• Format — 2,400+ free MCQs with instant explanations after every wrong answer.
• Duration — about 27.3 hours of focused practice; most learners finish over 5–8 weeks at 45–75 minutes a day.
• Level — intermediate to advanced. Assumes Java fundamentals (OOP, generics, collections, exceptions). No prior concurrency experience required.
• Cost — free, with a free completion certificate.
• Audience — working Java developers stepping up to senior roles, candidates preparing for product-company Java concurrency rounds, backend engineers debugging real race conditions, JVM developers in fintech, payments, ad-tech, and data infrastructure.
• Recommended before this — Java Fundamentals (the entry-point Java course on Abekus, covering language basics and OOP).
• Companion comparison — Python for learners comparing the GIL-bound concurrency model with Java's true threading.

Three audiences specifically. First, working Java developers who can write synchronized methods and call ExecutorService but have never sat down with the Java Memory Model — the people whose code passes review and then ships a race that only fires on production load. Second, candidates preparing for senior Java interviews at product companies, where the concurrency round is output-prediction (does this counter see the update?), pattern selection (synchronized, ReentrantLock, atomic, or CompletableFuture for this scenario?), and pitfall recognition (the classic double-checked locking trap, the ThreadLocal leak inside an app server). Third, JVM backend engineers in fintech, payments, ad-tech, and data infrastructure whose work is built on thread pools, blocking queues, and concurrent collections, and who want the model in their head before they design the next pipeline.

This course is not a Java starter. If you do not already know Java's OOP model, generics, exceptions, and Collections framework, work through a Java fundamentals course first and come back. The first topic introduces concurrency concepts but assumes the language itself is comfortable.

Foundations — threads and coordination

• Introduction to Concurrency — concurrency concepts (parallelism vs concurrency, race conditions, deadlock, liveness), the Java concurrency landscape (threads, executors, JMM, java.util.concurrent).
• Thread Basics — creating threads via Thread and Runnable, the thread lifecycle and state diagram, thread properties (name, priority, daemon).
• Thread Coordination — join and sleep semantics, the interrupt mechanism (how it actually works and when it is swallowed), yield and coordination patterns.

Depth — synchronization, memory model, and primitives

• Synchronization — the synchronized keyword on methods and blocks, lock contention and visibility, thread-safe patterns (immutable objects, confinement, copy-on-write).
• Volatile & Java Memory Model — the volatile keyword, the JMM happens-before relationship, visibility issues (stale reads, missed updates, instruction reordering).
• Wait, Notify & Thread Communication — wait and notify on intrinsic locks, the producer-consumer pattern done correctly, Condition objects with explicit locks.
• Locks & Atomic Variables — ReentrantLock with fairness and timeouts, ReadWriteLock and StampedLock trade-offs, atomic variables (AtomicInteger, AtomicReference, compare-and-set semantics).
• Executor Framework — Executor and ExecutorService, fixed and cached and scheduled thread pools (when each is right and when each is wrong), Callable and Future.
• CompletableFuture — CompletableFuture basics, chaining and combining (thenApply, thenCompose, allOf, anyOf), advanced patterns (timeouts, exception handling, custom executors).

Production patterns — concurrent collections and pitfalls

• Concurrent Collections & Synchronizers — ConcurrentHashMap and CopyOnWriteArrayList, BlockingQueue operations and their take/put/offer/poll variants, synchronizers (CountDownLatch, CyclicBarrier, Semaphore, Phaser).
• Thread Safety Patterns & Pitfalls — liveness problems (deadlock, livelock, starvation), ThreadLocal (use cases and the classic leak in long-lived pools), performance and design trade-offs.
• Java Concurrency in Practice — concept comparisons (synchronized vs ReentrantLock, volatile vs AtomicInteger, ConcurrentHashMap vs Collections.synchronizedMap), pattern selection (which tool for which problem), and concurrency in real production code.

The three Java tools for protecting shared state, asked about in nearly every senior Java interview, and a question this course makes you stop guessing at. synchronized is the simplest — an intrinsic lock on an object that gives you mutual exclusion plus the JMM visibility guarantee, with no try/finally bookkeeping. ReentrantLock gives you the same exclusion plus features synchronized cannot: timed and interruptible lock acquisition, fairness, and Condition objects for fine-grained waiting. Atomic variables skip locks entirely and use compare-and-set instructions for single-variable updates — faster under low contention, useless for compound operations across multiple variables.

The course works through this with output-prediction MCQs (does this counter see the increment?), pattern questions (this read-heavy cache wants ReadWriteLock; this counter wants AtomicInteger; this multi-field invariant needs synchronized), and trap questions (atomic on each field still races at the compound level — when and why). The Synchronization, Locks & Atomic Variables, and In Practice topics drill these comparisons until pattern selection is automatic.

One of the more useful comparisons for developers crossing over from Python. CPython has a Global Interpreter Lock (GIL) that serializes Python bytecode execution, so threads do not give you true CPU parallelism — they help with I/O concurrency but not with CPU-bound work, where multiprocessing is the actual answer. Java has no GIL. JVM threads run on real OS threads with true parallel execution on multi-core hardware, which is why the language invests so heavily in memory-model rigour (happens-before, volatile, synchronized) — the hardware can actually reorder and cache.

For a Python developer, this means concurrency questions you could get away with in Python (mutable state across threads often "works" because of the GIL) become real bugs in Java. The Volatile & Java Memory Model and Thread Safety Patterns topics are where this lands hardest.

Active recall on real code, not passive reading. Reading the Brian Goetz book once is a rite of passage but a week later you will still mis-predict whether a volatile long write is atomic on a 32-bit JVM, or whether double-checked locking without volatile is safe. The retrieval that sticks is: see the snippet, predict the output (or 'is this safe? if not, why?'), commit, get told why. That is what MCQ practice forces every single question.

Concurrency is unusually rule-dense — happens-before edges, lock acquisition order, visibility semantics, the exact reentrancy and fairness behaviour of each lock type. The 2,460 questions in this course are spread across the 12 topics so every concept comes back in different framings until the model in your head matches the JMM spec.

One question at a time. You read a snippet (often a 10–20 line concurrent class or method), pick the option that matches what the snippet computes, prints, or whether it is thread-safe at all, and submit. Wrong answers trigger an explanation that walks through the actual interleaving — the happens-before edge that was missing, the lock that was released too early, the visibility guarantee that volatile gives but synchronized also gives, the ABA scenario that defeats a naive compare-and-set.

The Abekus AI guide watches which topics you keep getting wrong and surfaces them more often. If you nail thread basics but keep mis-predicting CompletableFuture chains, the next session leans on chaining and combining. The certificate is gated on completing every top-level topic, so the depth signal is honest.

Plan on roughly 27.3 hours of focused practice. The math: 2,460 active questions × ~40 seconds per question (reading the snippet, picking an answer, skimming the explanation when wrong) = ~1,640 minutes = ~27.3 hours.

Most learners spread that across 5–8 weeks at 45–75 minutes a day. Some compress it into a long fortnight before a senior interview; that works for refresh mode but retention is weaker than spacing it out. Trust the spacing — JMM and lock semantics in particular only stick after the same trap has been rephrased four or five different ways.

This course assumes Java fundamentals — the entry-point Java Fundamentals course on Abekus covers the language basics, OOP, and exceptions you need before starting here. If you are picking the Java track up from scratch, do that course first. After concurrency, the natural next steps in the Java Mastery track are Java JVM & Performance (garbage collection, JIT, profiling), Java Streams & Functional Programming (parallel streams build on the executor framework you learn here), and Java Interview Mastery (senior-round trap recognition across the whole language).

For learners comparing concurrency models across languages, the Python course on Abekus is a useful adjacent — Python's GIL-bound threading versus Java's true threading is one of the cleanest contrasts in language design, and developers who understand both have a sharper instinct for when to reach for which tool.