Few courses currently exist on Agentic AI, and those that do focus on what it is, how it works, use cases, or the theory and set up of the machine learning. But great engineers know that the real challenge is learning how to actually build these systems - as with any software, knowing theory is nice but actually building infrastructure and products is what’s hard.
As a modern college of engineering focused on applied learning, we've built a fully applied Agentic AI course where you'll actually build agents and multi-agent systems in a cohort with other learners. You can apply to be an Alpha Tester of this new course!
Companies don’t just want engineers who understand concepts—they need professionals who can architect and deploy intelligent agents in real-world environments. In fact, Robinhood had a job posting recently for an Agentic AI Engineer and asked for “2+ years of software engineering experience, and Experience building or scaling AI-powered platforms, agent-based systems, data processing and API integration” - and that’s it! Normally we see “5 years of experience with CUDA” or “5 years of experience building Agentic AI systems”, but here, it’s so new that companies can’t ask for such experience, so instead, they want proof and evidence that you’ve worked with Agentic AI systems and are smart enough to figure out how to build what they want.
That’s why Qwasar is launching an Agentic AI course, and we’re looking for alpha testers who want to be at the forefront of this cutting-edge technology. This isn’t just another theory-heavy AI course. It’s 100% project-based, hands-on training that prepares you to build, scale, and deploy AI agents.
This is not an entry-level course!!!
This course is for developers or engineers or data scientists who already work with Python, understand at least the basics of Machine Learning, and are capable of using daily development tools.
You will work with some if not all of the following:
Are you up for the challenge?
Becoming an alpha tester for this program gives you a unique opportunity to:
This program is designed for engineers who want to specialize in Agentic AI and need a practical, portfolio-driven approach to mastering the field.
(Agentic AI Workflow by NVIDIA)
The Qwasar Agentic AI course is fully project-based and focused on building increasingly complex AI agents. You will:
The course is expected to last 3-12 weeks - depending on if you do it full time and how many years of development/engineering experience you have.
Principal and Staff Engineers complete projects 2-10x faster than Junior Engineers, so the variation in duration is normal, and also what we see on the job.
Here's an estimation based on level of experience:
| Level | Full Time | Part-time, 15 hours per week |
| Staff Engineering and above, 8+ years of engineering and development experience | 2-3 weeks | 6 weeks |
| Senior Engineer, 3-5 years of experience | 4-5 weeks | 8-9 weeks |
| Junior Engineer, 1-2 years of experience or significant project-based work | 6-8 weeks | 13-14 weeks |
| Recent college grad, no full-time hands-on development experience | 12 weeks | 20 weeks |
The alpha test Agentic AI course will start on March 25, 2025.
You have 3 options for participating:
We run the following program meetings that you will be expected to attend:
Meetings are Tuesday mornings and Thursday mornings (Pacific time, starting at 9:15am), or Saturday mornings (starting at 9:30am Pacific). Standup runs every morning at 9:15am for full-time, though all students are welcome to attend if they can.
You should expect to commit 40 hours per week for full-time, and 15-20 hours per week for part-time. You will need to put time on your personal schedule to complete projects - i.e. time to code!
We have expectations for our testers, so please review them if you're interested in our course!
To qualify as an alpha tester, you should have:
If you meet these criteria, and you are ready to fully immerse yourself, this course could take your AI skills to the next level.
Until now, most material on Agentic AI has been explanatory, informational, and in many cases architectural with drawings of how things should be set up.
But with any kind of software development, often the hard part is actually building the product or software!
There’s no instruction manual with a step by step guide on how to build a complex multi-agent system with great performance, guardrails, zero-trust IAM, shared memory, and consistent monitoring and evaluation.
Additionally, particularly with cloud-based tools, there are ALWAYS nuances that create blockers that often aren’t in documentation. They can be small things such as “error, containerID is missing” - well the documentation didn’t say to provide the containerID! But it’s things like this that make senior, staff, and principal engineers so valuable - they’ve spent so much time with their respective technologies, languages, tools, libraries and more, that they just know these things and make building go better, faster, and easier.
So how will companies get engineers who are capable of building Agentic AI systems? They hire ones who have already built them. And that’s why we’ve built a course that allows you to do exactly that.
First, review the expectations we have of you as an alpha tester. If it aligns with your expectations, we encourage you to apply.
We are only selecting a limited number of participants for this alpha phase. If you want to be among the first to develop next-gen AI agents and build an industry-ready portfolio, apply today!
Spots are limited! Apply now to become an alpha tester for Qwasar’s Agentic AI course.