Schedule and Calendar
Overall schedule can be found here and calendar here.
Week 1 - Introduction, Virtual Environments, Virtual Machines
- Sep 03
- Introduction
- Lecture 1 , Setup & Installation
- Sep 05
- Virtual Enviroments and Virtual Machines
- Lecture 2
Week 2 - Containers
Week 3 - Data Pipelines, TF Data, PyTorch Datasets
Week 4 - LLM Tools and Agents
Week 5 - Data, Advanced training workflows
- Oct 1
- Model Optimization: Distillation, Quantization, Compression, and LORA
- Lecture 9
- Oct 3
- LLM fine tuning and LORA
- Lecture 10
Week 6 - Project Week
- Oct 8
- Project
- Oct 10
- Project
Week 7 - Guest Lecture, Advanced Training Workflows
- Oct 15
- Modal Labs - Guest Lecture
- Lecture 11
- Oct 17
- Advanced training workflows: experiment tracking (W&B), multi GPU, serverless training (Vertex AI), LLM fine tuning
- Lecture 12
Week 8 - Model Deployment, Performance Monitoring
- Oct 22
- Model Deployment: Hosting, APIs, and Serving LLMs
- Lecture 13
- Oct 24
- Model performance monitoring, data drift, or other post release items
- Lecture 14
Week 9 - Midterm, Cloud Functions, Vertex AI Pipelines
- Oct 29
- Testing, Cloud Functions, Cloud Run, Kubeflow, Vertex AI Pipelines
- Lecture 15
- Oct 31
- Midterm (M3) Presentations
- M3 due 10/31
Week 10 - Github Actions, App Development
- Nov 5
- Automating Software Development: CI/CD with GitHub Actions and other tools
- Lecture 16
- Nov 7
- App design, setup and code organization
- Lecture 17
Week 11 - APIs & Frontend, Ansible
- Nov 12
- APIs & Frontend (Optional: Frontend - React - To be Scheduled on Zoom)
- Lecture 18
- Nov 14
- Deployment: Ansible
- Lecture 19
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Week 12 - Scaling Kubernetes, CI CD
- Nov 19
- Scaling: Kubernetes
- Lecture 20
- Nov 21
- Final: CI/CD releases
- Lecture 21
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Week 13 - Thanksgiving
- Nov 26
- Thanksgiving Week
- Nov 28
- Thanksgiving Week
Week 14 - Projects
- Dec 3
- Project
Week 15 - Projects
- Dec 11
- Project Deliverables Due
Setup & Installation
Refer to the setup and installation document for a full list of softwares and tools we will be using in this class
Policy on Usage of Publicly Available Class Material
Permitted Use: Class Material is made available primarily for the educational benefit of enrolled students and may be used by others for personal educational purposes only.
- Prohibited Use:
- Selling or commercializing any part of the Class Material.
- Sharing, distributing, or publishing any part of the Class Material in any form or through any medium without explicit permission from the instructor.
- Modifying or altering the Class Material to create derivative works.
Attribution: Any permitted use of the Class Material must carry appropriate acknowledgment of the source (e.g., the instructor’s name, course title, and institution).
- Enforcement: Failure to comply with this policy may result in legal action and/or disciplinary measures as applicable.
Consent:
By accessing and using the Class Material, you indicate your acknowledgment and acceptance of this policy.