diff --git a/index.qmd b/index.qmd index a6ee6f0..384cbea 100644 --- a/index.qmd +++ b/index.qmd @@ -27,13 +27,15 @@ select lectures and assignments. **Instructors:** -- Thomas Gardos (tgardos@bu.edu) -- Office hours: Tuesdays and Thursdays, 1:30-3:00pm -- Location: CDS 1623 +**Thomas Gardos** (tgardos@bu.edu) -- Ali Nahvi (TBD) -- Office hours: Thursdays 4-5pm -- Location: TBD +* Office hours: Tuesdays and Thursdays, 1:30-3:00pm +* Location: CDS 1623 + +**Ali Nahvi** (TBD) + +* Office hours: Thursdays 4-5pm +* Location: TBD Project Managers and TE: @@ -135,15 +137,16 @@ the report to your clients and the demo for Spark Demo Day. To ensure that students get the most out of this class, we require students to have taken one of -- **DS 340 (Into to Machine Learnihng and AI)** +- **DS 340 (Into to Machine Learning and AI)** +- **CS 440 (Intro to AI)** +- **CS 542 (Principles of ML)** - **DS 542 (Deep Learning for Data Science)** -- **CS 505 (Intro to Natural Language Processing)**, -- **CS 542 (Principles of Machine Learning)**, +- **CS 523 (Deep Learning)** +- **CS 505 (Intro to Natural Language Processing)** - **CS 585 (Image and Video Computing)** - **CS 640 (Artificial Intelligence)** -- **ENG EC 523 (Deep Learning)** -or have equivalent experience. You must have a strong programming background especially with proficiency in Python. Familiarity with web and/or mobile application development is helpful, though not required. Please consult with course staff during office hours if you have questions about the prerequisites. +or have equivalent experience. You must have a strong programming background especially with proficiency in Python. Familiarity with web and/or mobile application development is helpful, though not required. Please consult with course staff during class or office hours if you have questions about the prerequisites. ## Hub Learning Outcomes diff --git a/schedule.qmd b/schedule.qmd index f596edf..aca6679 100644 --- a/schedule.qmd +++ b/schedule.qmd @@ -2,6 +2,11 @@ title: Schedule --- +Abbreviations: + +- TG: Thomas Gardos +- AN: Ali Nahvi + ```{=html} @@ -16,25 +21,24 @@ title: Schedule - - + + +
Due: 11:59pm tonight - - @@ -56,7 +60,7 @@ title: Schedule - - - + @@ -86,9 +90,13 @@ title: Schedule - - + @@ -102,7 +110,7 @@ title: Schedule - @@ -118,13 +126,19 @@ title: Schedule - - + @@ -132,17 +146,18 @@ title: Schedule - - + + + + + + + @@ -176,11 +191,11 @@ title: Schedule - + @@ -188,13 +203,21 @@ title: Schedule - + + + - @@ -211,33 +234,25 @@ title: Schedule - + @@ -248,22 +263,22 @@ title: Schedule - + - + @@ -287,7 +302,7 @@ title: Schedule - + @@ -297,18 +312,15 @@ title: Schedule - + - - + + @@ -316,13 +328,13 @@ title: Schedule - + - + @@ -331,20 +343,22 @@ title: Schedule - + - + + + - + @@ -364,5 +378,22 @@ title: Schedule + + + +
Tue Jan 2101 -- Welcome, introduction, and course overview. Lecture Slides01 -- Welcome, introduction, and course overview (TG, AN). Lecture Slides Assigned: -
Due: Nothing
Thu Jan 23 02 -- Topics + 02 -- Topics (TG)
  • Project Pitches
  • Command Shells Recap
  • Python Environments
 + Bring your laptop to follow along with the lecture. Due:
    -
  • Intro Surveys
    • +
Tue Jan 28 03 -- Topics + 03 -- Topics (TG)
  • Git and GitHub
  • BU Shared Computing Cluster
    • @@ -72,13 +76,13 @@ title: Schedule
Thu Jan 30 04 -- Topics +
    -
  • ML Project Lifecycle
    • +
  • 04 -- System Design for ML Projects (AN)
  • MLops
 Lecture Slides Lecture Slides TBD Assigned:
Due:
Tue Feb 4 05 -- Team Formation and Agreement + 05 -- Topics (TG) +
    +
  • ML Project Lifecycle
    • +
  • Team Formation and Agreement
    • +
Lecture Slides Lecture Slides TBD Assigned:
Due:
Tue Feb 11 07 -- Topics + 07 -- Topics (TG)
  • Project Outline Document
  • SCC environment setup
    • @@ -110,7 +118,7 @@ title: Schedule
Thu Feb 13 08 -- Topics + 08 -- Topics (TG)
  • SCC Batch Computing
    • +
  • PLC -- Research Phase
  • Lab time
Batch computing notes + + Assigned:
Due:
Tue Feb 18 NO CLASS -- Monday Schedule Revise: 09 -- Topics -
    -
  • How to read a research paper
    • -
  • PLC -- Research Phase
    • -
  • Lab time
    • -
+ 		NO CLASS -- Monday Schedule Slides Assigned:
Due:
Thu Feb 209 -- Exploratory Data Analysis (AN) Slides TBD Assigned:
Due:
Week 6 (Project Week 4 -- EDA)
Thu Feb 27
    -
  • 11 -- Exploratory Data Analysis
    • +
  • 10 -- Intro to Pytorch and Computer Vision (Guest Lecturer)
  • Lab time
 EDA Slides Slides TBD Assigned:
Due:
Tue Mar 4TBD. +
    +
  • 11 -- PyTorch 02: Dataloaders and Transforms (AN)
    • +
  • Lab time
    • +
+ 		Slides TBD Assigned:
Due:
Thu Mar 6 + 12 --Topics
    -
  • 12 -- PyTorch 02: Dataloaders and Transforms
    • +
  • PLC Phase 04: PoC (TG)
    • +
  • PyTorch 03: Model Definition (AN)
  • Lab time
Tue Mar 18
    -
  • 13 -- PLC Phase 04: PoC
    • -
  • PyTorch 03: Model Definition
    • +
  • 13 -- How to use LLM in your workflow (Guest Lecturer)
  • Lab time
 - + Slides TBD Assigned:
Due: Presentations 		Assigned:
Due:
Thu Mar 20
    -
  • 14 -- PyTorch 04: Autograd and Backprop
    • -
  • 15 -- PyTorch 05: Training
    • +
  • 14 -- Introduction to AI Agents (Guest Lecturer)
  • Lab time
 - +
  • Slides TBD
    		• Assigned:
    Due:
    Tue Mar 25
      -
    • 16 -- LLM 01 - Building a Simple LLM App with LangChain
      • +
    • 15 -- Introduction to MLOps Cloud Technologies (Gues Lecture)
    • Lab time
    		 LLM 01 - Building a Simple LLM App with LangChain Slides TBD Assigned:
    Due:
    Thu Mar 27
      -
    • 17 -- LLM 02 - Build a simple LLM app with LangChain
      • +
    • 16 -- How to ace your MLE/DS job Interviews (Guest Lecturer)
    • Lab time
    		 LLM 02 - Build a simple LLM app with LangChain Slides TBD Assigned:
    Due:
    Thu Apr 3Lab Day -- Work with your teams on project deployment. TBA TBA Assigned:
    Due:
    Tue Apr 8 -
      -
    • 18 -- LangChain 03: Embeddings, vector stores and retrievers
      • -
    • Lab time
      • -
    + TBA     		LangChain 03: Embeddings, vector stores and retrievers TBD Assigned:
    Due:
    Thu Apr 10Lecture description. Instructor sick. Self-directed lab time. TBD. TBD. Assigned:
    Due:
    Tue Apr 15Lab Day -- Work with your teams on project deployment.TBA TBA Assigned:
    Due:
    Thu Apr 17Lab Day -- Work with your teams on project deploymentTBA TBA Assigned:
    Due:
    Tue Apr 22Lab Day -- Work with your teams on project deployment and evaluationTBA TBA Assigned:
    Due:Beta milestone check-in
    Thu Apr 24No class. Thanksgiving recess.TBA. TBA Assigned:
    Due:
    Week 14 (Project Week 12 -- Evaluation)
    Tue Apr 29Lab day -- Work with your team on project deployment/evaluation and final presentations.TBA TBA Assigned:
    Due:
    TBA Assigned:
    Due:
    ```