https://github.com/mukeshmithrakumar/missing-semester
The Missing Semester of My CS Education
https://github.com/mukeshmithrakumar/missing-semester
beam fastapi microservice protobuf redpanda rust streaming
Last synced: 5 months ago
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The Missing Semester of My CS Education
- Host: GitHub
- URL: https://github.com/mukeshmithrakumar/missing-semester
- Owner: mukeshmithrakumar
- Created: 2025-09-13T00:28:58.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2025-10-27T00:17:15.000Z (5 months ago)
- Last Synced: 2025-10-27T02:28:09.187Z (5 months ago)
- Topics: beam, fastapi, microservice, protobuf, redpanda, rust, streaming
- Language: Rust
- Homepage:
- Size: 19.8 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# The Missing Semester of My CS Education
Primary Goals: ***Learn topics related to you know what***
## Phase 1 - `dev-v0.0.1` (3 months)
**Streaming**
1. [ ] [Grokking Streaming Systems](https://learning.oreilly.com/library/view/grokking-streaming-systems/9781617297304/)
2. [ ] [Building Event-Driven Microservices, 2nd Edition](https://learning.oreilly.com/library/view/building-event-driven-microservices/9798341622180/)
3. [ ] [Building Resilient Streaming Analytics Systems on Google Cloud](https://www.cloudskillsboost.google/paths/16/course_templates/52)
**Rust**
1. [ ] [The Rust Programming Language Book](https://doc.rust-lang.org/book/)
2. [ ] [Rust Programming Specialization](https://www.coursera.org/specializations/rust-programming)
3. [ ] [Rustlings](https://github.com/rust-lang/rustlings/)
4. [ ] [Rust Development Classes](https://rust-classes.com/preface)
5. [ ] [Rust By Example](https://doc.rust-lang.org/rust-by-example/)
6. [ ] [The Rustonomicon](https://doc.rust-lang.org/nomicon/intro.html)
7. [ ] [Web Development with Rust](https://www.coursera.org/learn/web-development-with-rust)
8. [ ] [Rust exercises on Exercism](https://exercism.org/tracks/rust/exercises)
## Next Steps
**Finance**
1. [ ] [Financial Data Engineering](https://learning.oreilly.com/library/view/financial-data-engineering/9781098159986/)
2. [ ] [Analyzing Time Series and Sequential Data Specialization](https://www.coursera.org/specializations/time-series-sequential-data)
3. [ ] [Trading Strategies in Emerging Markets Specialization](https://www.coursera.org/specializations/trading-strategy)
4. [ ] [Machine Learning and Reinforcement Learning in Finance Specialization](https://www.coursera.org/specializations/machine-learning-reinforcement-finance)
**Data Engineering**
1. [ ] [Data Engineer Learning Path in GCP](https://www.cloudskillsboost.google/paths/16)
2. [ ] [Redpanda University](https://www.redpanda.com/university)
3. [ ] [feast](https://docs.feast.dev/)
4. [ ] [RAPIDS: GPU Accelerated Data Science](https://rapids.ai/)
5. [ ] [Accelerate Data Science Workflows with Zero Code Changes](https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+T-DS-03+V1)
6. [ ] [Accelerating End-to-End Data Science Workflows](https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+S-DS-01+V2)
7. [ ] [Analyzing and Visualizing Large Data Interactively using Accelerated Computing](https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+S-DS-05+V1)
8. [ ] [Best Practices in Feature Engineering for Tabular Data With GPU Acceleration](https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+S-DS-06+V1)
9. [ ] [Synthetic Tabular Data Generation Using Transformers](https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+S-FX-09+V1)
10. [ ] [Designing Data-Intensive Applications](https://learning.oreilly.com/library/view/designing-data-intensive-applications/9781491903063/)
11. [ ] [Data Engineering Design Patterns](https://learning.oreilly.com/library/view/data-engineering-design/9781098165826/)
12. [ ] [Designing Event-Driven Systems](https://learning.oreilly.com/library/view/designing-event-driven-systems/9781492038252/)
13. [ ] [Software Architecture Patterns for Big Data](https://www.coursera.org/learn/software-architecture-patterns-for-big-data)
14. [ ] [Streaming Systems](https://learning.oreilly.com/library/view/streaming-systems/9781491983867/)
15. [ ] [Streaming Databases](https://learning.oreilly.com/library/view/streaming-databases/9781098154820/)
**GCP/Platform**
1. [ ] [Getting Started with Terraform for Google Cloud](https://www.coursera.org/learn/getting-started-with-terraform-for-google-cloud)
2. [ ] [Infrastructure as Code with Terraform](https://www.linkedin.com/learning/paths/infrastructure-as-code-with-terraform?u=36492188)
**General**
1. [ ] [Designing Distributed Systems, 2nd Edition](https://learning.oreilly.com/library/view/designing-distributed-systems/9781098156343/)
2. [ ] [Software Architecture Patterns for Big Data](https://www.coursera.org/learn/software-architecture-patterns-for-big-data)
3. [ ] [UvA Deep Learning Tutorials](https://uvadlc-notebooks.readthedocs.io/en/latest/index.html)
4. [ ] [Computer Architecture](https://www.coursera.org/learn/comparch)
5. [ ] [Introduction to Operating Systems Specialization](https://www.coursera.org/specializations/codio-introduction-operating-systems)
6. [ ] [High-Performance and Parallel Computing Specialization](https://www.coursera.org/specializations/high-performance-parallel-computing)
7. [ ] [CS149 Parallel Computing](https://gfxcourses.stanford.edu/cs149/fall23), [video](https://youtube.com/playlist?list=PLoROMvodv4rMp7MTFr4hQsDEcX7Bx6Odp&si=UADWlntDE7hdraju)
8. [ ] [I/O-efficient algorithms](https://www.coursera.org/learn/io-efficient-algorithms)
9. [ ] [Data Structures and Performance](https://www.coursera.org/learn/data-structures-optimizing-performance)
## Optional
**GCP**
* [Data Engineering, Big Data, and Machine Learning on GCP Specialization](https://www.coursera.org/specializations/gcp-data-machine-learning)
**LLM Related**
* [Natural Language Processing for Semantic Search](https://www.pinecone.io/learn/series/nlp/)
* [Faiss: The Missing Manual](https://www.pinecone.io/learn/series/faiss/)
* [LLM Embeddings Explained: A Visual and Intuitive Guide](https://huggingface.co/spaces/hesamation/primer-llm-embedding)
* [The Ultra-Scale Playbook: Training LLMs on GPU Clusters](https://huggingface.co/spaces/nanotron/ultrascale-playbook)
* [DevOps-Projects](https://github.com/NotHarshhaa/DevOps-Projects)
* [LLM Course](https://github.com/mlabonne/llm-course)
**Generals**
* [School of SRE](https://linkedin.github.io/school-of-sre/)
* [Microservices Patterns](https://learning.oreilly.com/library/view/microservices-patterns/9781617294549/)
* [gRPC Microservices in Go](https://learning.oreilly.com/library/view/grpc-microservices-in/9781633439207/)
* [Software Engineering at Google](https://abseil.io/resources/swe-book)
* [System Design: The complete course](https://kps.hashnode.dev/system-design-the-complete-course)
* [The Missing Semester of Your CS Education](https://missing.csail.mit.edu/)
* [Designing Distributed Systems](https://learning.oreilly.com/library/view/designing-distributed-systems/9781491983638/)
**Algorithms**
* [Advanced Algorithms and Data Structures](https://learning.oreilly.com/library/view/advanced-algorithms-and/9781617295485/)
**Rust**
* [Rust Programming](https://www.risein.com/courses/rust-programming)
* [Programming with Rust Specialization](https://www.coursera.org/specializations/programming-with-rust)
**JAX**
* [Jaxformer: Scaling Modern Transformers](https://jaxformer.com/)
**ML Hardware & Systems**
* [Stanford MLSys Seminar](https://mlsys.stanford.edu/)
* [Machine Learning Systems](https://ucbrise.github.io/cs294-ai-sys-sp22/)
**ML Compilers**
* [Compilers for Machine Learning](https://www.c4ml.org/c4ml2019)
* [Machine Learning Compiler](https://mlc.ai/)
* [MLIR and MLIR Components Talks](https://mlir.llvm.org/talks/)
**NVIDIA Triton**
* [NVIDIA Dynamo Platform](https://developer.nvidia.com/dynamo)
**CUDA**
* [CUDA Mastery](https://tailoredread.com/book/cuda-mastery-advanced-techniques-high-performance-gpu-621c9c8e8c6d)
* [NVIDIA Self-Paced Courses](https://www.nvidia.com/en-us/training/self-paced-courses/)
* [GPU Programming Specialization](https://www.coursera.org/specializations/gpu-programming)
* [Parallel and High Performance Computing](https://learning.oreilly.com/library/view/parallel-and-high/9781617296468/)
**Hacking**:
* [Root Me Website](https://www.root-me.org/?lang=en)
**Linux**
* [pwn.dojos](https://pwn.college/dojos)
* [Introduction to Linux – Full Course for Beginners](https://youtu.be/sWbUDq4S6Y8?si=NC2qXNMRxT9wYc_k)
* [Linux Networking: How The Kernel Handles A TCP Connection](https://youtu.be/ck4WvYM9V4c?si=g9TnqKJpL_s3Aazb)
* [Rearchitecting Linux Storage Stack for µs Latency and High Throughput](https://www.usenix.org/conference/osdi21/presentation/hwang)
* [glibc Heap Series](https://youtube.com/playlist?list=PLZQ4UbPWTlon-F9l6KAlAjxeZsqNmxM5K&si=YvYeOg3lyX5F_Fd6)
**Network**:
* [Network Fundamentals](https://www.networkacademy.io/ccna/network-fundamentals)
* [Computer Networking Full Course - OSI Model Deep Dive with Real Life Examples](https://youtu.be/IPvYjXCsTg8?si=g2ebQPC2C5WZ8MFt)
* [Computer Networking Course - Network Engineering [CompTIA Network+ Exam Prep]](https://youtu.be/qiQR5rTSshw?si=5IbUPIQ_ej-SMAHL)
* [AWS Networking Basics For Programmers | Hands On](https://youtu.be/2doSoMN2xvI?si=NMiiAmL2APC51-PT)
**Operating Systems**:
* [Operating Systems: From 0 to 1](https://github.com/tuhdo/os01)
* [Wargames](https://overthewire.org/wargames/)
* [From Nand to Tetris](https://www.nand2tetris.org/)
* [Evolution of the Unix System Architecture: An Exploratory Case Study](https://ieeexplore.ieee.org/ielx7/32/9453223/08704965.pdf)
**Containers**:
* [Fork in the Road: Reflections and Optimizations for Cold Start Latency in Production Serverless Systems](https://www.usenix.org/conference/osdi25/presentation/chai-xiaohu)
* [Fast, lazy container loading in modal.com by Jonathon Belotti](https://youtu.be/SlkEW4C2kd4?si=KkbJDxvku2Vv-yxr)
* [How Modal built their own container runtime, file system, GPU resource solver, and more](https://youtu.be/pLBxrY8RX6w?si=827jACa2wVWnRoKm)
**Compiler**
* [A Gentle Introduction to LLVM IR](https://mcyoung.xyz/2023/08/01/llvm-ir/)