From e06642748e6b7a381822f77806aea5d5a5f8044a Mon Sep 17 00:00:00 2001 From: Rashmi Banthia Date: Mon, 16 Sep 2024 06:51:01 -0400 Subject: [PATCH] L05_data_pipelines_part1.pdf placeholder --- _modules/week-03.md | 8 +++----- .../lecture5/L05_data_pipelines_part1.pdf | Bin 0 -> 1583979 bytes .../lecture5/under-construction-gif-17.gif | Bin 268497 -> 0 bytes _site/schedule/index.html | 2 +- .../lecture5/L05_data_pipelines_part1.pdf | Bin 0 -> 1583979 bytes .../lecture5/under-construction-gif-17.gif | Bin 268497 -> 0 bytes 6 files changed, 4 insertions(+), 6 deletions(-) create mode 100644 _site/assets/lectures/lecture5/L05_data_pipelines_part1.pdf delete mode 100644 _site/assets/lectures/lecture5/under-construction-gif-17.gif create mode 100644 assets/lectures/lecture5/L05_data_pipelines_part1.pdf delete mode 100644 assets/lectures/lecture5/under-construction-gif-17.gif diff --git a/_modules/week-03.md b/_modules/week-03.md index 11e6a1a..865da60 100644 --- a/_modules/week-03.md +++ b/_modules/week-03.md @@ -3,13 +3,11 @@ title: Week 3 - Data Pipelines, TF Data, PyTorch Datasets --- Sep 17 -: Data Pipelines/ Data Management: Extract, Transform, Data Version - : [Lecture 5](../assets/lectures/lecture5/under-construction-gif-17.gif) - +: Data Pipelines/ Data Management: Extract, Transform, Data Version +: [Lecture 5](../assets/lectures/lecture5/L05_data_pipelines_part1.pdf) Sep 19 : TF Data, TF Records, PyTorch Dataset, DataLoader, Cloud Storage - : [Lecture 6](../assets/lectures/lecture6/under-construction-gif-17.gif) +: [Lecture 6](../assets/lectures/lecture6/under-construction-gif-17.gif) - : [**M1 due 09/20**](https://harvard-iacs.github.io/2024-AC215/milestone1/){: .label .label-red } diff --git a/_site/assets/lectures/lecture5/L05_data_pipelines_part1.pdf b/_site/assets/lectures/lecture5/L05_data_pipelines_part1.pdf new file mode 100644 index 0000000000000000000000000000000000000000..6e0835132d5d603f64df24a6801b04a9893c3b9b GIT binary patch literal 1583979 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    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

    Sep 10
    Containers I
    Lecture 3
    Sep 12
    Containers II
    Lecture 4  

    Week 3 - Data Pipelines, TF Data, PyTorch Datasets

    Sep 17
    Data Pipelines/ Data Management: Extract, Transform, Data Version
    Lecture 5
    Sep 19
    TF Data, TF Records, PyTorch Dataset, DataLoader, Cloud Storage
    Lecture 6

    M1 due 09/20

    Week 4 - LLM Tools and Agents

    Sep 24
    LLM tools and agents 1: LangChain, LlamaIndex, API calls, RAG, AI agents
    Lecture 7
    Sep 26
    LLM tools and agents 2: LangChain, LamaIndex, API calls, RAG, AI agents
    Lecture 8

    HW 1 due 09/27

    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

    M2 due 10/18

    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

    HW2 due 11/08

    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

    M4 due 11/15

    Week 12 - Scaling Kubernetes, CI CD

    Nov 19
    Scaling: Kubernetes
    Lecture 20
    Nov 21
    Final: CI/CD releases
    Lecture 21

    Week 13 - Thanksgiving

    Nov 26
    Thanksgiving Week
    Nov 28
    Thanksgiving Week

    Week 14 - Projects

    Dec 3
    Project

    HW3 due 12/02

    Week 15 - Projects

    Dec 11
    Project Deliverables Due

    M 5 due 12/11

    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

    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 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, Virtual Machines

    Sep 03
    Introduction
    Lecture 1 ,   Setup & Installation
    Sep 05
    Virtual Enviroments and Virtual Machines
    Lecture 2

    Week 2 - Containers

    Sep 10
    Containers I
    Lecture 3
    Sep 12
    Containers II
    Lecture 4  

    Week 3 - Data Pipelines, TF Data, PyTorch Datasets

    Sep 17
    Data Pipelines/ Data Management: Extract, Transform, Data Version
    Lecture 5
    Sep 19
    TF Data, TF Records, PyTorch Dataset, DataLoader, Cloud Storage
    Lecture 6

    M1 due 09/20

    Week 4 - LLM Tools and Agents

    Sep 24
    LLM tools and agents 1: LangChain, LlamaIndex, API calls, RAG, AI agents
    Lecture 7
    Sep 26
    LLM tools and agents 2: LangChain, LamaIndex, API calls, RAG, AI agents
    Lecture 8

    HW 1 due 09/27

    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

    M2 due 10/18

    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

    HW2 due 11/08

    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

    M4 due 11/15

    Week 12 - Scaling Kubernetes, CI CD

    Nov 19
    Scaling: Kubernetes
    Lecture 20
    Nov 21
    Final: CI/CD releases
    Lecture 21

    Week 13 - Thanksgiving

    Nov 26
    Thanksgiving Week
    Nov 28
    Thanksgiving Week

    Week 14 - Projects

    Dec 3
    Project

    HW3 due 12/02

    Week 15 - Projects

    Dec 11
    Project Deliverables Due

    M 5 due 12/11

    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

    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.

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