• Format — 1,400+ MCQs with an instant explanation on every wrong answer
• Duration — about 16 hours of focused practice, most learners over three to six weeks
• Level — intermediate; assumes SystemVerilog language basics
• Cost — free, with a verifiable completion certificate
• Audience — DV engineers, RTL designers moving to verification, DV placement candidates
• Prerequisite — SystemVerilog Verification: Foundations

This course is for engineers who can already write SystemVerilog classes, interfaces and processes but have not yet built constrained-random stimulus, a coverage model, or assertions — and for those who learned these on the job and have gaps in the harder parts. It suits DV placement candidates, RTL designers crossing into verification, and verification engineers who want to tighten their constraint, coverage and SVA skills. It is intentionally intermediate: the language itself is not re-taught.

The 12 topics are grouped into the three pillars of constrained-random verification, ending with a mastery topic that ties them together.

Constrained randomization

• Introduction to Constrained Random Verification — why CRV beats directed testing, and the randomize-coverage-assertion loop
• Randomization Mechanics — rand vs randc, the randomize() call, and seed stability
• Constraint Fundamentals — constraint blocks, inside sets, ranges and implication
• Advanced Constraint Techniques — solve-before ordering, dist weighting, foreach and soft constraints
• Controlling & Randomizing Complex Types — rand_mode, constraint_mode, pre/post_randomize, and randomizing arrays and objects

Functional coverage

• Functional Coverage Fundamentals — covergroups, coverpoints, sampling and options
• Bins & Cross Coverage — explicit, transition, ignore and illegal bins; cross with binsof and intersect
• Coverage Methodology & Closure — code vs functional coverage, holes, exclusions and merging

SystemVerilog Assertions

• Assertion Fundamentals — immediate vs concurrent assertions and sampling semantics
• SVA Sequences & Properties — implication, repetition and sequence operators
• Advanced SVA & Assertion Usage — multi-clock sequences, vacuity, cover, assume and bind
• CRV Mastery — comparisons, when-to-use decisions, and applying all three pillars to testbench scenarios

Directed testing writes one test per scenario — predictable, but it scales badly and misses the corner cases nobody thought to write. Constrained-random verification instead randomizes legal stimulus under constraints, so a single test can hit thousands of cases, and functional coverage tells you which ones actually ran. Assertions then check correctness continuously rather than at the end. The trade-off is that CRV needs discipline: constraints must be solvable, coverage must be meaningful, and assertions must not pass vacuously. This course drills exactly that discipline, which is why CRV is the industry default for anything beyond a trivial block.

Video platforms walk you through CRV concepts; this course tests whether they stuck. Watching someone explain solve-before ordering or cross coverage builds recognition, but interviews and real debugging demand retrieval — producing the answer yourself. Each MCQ here forces a decision and then explains it, so a wrong guess becomes a correction you remember. Most learners pair the two: a lecture once for first exposure, then repetition here until constraint, coverage and assertion behaviour is automatic.

Write small constraints, coverage models and assertions, predict their behaviour, then check yourself — repeatedly, spaced over weeks. CRV is full of subtle behaviour: why a constraint is unsolvable, why a covergroup never samples, why an assertion passes vacuously. Recognizing these by reading is easy; fixing them under pressure is not. This course is built around that retrieval loop, and it pairs well with running the same examples in a free simulator to watch them solve and sample.

You answer one question at a time. A correct answer moves you on; a wrong one shows an explanation first, so every mistake teaches something. An AI study guide notices which topics you miss — constraint solver ordering, illegal bins, multi-clock assertions — and steers you back to them rather than letting you re-drill what you already know. Progress is saved, so a topic fits into a short session.

About 16 hours of focused practice. That is the 1,400+ MCQs at roughly 40 seconds each including explanations — around 980 minutes, or just over 16 hours. At 80 questions a day you finish in under three weeks; at 40 a day, about five weeks. The three pillars make natural weekly milestones — randomization, then coverage, then assertions — and spacing the work lets retrieval do its job. Cramming all 1,400 in a weekend is possible but wastes the spacing effect.

This course assumes the language, so if constraints and classes are new, start with SystemVerilog Verification: Foundations first. After finishing, move to UVM Foundations, where these techniques get organized into a reusable methodology — sequences randomize items, subscribers collect coverage, and assertions live in interfaces. If you are preparing for placements in parallel, the DV Interview Prep (Entry-Level) course drills the cross-cutting questions interviewers ask across all of these areas.