ICME Summer Workshops 2022 | Fundamentals of Data Science
2022 Summer Workshops will be online via Zoom Aug 1 - Aug 19

ICME’s annual Summer Workshop Series will offer a variety of virtual data science and AI courses, taught live via Zoom by world renowned Stanford faculty and Stanford-affiliated instructors. The series is open to the general public worldwide. Discounts are offered to students, staff, and faculty from all schools as well as to ICME industry partners.
The series offers:
- Intermediate workshops such as Data Privacy and Ethics, and Intermediate Topics in Machine Learning & Deep Learning.
- Fourteen workshops over three weeks, from August 1-19, 2022.
- Half-day workshops (from either 8-11 am or 1-4 pm Pacific time) spread over two days.

Discounts are available for all University faculty, staff, and students. Please contact icme-contact@stanford.edu for directions on how to obtain your promo code.
Registration is now closed.

Linear Algebra
8-11 am PDT
Linear algebra forms the foundation of many algorithms in computational mathematics and engineering, and data science is no exception. Read More

Introduction to Statistics
1-4 pm PDT
This workshop will help you to develop the skills you need to analyze data and to communicate your findings. Read More

Introduction to Python
8-11 am PDT
Introduction to Python will focus on scientific computing, data science and machine learning. Read More

Introduction to Programming in R
1-4 pm PDT
This workshop is recommended for those who want to learn the basics of R programming in statistics, science, or engineering. Read More

Introduction to Mathematical Optimization
1-4 pm PDT
Mathematical optimization underpins many applications in science and engineering, as it provides a set of formal tools to compute the ‘best’ action, design, control, or model from a set of possibilities. Read More

Introduction to Machine Learning
8-11 am PDT
This workshop presents the basics behind understanding and using modern machine learning algorithms.

Introduction to Deep Learning
1-4 pm PDT
In this workshop we will cover the fundamentals of deep learning for the beginner.

Data Visualization in Tableau
8-11 am PDT
This workshop will cover best practices for telling compelling stories via data visualization, with demos and hands-on exercises in Tableau.

Introduction to High Performance Computing
1-4 pm PDT
This workshop explores the features of three key parallel programming approaches, OpenMP, CUDA, and MPI; it will explain their underlying philosophy and how they are adapted to different computer architectures.

Deep Learning for Natural Language Processing
8-11 am PDT
This workshop will focus on practical applications and considerations of applying deep learning to Natural language processing (NLP).

Data Privacy and Ethics
1-4 pm PDT
This workshop engages with difficult challenges in the modern practice of data science and the design of data products. We will begin by discussing the promises and perils of mining digital exhaust: location, transaction, social media, and other data types that are increasingly recorded and accessible within digital platforms.

Intermediate Topics in Machine Learning and Deep Learning
1-4 pm PDT
Through a series of rapid surveys, including guest lectures, we will present an overview of recent topics in deep learning and machine learning with particular relevance for practitioners.