Basic Python helps — loops, functions, lists, dicts. If you have never written code before, start with our Programming & CS Foundations course. It covers Python from zero. Most courses open with free phases, so you can try it before paying.
High school math is fine. Phase 0 covers the linear algebra, calculus, and probability you actually need for ML — not a full university course. If you remember what a derivative is, you are good.
No. Labs run on a modern laptop or in the browser. Deep learning labs use small CPU-friendly models. LLM labs use API-based models (OpenAI, Anthropic). Local LLM deployment is covered but optional.
Depends on your background and how much time you put in. Individual courses range from 20 to 80 hours. The full AI & ML Engineering track is 200–400 hours. Most people working full-time finish in 6–12 months. There is no time limit — you move at your own pace.
The opening phases of 24 of our 30 live courses, plus the first lesson of every phase in every course. Daily coding challenges, the tools directory, and progress tracking are included. No credit card, no expiration.
All phases of every course, the AI mentor, project submission and review, the full Defend Your Work scenario library with saved practice reports, portfolio builder, certifications, and referral system. $29/month or $279/year. Cancel anytime.
You get more content and more flexibility for about 10% of the cost. The AI mentor is available 24/7 instead of during scheduled office hours. The trade-off: no peer cohort and no deadlines. If you need external pressure to stay motivated, a bootcamp might work better for you. If you are self-disciplined, this is the better deal.
Yes. You keep access until the end of your billing period. No cancellation fees, no phone call required.
Yes — 14-day money-back guarantee on your first Pro payment. Email support@deventureacademy.com within 14 days and we will refund you, no questions. After that, subscriptions are non-refundable but you can cancel anytime to stop future charges.
Each lesson covers a concept, walks through code, then drops you into a hands-on lab where you build something real. No passive video lectures. The labs are the point — you learn by doing, not by watching someone else do it.
No. Lessons are text-based with interactive code blocks, diagrams, and inline checks. Text is searchable and skimmable. Video goes stale fast in AI engineering — text is easier to keep current.
Python, NumPy, pandas, scikit-learn, PyTorch, OpenAI and Anthropic APIs, LangChain, LlamaIndex, LangGraph, Qdrant, ChromaDB, RAGAS, DeepEval, FastAPI, Docker, AWS, SQL, and MCP. We update the stack as the industry shifts.
We update regularly. The curriculum uses 2026 patterns — agents, MCP, modern RAG with reranking, eval suites in CI, vLLM serving. When a tool becomes standard, we add it. When something becomes obsolete, we remove it.
ML Engineer, AI Engineer, LLM Engineer, MLOps Engineer, Applied ML Engineer, AI Product Engineer. The career phase covers resume prep, LinkedIn optimization, system design interviews, STAR stories, and a structured job search process.
No, and you should be skeptical of anyone who does. What we provide: real portfolio projects with evaluation reports, practice defending AI-assisted decisions, and a resume builder tied to the work you finish. Your results depend on your effort, your background, and the job market.
Yes, Pro subscribers get a certificate of completion. But being honest — certificates do not get people hired. Portfolio projects do. The certificate is a nice-to-have, not the point.
A realistic practice format where AI use is allowed. You make a technical decision, cite evidence, explain how you would verify it, respond to new information, and revise the answer you are willing to own. Reports are coaching feedback, not a hiring credential.
It is powered by Claude and has context of your progress — which lessons you have completed, what you are working on, where you are stuck. It is available 24/7 for Pro subscribers. For labs, it uses Socratic questioning to guide you toward the answer instead of handing it over.
It will help you debug, explain concepts, and suggest approaches. It will not give you the answer to a lab. The whole point is learning by doing.
Create a free account — the opening phases of 24 of 30 courses are free, no credit card. Or see Pro pricing.
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