Image 1

Mocksphere for Students

Image 2

Mocksphere for Teacher

Image 5

Mocksphere for Parents/Guardians

Image 3

Mocksphere for Job Seeker

Image 4

Mocksphere for Recruiter

Online Workshop
Online Workshop Every Week

Join our free weekly interactive learning sessions.

Master AI/ML with instant feedback and personalized learning

"Cogito, ergo sum" (I think, therefore I am)

— René Descartes

René Descartes
Free Problems
View All Free Problems
System Design Fundamentals Practice
This problem set covers the core concepts from the video "I ACED my Technical Interviews knowing these System Design Basics". You'll practice key distributed systems concepts including scalability, reliability, caching strategies, database design, and partitioning techniques essential for designing scalable applications.
29 pts Medium 95 distributed-systems cap-theorem consistency +7
Regression Trees, Clearly Explained!!!
This problem set covers the fundamental concepts of regression trees as explained in the StatQuest video. You'll explore how regression trees work, how they're constructed, and how they handle different types of data compared to traditional linear regression. The problems progress from basic concepts to practical implementation details.
17 pts Medium 98 regression-trees classification-trees machine-learning +7
Word Embeddings: Word2Vec Practice Problems
This problem set explores Word2Vec, a milestone technique in natural language processing that converts words into meaningful numerical representations called embeddings. You'll learn about the two main Word2Vec architectures (CBOW and Skip-Gram), understand how word embeddings capture semantic relationships, and explore practical applications and limitations of this technology.
22 pts Medium 100 word-embeddings nlp-basics computer-understanding +7
Uniform Cost Search Algorithm Practice
This problem set tests your understanding of the Uniform Cost Search (UCS) algorithm as explained in the video "Uniform Cost Search Algorithm | UCS Search Algorithm in Artificial Intelligence by Mahesh Huddar". UCS is an informed search algorithm that finds the optimal path from source to goal by selecting the path with the lowest cumulative cost using a priority queue. Practice these problems to master UCS concepts and applications.
14 pts Medium 104 uniform-cost-search search-algorithms artificial-intelligence +7
Bellman Equation Advanced for Reinforcement Learning
This problem set explores the advanced Bellman equation for stochastic Markov Decision Processes (MDPs) as discussed in the video. You'll work with concepts like stochastic transitions, state transition probabilities, and the modified Bellman equation that handles uncertainty in reinforcement learning environments.
15 pts Medium 100 stochastic-mdps bellman-equation reinforcement-learning +7
Foundations of Q-Learning
This problem set covers the fundamental concepts of Q-Learning, a type of reinforcement learning in artificial intelligence. The problems test understanding of Q-values, temporal differences, the Bellman equation, and the Q-learning process as explained in the video "Foundations of Q-Learning".
27 pts Medium 99 q-learning reinforcement-learning model-characteristics +7
Premium Problems
View All Premium Problems
Python I/O and Data Pipeline Assessment - Part 4
20 questions focused on PyTorch Dataset/DataLoader design: map/iterable datasets, transforms, custom collate/padding, worker seeding/sharding, num_workers/pin_memory/prefetch_factor, caching, memmap/shared memory, batching by size, profiling, and performance tuning.
10.00 60 pts Medium 98 torch.utils.data.dataset pytorch dataset +7
Chapter 2 Numeric Python (NPSCDS)
This problem set covers key concepts from Chapter 2: Vectors, Matrices, and Multidimensional Arrays. The problems test understanding of NumPy array fundamentals, including array creation, indexing, slicing, operations, and vectorized computing. Each question is designed to reinforce the core concepts presented in the chapter.
5.00 26 pts Medium 99 numpy-arrays array-attributes shape +7
USAAIO 2025 R1P3 - Logistic Regression Implementation
This problem focuses on implementing logistic regression from scratch using the Titanic dataset. You will work through data pre-processing, mathematical derivations, and implement both gradient descent and Newton's method for logistic regression. The dataset contains passenger information from the Titanic, and your goal is to predict survival based on various features.
10.00 48 pts Easy 93 data-loading pandas data-exploration +7
USAAIO 2025 R1P2 - Basics of Neural Network - From Linear Regression to DNN Training
This problem is about the basics of neural network. Each part has its particular purpose to intentionally test you something. Do not attempt to find a shortcut to circumvent the rule. And all coding tasks shall run on CPUs, **not GPUs**.
10.00 36 pts Easy 96 learning-rate-scheduler pytorch optimization +12
USAAIO 2025 R1P1 - Fibonacci Matrix Form
Let us consider the following sequence: $$ F_n = F_{n-1} + F_{n-2},\ \forall\ n \ge 2. $$
8.00 27 pts Medium 96 fibonacci sequence linear algebra matrix form +7
IAIO 2024 Part 2 - Machine Learning Algorithms and Deep Learning
This problem covers the remaining categories of the 2024 International Artificial Intelligence Olympiad (IAIO), focusing on machine learning algorithms and deep learning. You'll work through practical implementations of k-means clustering, deep learning architectures, and advanced machine learning theory including kernel methods and the Perceptron algorithm. The problems cover: - K-means clustering algorithm implementation and convergence - Deep learning architectures (DALL-E, Transformers) - Perceptron algorithm and kernel methods - Mathematical proofs and theoretical analysis - Parameter counting and computational complexity
10.00 44 pts Hard 99 k-means clustering euclidean distance machine learning +7

Knowledge Graphs

USA AI Olympiad

Explore competitive programming and AI contest preparation concepts

View Full Graph
Grade 5 Math

Discover elementary mathematics concepts and learning paths

View Full Graph

Featured Docs

View All PDFs
Cover of System Design Interview: An Insider's Guide Volume 2
System Design Interview: An Insider's Guide Volume 2
116 questions 348 pts
Cover of System Design Interview: An Insider's Guide
System Design Interview: An Insider's Guide
108 questions 317 pts
Cover of UNICALLI: A UNIFIED DIFFUSION FRAMEWORK FOR COLUMN-LEVEL GENERATION AND RECOGNITION OF CHINESE CALLIGRAPHY
UNICALLI: A UNIFIED DIFFUSION FRAMEWORK FOR COLUMN-LEVEL GENERATION AND RECOGNITION OF CHINESE CALLIGRAPHY
10 questions 38 pts
Cover of The Principles of Deep Learning Theory
The Principles of Deep Learning Theory
107 questions 418 pts

Featured Books

View All Books
Cover of Acing the System Design Interview
Acing the System Design Interview
153 questions 456 pts
Cover of Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib
Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib
240 questions 684 pts
Cover of Hands-On Machine Learning with Scikit-Learn and PyTorch
Hands-On Machine Learning with Scikit-Learn and PyTorch
200 questions 554 pts
Cover of Deep Reinforcement Learning Hands-On - Third Edition
Deep Reinforcement Learning Hands-On - Third Edition
222 questions 720 pts

Featured Videos

View All Videos
Cover of Flow-Matching vs Diffusion Models explained side by side
Flow-Matching vs Diffusion Models explained side by side
10 questions 29 pts
Cover of Attention in transformers, step-by-step | Deep Learning Chapter 6
Attention in transformers, step-by-step | Deep Learning Chapter 6
10 questions 30 pts
Cover of Knowledge Distillation: How LLMs train each other
Knowledge Distillation: How LLMs train each other
10 questions 27 pts
Cover of Diffusion Model
Diffusion Model
10 questions 32 pts

Popular Topics

beginner 456 easy 216 fundamental-concepts 112 optimization 96 performance 87 medium 84 machine-learning 83 distributed-systems 83 fundamentals 82 basic-concepts 78 linear-algebra 77 architecture 74 classification 73 data-structures 73 time-complexity 66 system-design 66 scalability 64 calculation 63 neural-networks 61 machine learning 58
Click on any tag to filter problems by that topic