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AI Engineer Foundations (Maven cohort)vsMastering LLMs: Evaluation (Hamel Husain & Shreya Shankar)

Side-by-side comparison on level, duration, pricing, instructor, tier. Editor verdict on which course wins for which buyer.

M
Maven

AI Engineer Foundations (Maven cohort)

The most-recommended cohort for engineers transitioning into AI in 2026. The Maven format — small cohort (40-80 students), live weekly sessions, group projects, capstone — produces ~70% completion vs ~5% for self-paced equivalents. Pick the cohort run by the instructor whose published work most closely matches your target stack; instructor variance is the biggest determinant of value. Worth the $1,495 only if you'll commit to the 24 hours of live time and ship the capstone — if you suspect you won't, save the money and self-direct through DeepLearning.AI's free short courses.

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Maven

Mastering LLMs: Evaluation (Hamel Husain & Shreya Shankar)

The cohort that defined the modern AI evaluation playbook. Hamel and Shreya teach you how to build eval sets, run experiments, ship dashboards, and avoid the LLM-as-judge traps that fool most teams. $1,995 for 4 weeks with live sessions and a capstone. Worth every dollar if you're shipping production LLM features — the cost of doing evaluation wrong is bigger than the tuition. Sells out within hours of every run.

Side-by-side

DimensionAI Engineer Foundations (Maven cohort)Mastering LLMs: Evaluation (Hamel Husain & Shreya Shankar)
ProviderMavenMaven
Editorial tierCuratedCurated
LevelIntermediateAdvanced
Formatcohortcohort
Duration4 weeks (~6h/wk live + work)4 weeks (~6-8h/wk live + work)
Pricing$1495 one-time$1995 one-time
InstructorVarious Maven instructors — Practicing AI engineers (cohort-specific)Hamel Husain & Shreya Shankar — Independent AI consultants; ex-Airbnb, GitHub
RatingNo public ratingNo public rating
Topicsai engineering, build ai agentsai evals, ai engineering, build ai agents
Last verified2026-05-232026-05-24

Pros & cons

AI Engineer Foundations (Maven cohort)
Pros
  • +Live cohort = real commitment device; completion rate dramatically higher than self-paced
  • +Peer network of working AI engineers — alone worth the ticket price for many
  • +Capstone project is shippable portfolio piece, not throwaway homework
Cons
  • −$1,495 is steep — only pays back if you ship and complete
  • −Quality varies by instructor; do the homework before enrolling
  • −Live session timing may not work for non-US-timezone students
Mastering LLMs: Evaluation (Hamel Husain & Shreya Shankar)
Pros
  • +Defined the modern AI evals playbook — most-cited course in the space
  • +Live cohort + capstone — material commitment device
  • +Hamel and Shreya are both practicing experts, not generalists
Cons
  • −$1,995 is steep; you need to ship a real eval project to recoup
  • −Sells out fast; runs only 4-6 times/year
  • −Heavy pre-reqs: Python + production LLM shipping experience

Which course is for whom?

AI Engineer Foundations (Maven cohort)
Best for
  • · Working engineers committing to a career pivot into AI
  • · Self-directed learners who consistently start but never finish self-paced courses
Not ideal for
  • · Beginners with no Python or LLM API exposure — too steep
  • · Anyone whose schedule can't accommodate the live sessions
Mastering LLMs: Evaluation (Hamel Husain & Shreya Shankar)
Best for
  • · Engineers shipping LLM features in production who lack eval infrastructure
  • · Senior IC or staff engineers tasked with "make our AI more reliable"
Not ideal for
  • · Anyone not actively building production LLM systems
  • · Beginners — pre-reqs are real

Editor's short verdict

These cover different primary topics — AI Engineer Foundations (Maven cohort) focuses on ai engineering while Mastering LLMs: Evaluation (Hamel Husain & Shreya Shankar) focuses on ai evals. Take the one matching your current goal first; the other can come later if your interests expand.

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AI Engineer Foundations (Maven cohort) vs Mastering LLMs: Evaluation (Hamel Husain & Shreya Shankar) (2026): which course wins? · AI Agent Rank