Prerequisites

To participate in the summer school students need to master the basics in Linear Algebra and Analysis and have an advanced level in Python programming.

Preparatory material to reach a basic level in Machine Learning will be distributed beforehand. It is expected that the students prepare themselves with these documents for the summer school.

English Level B2 is compulsory.

Program structure

During the mornings, you will receive inputs and lectures, followed by structured exercises in a lab. In the afternoon you will work in teams on a challenge /task as project work.

At the end of week two (part ZHAW SoE), the teams will present their solutions to a jury.

Topical and touristic excursion complement the academic curriculum.

Program (tbc)

DOWNLOAD THE DRAFT SYLLABUS OF THE CURRICULUM

Week 1 at ZHAW: Data Engineering, lecturer: Dr. Jonathan Fürst

  Sun 30.6 Mon 1.7 Tue 2.7 Wen 3.7 Thu 4.7 Fri 5.7 Sat 6.7 Sun 7.7.
Morning Arrival US guests Lecture: Data Science-Process and Elements of Exploratory Data Analysis, Lab: Development Environment and The Python Data Science stack Lecture: Data Curation, Data Integration, Data Extraction, Data Wrangling and Exploration, Record Linkage, Lab: Data Extraction, Data Wrangling and Exploration Lecture: Pre-processing and Feature Extraction, Unstructured Data: Text and Images, Lab: tbd Lecture: Data Annotation and Scaling, Data Centric AI, Big Data, Lab: Data Annotation and Parallel data processing with Dask Topical excursion to a company dealing with large data sets (full day) Excursion Rhine Fall & Alpstein Mountain Range incl overnight stay Short hike and transfer back to Winterthur
Afternoon Arrival US guests and welcome barbecue Data Science Project: Introduction and Selection of Project Data Science Project: Project Work, Data Management, Data Report Data Science Project: Project work in groups and individual supervision Project checkpoint presentations and discussions 4 pm: Frack parade and night of technology at ZHAW SoE Excursion Rhine Fall & Alpstein Mountain Range incl overnight stay Free time

Week 2: Machine Learning (ZHAW), lecturers Dr. Manuel Dömer and Dr. Andreas Weiler

  Mon 8.7 Tue 9.7 Wen 10.7 Thu 11.7 Fri 12.7 Sat 13.7
Morning Lecture: Regression, Classification, Evaluation, Lab: Supervised Learning using the Python Stack Lecture: Clustering, Anomaly Detection, Evaluation, Lab: Unsupervised Learning using the Python Stack Lecture: Association rules- recommender systems, Lab: Recommender Systems using the Python Stack Data Science Project: Project work in groups and individual supervision Full day excursion to Berne incl visit of the federal parliament building Transfer to Allendale, Michigan, USA for second part of summer school on the GVSU campus
Afternoon Data Science Project: Project work in groups and individual supervision Data Science Project: Project work in groups and individual supervision Data Science Project: Project work in groups and individual supervision Data Science Project: Project presentations and discussions, evaluation, celebration and reception Full day excursion to Berne incl visit of the federal parliament building Transfer to Allendale, Michigan, USA for second part of summer school on the GVSU campus

Week 3: Deep Learning (GVSU), lecturer Dr. Denton Bobeldyk

  Mon 15.7 Tue 16.7 Wen 17.7 Thu 18.7 Fri 19.7 Sat 20.7
Morning Lecture: Convolutional Neural Networks, Deep learning evaluation methods, Group Lab Lecture: Deep learning dataset management and augmentation, Group Lab Lecture: Deep learning evaluation methods, Autoencoders & GANs, Group Lab Lecture: Introduction to Group Deep Learning, Project Lab presentation preparation Excursion to Sleeping Bear Dunes Tour historic Fort Michilimackinac and ferry to Mackinac Island
Afternoon Group Deep Learning Project and Morning Lecture Review Kahoot Group Deep Learning Project and Morning Lecture Review Kahoot Group Deep Learning Project and Morning Lecture Review Kahoot Project presentations, discussions, evaluation and celebration Catamaran Ride and overnight stay in Mackinaw City, MI Transfer back to Allendale

Week 4: Data Visualization (GVSU), lecturer Dr. Jonathan Leidig

  Mon 22.7 Tue 23.7 Wen 124.7 Thu 25.7 Fri 26.7 Sat 27.7
Morning Lecture: Intro to visualization and design principles, Exercises: Human cognition and UX concepts Lecture: Descriptive chart design, persona & task modeling, Exercises: Gestalt psychology, user/persona modeling, task modeling Lecture: Multi-dimensional datasets, overviews, navigation and exploration with large datasets, Lab: Group project Lecture: Tree, network, spatial analysis, persuasion, Lab: Group project Excursion to Chicago Free Time in Chicago and closure of summer school
Afternoon Visual analytics projects: Exploratory data analysis lab with Tableau Visual analytics projects: Statistical charts lab with programming librarie Visual analytics projects: Visualization design with D3, Gephi, GIS, or Google Cloud Platform packages Visual analytics projects: Project presentations, evaluation, celebration Free time in Chicago and overnight stay at Chicago Hostel-International