PDS II (IDS 541)

Practical Data Science II is a flipped-classroom, exercise and project-focused course. Building on the computational thinking skills developed in Practical Data Science I, this course introduces students to a range of computational inquiry methods, including network analysis, geospatial analysis, advanced plotting, and natural language processing (NLP). Throughout, the focus will be on developing hands-on experience implementing these methods with messy real-world data to ensure students are prepared to deploy these tools to answer the questions they care about. Requirements: Practical Data Science I.

Syllabus

A preliminary syllabus can be found here.

Office Hours

Adriane: Signup with this link

Nick (Zoom or in Gross 231): Thursday 9 am - 10:00 am. Please email me in advance if you plan to attend. I’ll usually be there regardless, but knowing people are coming is useful if conflicts arise.

Diego (Zoom or Gross Hall 2nd Floor, 230K): Monday 12:00 - 1:00 pm

Meron (Zoom or Gross Hall 2nd Floor, 230N): Wednesday 12:00 - 1:00 pm.

Books

• Python for Geographic Data Analysis (PGDA)

• Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 3rd Edition . Available online via Duke Library for Duke students here.

Class Schedule (Preliminary)

Date	Topic	Do Before Class	In-Class Exercise
Mon Jan 11	Pandas: Reshaping	Tidy Data Format: the goal of reshaping Reshaping Pandas reshaping (with pics!)
Wed Jan 13	Speed and Performance in Python Pandas: Categoricals	Understanding Performance Solving Performance Problems
Mon Jan 18	MLK DAY NO CLASS
Wed Jan 20	Big Data: What is it, how do I work with it?	What is Big Data? Strategies for Big Data Download the dataset linked at the top of the linked exercise before class. Parquet Format
Mon Jan 25	SNOW
Wed Jan 27	Parallelism Distributed Computing	conda Environments Parallel Computing Distributed Computing with dask (Note reading includes a 45 minute video to watch)
Mon Feb 1	SNOW AGAIN
Wed Feb 3		More Dask
Mon Feb 8	-GIS: Vector Data	What is GIS? Installing Geopandas Intro to Geopandas
Wed Feb 10	-GIS: Vector Data	Mapping
Mon Feb 15	-GIS: Vector Data	Projections Projections and Geopandas GIS Data Formats
Wed Feb 17	-GIS: Vector Data	Spatial Joins Set Operations (Yes, this is just the docs. But I wrote a lot of them so it’s not cheating!)
Mon Feb 22	WORK DAY
Wed Feb 24	GIS: Rasters	PGDA Chpt 7 through 7.2 (x-array)
Mon Mar 1	GIS: Rasters	PGDA 7.3 through “Creating a raster mosaic by merging datasets” (stop before Raster to vector conversion) PGDA 7.5
Wed Mar 3	GIS: Rasters	Finish PGDA 7.3 (Creating a raster mosaic sub section to the end) PGDA 7.4 Reproject Match
Mon Mar 8	NO CLASS	SPRING BREAK
Wed Mar 10	NO CLASS	SPRING BREAK
Mon Mar 15	Data Science Questions	Solving Probs with Data Solving Right Problem (include second page with solving wrong problem example)
Wed Mar 17	Data Science Questions	Answering Questions (include inference/prediction comparison)
Mon Mar 22	Machine Learning	Géron, Chpt 1: The Machine Learning Landscape (stop before “Batch and Online Learning,” then read the “Testing and Validating” section) Géron, Chpt 2: End-to-End Machine Learning Project
Wed Mar 24	Machine Learning	Pandas, Numpy, and Patsy Spend more time with Géron 1 and 2
Mon Mar 29	Machine Learning	Chpt 9 Chpt 10 Chpt 11 ONLY FIRST READING, not Fairness
Wed Mar 31	Git and github	Git and Github Create an ssh key and register with ssh-agent (you don’t need to create a passphrase) If you don’t have a github account, make one. Register a passkey or at least two factor authentication. Add your ssh key to your github account Visualize Git Branches
Mon Apr 5	Git and github	Defensive Programming: from first reading through Iceberg Principle Workflow Management Getting Help Code Reviews
Wed Apr 7	Network Data	Network Analysis, Chpt 1 and 2
Mon Apr 12	Network Data	Intro to graph-tool
Wed Apr 14	LAST CLASS