This repository contains a list of MIT OpenCourseWare courses with content focused on computational science and low-level topics, bypassing courses that are exclusively or mostly centered on mathematics.
scraper.py: Python script to scrape course data from MIT OpenCourseWare.requirements.txt: The list of requirements to run scraper.py.list.md: A list of all the scraped courses in an enumerated Markdown format.README.md: The comprehensive guide (this file) explaining the curriculum.
Below is the learning path, organized to build a solid foundation in computer science, C, and low-level topics in general. The courses are structured in sequential order, with optional courses inserted in logical places based on the knowledge needed to complete them.
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Introduction to Computer Science and Programming in Python (15) [CORE]
- Purpose: Learn programming basics and foundational computer science concepts.
- Why It’s Important: Introduces problem-solving techniques and sets the stage for understanding more advanced topics.
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Mathematics for Computer Science (55) [CORE]
- Purpose: Focus on discrete mathematics and structures relevant to computer science.
- Why It’s Important: Provides the mathematical tools necessary for algorithms and systems.
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Introduction to C Memory Management and C++ Object-Oriented Programming (77) [CORE]
- Purpose: Understand memory management in C and fundamental OOP concepts in C++.
- Why It’s Important: These skills are essential for working with low-level systems and performance-critical applications.
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Practical Programming in C (17) [CORE]
- Purpose: Gain a deeper understanding of C programming and its interaction with system-level operations.
- Why It’s Important: Develops practical skills for low-level and system programming.
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Effective Programming in C and C++ (50) [CORE]
- Purpose: Master advanced programming techniques and effective practices.
- Why It’s Important: Enhances your ability to write efficient and maintainable low-level code.
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Elements of Software Construction (23) [OPTIONAL]
- Purpose: Learn secure software design principles and patterns.
- Why It’s Important: Helps ensure reliability and security in software systems.
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Introduction to Electronics, Signals, and Measurement (80) [OPTIONAL]
- Purpose: Explore hardware fundamentals and signal processing.
- Why It’s Important: Useful for understanding the interplay between software and hardware.
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Computation Structures (28) [CORE]
- Purpose: Study computer architecture, assembly language, and digital logic.
- Why It’s Important: Builds a comprehensive understanding of how computers function at a low level.
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Introductory Digital Systems Laboratory (26) [CORE]
- Purpose: Hands-on experience with digital systems and their design.
- Why It’s Important: Complements theoretical knowledge with practical applications.
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Software Construction (39) [OPTIONAL]
- Purpose: Advanced software design techniques and secure architecture.
- Why It’s Important: Enhances skills in building robust and scalable software.
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Operating System Engineering (67) [CORE]
- Purpose: Learn how operating systems work, including process management and memory handling.
- Why It’s Important: A foundational topic for understanding system-level programming.
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Performance Engineering of Software Systems (46) [CORE]
- Purpose: Techniques for analyzing and optimizing software performance.
- Why It’s Important: Helps you write efficient and scalable applications.
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Fundamentals of Program Analysis (83) [CORE]
- Purpose: Study techniques for analyzing software behavior.
- Why It’s Important: Useful for ensuring correctness and reliability in complex programs.
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Multicore Programming Primer (95) [OPTIONAL]
- Purpose: Learn concepts of parallel programming and multithreading.
- Why It’s Important: Critical for developing applications that leverage modern multicore architectures.
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Computer System Engineering (2) [CORE]
- Purpose: Study distributed systems and their design principles.
- Why It’s Important: Fundamental for understanding modern computing systems.
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Database Systems (9) [OPTIONAL]
- Purpose: Explore database architecture and design.
- Why It’s Important: Useful for understanding data management in applications.
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Introduction to Algorithms (29) [CORE]
- Purpose: Learn data structures and algorithm analysis.
- Why It’s Important: Foundational for solving computational problems effectively.
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Software Engineering for Web Applications (20) [OPTIONAL]
- Purpose: Study web development and security principles.
- Why It’s Important: Complements knowledge in systems programming with web-related skills.
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Computer Language Engineering (37) [CORE]
- Purpose: Learn compiler design and code analysis techniques.
- Why It’s Important: Essential for understanding programming languages at a deeper level.
- CORE courses form the backbone of this learning path.
- OPTIONAL courses provide additional depth in specific areas and should be pursued after acquiring the relevant fundamentals.
- The list is arranged to ensure prerequisites are completed before advancing to more complex topics.
- The actual availability of the courses has not been reviewed, as I take them I will update if they can be really studied.
- This repository is an ongoing project. Contributions are welcome for improvement and updates.
The code is simply something I used to create a list of courses and then curate it. If anyone finds it useful, I'll just leave it here.