Bundles

The complete 3-step roadmap to master AI math, code neural networks from scratch, and keep the ultimate quick-reference sheet at your desk.The ultimate 3-step roadmap to bridge the gap between AI math and Python code. Master foundational formulas, build neural networks from scratch, and keep the ultimate quick-reference sheet at your desk.

From architecture to implementation, determinism reduces complexity. Learn how to design predictable systems and preserve architectural intent through abstraction and deterministic code generation.

The ultimate guide to cracking Android technical interviews, a dissection of what runs beneath every @Composable, and unlocking the 'How' and 'Why' behind Kotlin fundamentals and internal mechanisms.

The ultimate guide to cracking Android technical interviews and a dissection of what runs beneath every @Composable.

From your first LLM call to production-grade AI systems. Seven books covering agents, MCP, prompt engineering, evals, cost optimization, and observability — the complete engineering stack for building with AI in 2026. Save over 40% versus buying individually.

Everything is connected.People, computers, businesses, cities, knowledge, and intelligent systems all exist within networks of relationships.Understanding those relationships is the key to modern Artificial Intelligence.The Graph Theory with AI Applications Complete Series (VOL-1 & VOL-2) takes readers from classical graph theory foundations to cutting-edge Graph Neural Networks and Graph AI.Inside this bundle, you'll discover:✓ Graph Theory Fundamentals✓ Graph Traversal and Pathfinding Algorithms✓ Shortest Path and Network Optimization✓ Social Network Analysis✓ Community Detection and Graph Mining✓ Graph Representation Learning✓ Graph Embeddings (DeepWalk, Node2Vec, LINE)✓ Graph Neural Networks (GCN, GAT, GraphSAGE)✓ Knowledge Graphs and Graph-Based NLP✓ AI-Powered Recommendation Systems✓ Cybersecurity and Fraud Detection✓ Explainable Graph AI✓ Distributed Graph Learning✓ Graph Foundation Models✓ Quantum Graph Neural NetworksWhether you are a student, researcher, educator, or AI professional, this bundle provides the mathematical foundations and modern AI techniques required to understand how intelligent systems learn from connected data.Learn Graph Theory.Master Graph Neural Networks.Build the future of connected intelligence.

What is intelligence?At its core, intelligence is the ability to acquire, compress, transform, communicate, and generate information.The Information Theory and Artificial Intelligence Complete Series explores the mathematical foundations that power modern machine learning, deep learning, generative AI, reinforcement learning, and large language models.Inside this two-volume series, you'll discover:✓ Shannon Entropy and Information Measures✓ Mutual Information and Representation Learning✓ Cross-Entropy and KL Divergence✓ Data Compression and Coding Theory✓ Information Bottleneck Theory✓ Variational Autoencoders (VAEs)✓ Contrastive and Self-Supervised Learning✓ Generative Adversarial Networks (GANs)✓ Entropy-Driven Reinforcement Learning✓ Fisher Information and Information Geometry✓ Information Theory Behind Transformers and LLMs✓ Federated Learning and Distributed Intelligence✓ Explainable AI Through Entropy✓ Quantum Information Theory✓ AI Fairness, Safety, Alignment, and Future ResearchWhether you are learning information theory for the first time or exploring the mathematical foundations of advanced AI systems, this bundle provides the tools, theory, and insights needed to understand how information becomes intelligence.Learn not just how AI works—but why it works.

What happens when intelligent machines must compete, cooperate, negotiate, and learn in the same environment?The answer lies at the intersection of Game Theory and Artificial Intelligence.This complete two-volume series explores how modern AI systems make strategic decisions in environments filled with uncertainty, competition, cooperation, and dynamic interactions.Inside the bundle, you'll discover:✓ Classical Game Theory and Nash Equilibrium✓ Multi-Agent Systems and Distributed Intelligence✓ Reinforcement Learning and Multi-Agent RL✓ Deep Reinforcement Learning Algorithms✓ Nash Q-Learning, Minimax-Q, and Correlated-Q✓ DQN, Actor-Critic, MADDPG, QMIX, and CTDE✓ Mechanism Design and Incentive Engineering✓ Decision Making Under Uncertainty✓ Social Choice Theory and Collective Intelligence✓ Applications in Robotics, Economics, Networks, and Cybersecurity✓ Evolutionary and Quantum Game Theory✓ AI Safety, Governance, and Alignment✓ Future Research Directions in Strategic AIFrom autonomous vehicles and intelligent robots to cybersecurity defense systems and large-scale AI simulations, this bundle provides the mathematical foundations, algorithmic techniques, and practical insights needed to understand the future of intelligent autonomous systems.Whether you are a student, researcher, engineer, educator, or AI professional, this series offers a comprehensive roadmap to mastering strategic artificial intelligence and multi-agent intelligence.

The complete ECBA® prep toolkit — study guide, 555-question bank, and 4 full mock exams. 755+ practice questions, full rationales, near-miss analysis. Save $20 vs. buying separately.

755 ECBA® practice questions — 4 full mock exams plus a 555-question domain bank. Near-miss analysis on every answer. Save 26% vs. buying separately.

200 ECBA® practice questions across 4 full mock exams — near-miss analysis on every answer, Blueprint V1.1 aligned. Save 22% vs. buying separately.

Why learn to touch-type Chinese, or failing that, why learn this shape-based input system? Because it is one way of practicing a key element of learning, breaking things down into clearly defined (and recognizable) elements. Plus, it's really cool to touch-type Chinese (Traditional Chinese) characters.