Schedule
Overall schedule can be found here.
Week 1 - Introduction, Virtual Environments, Virtual Machines
- Sep 02
- Introduction
- Lecture 1 , Setup & Installation
- Sep 04
- Virtual Enviroments and Virtual Machines
- Lecture 2
Week 2 - Containers
Week 3 - Containers, App Design
Week 4 - Project Ideation week
- Sep 23
- Project Ideation week
- Sep 25
- Project Ideation week
Week 5 - LLMs - I
Week 6 - LLMs - II
- Oct 7
- LLM: RAGs / Agents
- Lecture 9
- Oct 9
- LLM: Agents
- Lecture 10
Week 7 - LLMs - III
- Oct 14
- LLM: Finetuning
- Lecture 11
- Oct 16
- Advanced training workflows: experiment tracking (W&B), multi GPU, serverless training (Vertex AI)
- Lecture 12
Week 8 - Serverless
- Oct 21
- Serverless Deployment: Cloud Functions, Cloud Run
- Lecture 13
- Oct 23
- ML Workflows with Vertex AI
- Lecture 14
Week 9 - Midterm , Guest Lecture
- Oct 28
- Midterm
- Oct 30
- Guest Lecture - Modal Labs
Week 10 - APIs and Frontend
- Nov 4
- APIs
- Lecture 15
- Nov 6
- Frontend
- Lecture 16
Week 11 - CI/CD with GitHub Actions
- Nov 11
- Automating Software Development: CI/CD with GitHub Actions and other tools I
- Lecture 17
- Nov 13
- Automating Software Development: CI/CD with GitHub Actions and other tools II
- Lecture 18
Week 12 - Scaling Kubernetes
- Nov 18
- Deployment: Pulumi
- Lecture 19
- Nov 20
- Scaling: Kubernetes
- Lecture 20
Week 13 - Thanksgiving
- Nov 25
- Thanksgiving Week
- Nov 27
- Thanksgiving Week
Week 14 - Final deployment and review
- Dec 2
- Final deployment and review
- Lecture 21
Week 15 - Projects
- Dec 10
- Showcase
- 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.