diff --git a/_modules/week-09.md b/_modules/week-09.md index e068d1d..6fc321e 100644 --- a/_modules/week-09.md +++ b/_modules/week-09.md @@ -4,7 +4,7 @@ title: Week 9 - App Development Oct 31 : App design, setup and code organization - : [Lecture 13](../assets/lectures/lecture11/09_app_development_design_setup.pdf) + : [Lecture 13](../assets/lectures/lecture13/09_app_development_design_setup.pdf) Nov 2 : APIs & Frontend diff --git a/_site/assets/lectures/lecture13/09_app_development_design_setup.pdf b/_site/assets/lectures/lecture13/09_app_development_design_setup.pdf new file mode 100644 index 0000000..682f4bc Binary files /dev/null and b/_site/assets/lectures/lecture13/09_app_development_design_setup.pdf differ diff --git a/_site/schedule/index.html b/_site/schedule/index.html index 2ad70fd..9f40e23 100644 --- a/_site/schedule/index.html +++ b/_site/schedule/index.html @@ -1 +1 @@ - Schedule and Calendar | AC215, CSCIE-115 Skip to main content Link Menu Expand (external link) Document Search Copy Copied

Schedule and Calendar

Overall schedule can be found here and calendar here.

Week 1 - Introduction, Virtual Environments and Virtual Machines

Sep 05
Introduction
Lecture 1 ,   Setup & Installation
Sep 07
Virtual Environments and Virtual Machines
Lecture 2

Week 2 - Containers

Sep 12
Containers I
Lecture 3
Sep 14
Containers II
Lecture 4
M 1 due

Week 3 - Data

Sep 19
Data Pipelines: Extract, Transform, Labeling, Versioning
Lecture 5
Sep 21
Dask
Lecture 6

Week 4 - Data and Models

Sep 26
TF Data and TF Records
Lecture 7
M 2 due
Sep 28
Advanced training workflows: experiment tracking (W&B), multi GPU, serverless training (Vertex AI), kubeflow
Lecture 8

Week 5 - Project Week

Oct 3
No class (Project Week)
Oct 5
No class (Project Week) M 3 due

Week 6 - Model

Oct 10
Distillation/Quantization/Compression, TF lite
Lecture 9
Oct 12
Model performance monitoring, data drift, or other post release items to be aware of
Lecture 10

Week 7 - ML Workflow Management

Oct 17
Cloud functions, Cloud Run, Vertex AI Pipelines
Lecture 11
Oct 19
Hands on Mushroom App Pipelines
Lecture 12

Week 8 - Midterm presentations

Oct 24
Midterm presentations (See Ed)
M 4 due
Oct 26
Midterm presentations (See Ed)
M 4 due

Week 9 - App Development

Oct 31
App design, setup and code organization
Lecture 13
Nov 2
APIs & Frontend
Lecture 14

Week 10 - App Development

Nov 7
APIs & Frontend
Lecture 15
Nov 9
Deployment
Lecture 16

Week 11 - Scaling & Deployment

Nov 14
Scaling: Kubernetes
Lecture 17
Nov 16
Projects

Week 12 - Thanks giving

Nov 20

M 5 due

Week 13 - Scaling & Deployment

Nov 28
Scaling: Kubernetes
Lecture 18
Nov 30
Deployment: Ansible
Lecture 19

Week 14 - Projects

Week 15 - Presentations

Dec 12
Presentations M 6 due

Setup & Installation

Refer to the setup and installtion document for a full list of softwares and tools we will be using in this class

Policy on Usage of Publicly Available Class Material

  1. 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.

  2. 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.

  3. 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).

  4. Enforcement: Failure to comply with this policy may result in legal action and/or disciplinary measures as applicable.

By accessing and using the Class Material, you indicate your acknowledgment and acceptance of this policy.

+ Schedule and Calendar | AC215, CSCIE-115 Skip to main content Link Menu Expand (external link) Document Search Copy Copied

Schedule and Calendar

Overall schedule can be found here and calendar here.

Week 1 - Introduction, Virtual Environments and Virtual Machines

Sep 05
Introduction
Lecture 1 ,   Setup & Installation
Sep 07
Virtual Environments and Virtual Machines
Lecture 2

Week 2 - Containers

Sep 12
Containers I
Lecture 3
Sep 14
Containers II
Lecture 4
M 1 due

Week 3 - Data

Sep 19
Data Pipelines: Extract, Transform, Labeling, Versioning
Lecture 5
Sep 21
Dask
Lecture 6

Week 4 - Data and Models

Sep 26
TF Data and TF Records
Lecture 7
M 2 due
Sep 28
Advanced training workflows: experiment tracking (W&B), multi GPU, serverless training (Vertex AI), kubeflow
Lecture 8

Week 5 - Project Week

Oct 3
No class (Project Week)
Oct 5
No class (Project Week) M 3 due

Week 6 - Model

Oct 10
Distillation/Quantization/Compression, TF lite
Lecture 9
Oct 12
Model performance monitoring, data drift, or other post release items to be aware of
Lecture 10

Week 7 - ML Workflow Management

Oct 17
Cloud functions, Cloud Run, Vertex AI Pipelines
Lecture 11
Oct 19
Hands on Mushroom App Pipelines
Lecture 12

Week 8 - Midterm presentations

Oct 24
Midterm presentations (See Ed)
M 4 due
Oct 26
Midterm presentations (See Ed)
M 4 due

Week 9 - App Development

Oct 31
App design, setup and code organization
Lecture 13
Nov 2
APIs & Frontend
Lecture 14

Week 10 - App Development

Nov 7
APIs & Frontend
Lecture 15
Nov 9
Deployment
Lecture 16

Week 11 - Scaling & Deployment

Nov 14
Scaling: Kubernetes
Lecture 17
Nov 16
Projects

Week 12 - Thanks giving

Nov 20

M 5 due

Week 13 - Scaling & Deployment

Nov 28
Scaling: Kubernetes
Lecture 18
Nov 30
Deployment: Ansible
Lecture 19

Week 14 - Projects

Week 15 - Presentations

Dec 12
Presentations M 6 due

Setup & Installation

Refer to the setup and installtion document for a full list of softwares and tools we will be using in this class

Policy on Usage of Publicly Available Class Material

  1. 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.

  2. 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.

  3. 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).

  4. Enforcement: Failure to comply with this policy may result in legal action and/or disciplinary measures as applicable.

By accessing and using the Class Material, you indicate your acknowledgment and acceptance of this policy.