Syllabus | Module 2

Day 1 | Monday, March 4, 2024

Module 2 Introduction (45 min)

• Welcome Back
• Interim Check In
• Where we are in Earth Systems Data Science in the Cloud
• Course Goals and Objectives
• Module Goals and Objectives
• Course Logistics

Going to Cloud9 (60 min)

• Introduction to Cloud9
• AWS Credentials Management
• Connecting Git
• Installing Packages

To the Cloud | Introduction to AWS (60 min)

• Intro to AWS
• AWS Services:
  • EC2
  • S3
  • Sagemaker
  • Lambda

Lunch and Learn

• Individual and Team Progress Check In

Setting up a Team Project Repo (60 min)

• Initializing GitLab Repos
• Collaborations
• Issues & Branching
• SSH Setup

Day 2 | Tuesday, March 5, 2024

Input/Output (I/O) (60min)

• Data Formats
• I/O on the Cloud
• Foundations for Performant Data Science

Team Project Check In (30 min)

• Team Name
• Project Ideation
• Project Idea Curation

Containers: Reproducible Computing Environments (60 min)

• Containers & Containerization
• Dependency Management
• Deployment, Use, and Sharing
• Using Containers on Cloud9

Rich Signell | Visiting Speaker (60 min)

• Pangeo: A community platform for open, reproducible, and scalable geoscience

Lunch and Learn

• Individual and Team Progress Check In

Programmatic Cloud Access (60 min)

• AWS CLI
• Boto3
• Other tools

Team Project Play (60 min)

• Intro to Exploratory Data Analysis
• Finding Data
• Getting Data on the cloud

Day 3 | Wednesday, March 6, 2024

Team Project Work (120 min)

• Review from Yesterday
• Finding Data
• Getting Data on the cloud
• Exploratory Data Analysis

Managing Containers (60 min)

• Finding Running Containers
• Entering Running Containers
• Removing Running Containers

Lunch and Learn

• EDA Questions and Check In

I/O in Python (60 min)

• Lazy Loading Constructs
• Tabular Data
• Gridded Data

Overleaf & LaTeX: Production Publishing (60 min)

• Overleaf Introduction
• Overleaf Configuration
• Accelerating collaboration & publication

Day 4 | Thursday, March 7, 2024

Introduction to Data Cleaning (60 min)

• Grammar of Data
• Order of Operations
• Time Complexity (Big O Notation)
• Functional Programming (Mapping)
• Building a Pipeline
• Troubleshooting
• Performance

Parallel Computing in Python | Single Machine (120 min)

• Paradigms
• Templates
• Multiprocessing, Polars, Dask

Lunch and Learn

• Team Project Check In

Team Presentation Training (120 min)

• Presentation Goals
• Clear Communication
• Primacy, Frequency, and Recency
• Body Language
• START Method
• Training

Day 5 | Friday, March 8, 2024

Team Presentations | EDA (120 min)

• Capstone Presentations and Feedback.

Module Wrap Up (30 min)

• Closing
• Architecting Data Product Development based on EDA.
• Interim Period
• Next Steps