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Foundations of Computer Science

Data Structures for Efficient Computation

Exploring Core Computational Concepts

Computer Systems and Architecture

Computer Architecture Essentials

Operating Systems Principles

Networking and Distributed Systems

Computer Networks: Models and Protocols

Distributed Systems Concepts

Software Construction and Reasoning

Programming Paradigms and Software Design

Integrated Assessments

Quiz: Algorithms and Data Structures

Quiz: Computer Architecture

Quiz: Operating Systems

Quiz: Networking

Quiz: Distributed Systems

Course Reflection and Feedback Survey

Foundations of Computation

Integrating Algorithms with Data Structures

Integrative Computer Science: Algorithms, Architecture, Systems, and Networks is a comprehensive, practice-oriented course that unifies CS fundamentals into a single, coherent journey. You’ll learn to design efficient algorithms, choose data structures that actually deliver in real workloads, and reason about performance from the CPU pipeline to distributed services at Internet scale. By connecting theory to real systems—caches and virtual memory, threads and scheduling, TCP congestion control, and consensus in distributed clusters—you’ll gain the intuition and tools to build robust, fast, and scalable software. The curriculum blends analysis with hands-on thinking: invariants and correctness proofs meet profiling and trade-off analysis; graph algorithms meet routing; synchronization hazards meet fault tolerance. Whether you’re preparing for advanced study, systems interviews, or building production systems, this course equips you to navigate complexity, make principled design choices, and communicate them clearly. Quizzes across domains help you self-assess and cement knowledge, while integrated perspectives show how components interact end-to-end. If you want to move beyond isolated topics and develop a systems-level mindset grounded in algorithmic rigor, this integrative program is for you.

Integrative Computer Science: Algorithms, Architecture, Systems, and Networks

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            <p>Integrative Computer Science: Algorithms, Architecture, Systems, and Networks is a hands-on, concept-to-practice journey through the pillars that make modern computing work. The course connects algorithmic thinking with data structures, grounds abstract computation in concrete architectures, and extends systems knowledge into networks and distributed coordination. You will learn how performance emerges from design choices: from asymptotic bounds and memory locality to cache behavior, scheduling, congestion control, and consensus. Along the way, you will reason about correctness and invariants, navigate trade-offs among latency, throughput, and scalability, and practice turning theory into robust, measurable implementations.</p>

<p>The learning path begins with the Foundations of Computer Science, covering algorithm design paradigms—greedy, divide-and-conquer, dynamic programming, and backtracking—alongside graph algorithms, NP-completeness intuition, and algorithm correctness. Complementing this, the Data Structures module examines arrays, linked lists, trees (BST, AVL/Red-Black), tries, heaps, and hash tables, including amortized analysis and the impact of memory hierarchies on performance. Computer Systems and Architecture then demystifies digital representation, datapaths and control, memory hierarchy, and parallelism, before moving into Operating Systems with processes and threads, scheduling, synchronization, memory management, and file systems. Networking and Distributed Systems explores the Internet’s layered model, TCP/UDP with congestion control, IP routing and addressing, DNS and web protocols with security basics, and distributed concepts such as RPC, replication, consistency, fault tolerance, and consensus (Raft/Paxos) with an eye to scalability and partitioning.</p>

<p>To tie software construction to these foundations, Programming Paradigms and Software Design integrates functional, object-oriented, and data-parallel styles with abstraction, modularity, interface design, testing, debugging, verification basics, and performance profiling. An additional synthesis module focuses on integrating algorithms with data structures in end-to-end problem solving. Throughout the course, integrated assessments—quizzes on algorithms and data structures, architecture, operating systems, networking, and distributed systems—reinforce core concepts and help you gauge mastery. The course concludes with a structured reflection and feedback survey to consolidate learning and guide next steps. By the end, you will be equipped to reason across the stack, optimize for real workloads, and design systems that are correct, efficient, and scalable.</p>
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