore the "Who Knows What" Architecture Your Team Lost

Walk Away with a "Plug-and-Play" Facilitation Kit

To get ROI from this course, a real-world team (direct reports or agile squads) is recommended to apply the Matching Compass frameworks.

Team Leadership or Management Role

You must take the free Big Five test (or CliftonStrengths) before to map your personal psychological operating system.

Completion of a Baseline Assessment

The Overwhelmed Engineering Manager / Tech LeadYou lead a hybrid or remote team. You want a data-driven system, not another workshop.

The Ambitious Senior / Staff Engineer<blockquote>You're moving to people manager. You want proven frameworks to lead a team without micromanaging.</blockquote>

The People-Conscious CTO / CPO<blockquote>You own culture and delivery for 10–200 people. Your board wants AI readiness. You need L&amp;D that's credible.</blockquote>

Build a Full-Stack AI Engineer Portfolio in 21 Days

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