ICME Summer Workshops 2021 | Fundamentals of Data Science
2021 Summer Workshops will be online via Zoom Aug 2-20
ICME’s 6th 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. Attendees completing four or more workshops can earn a Stanford ICME Fundamentals of Data Science Summer Workshops Certificate of Completion.
New this year, the series offers:
- New and Intermediate workshops such as Data Privacy and Ethics, Intermediate Topics in Machine Learning & Deep Learning, and Deep Learning for Natural Language Processing - Part II.
- Thirteen workshops over three weeks, from August 2-20, 2021.
- Half-day workshops (from either 8-11 am or 1-4 pm Pacific time) spread over two days.
Linear Algebra [closed]
8-11 am PDT
Linear algebra forms the foundation of many algorithms in computational mathematics and engineering, and data science is no exception.
Introduction to Statistics [closed]
1-4 pm PDT
This workshop will help you to develop the skills you need to analyze data and to communicate your findings.
Introduction to Python [closed]
8-11 am PDT
Introduction to Python will focus on scientific computing, data science and machine learning.
Introduction to Programming in R [closed]
1-4 pm PDT
This workshop is recommended for those who want to learn the basics of R programming in statistics, science, or engineering.
Introduction to Mathematical Optimization [closed]
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.
Introduction to Machine Learning [closed]
8-11 am PDT
This workshop presents the basics behind understanding and using modern machine learning algorithms.
Introduction to Deep Learning [closed]
8-11 am PDT
In this workshop we will cover the fundamentals of deep learning for the beginner.
Data Privacy and Ethics [closed]
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.
Deep Learning for Natural Language Processing - Part I [closed]
8-11 am PDT
This workshop will focus on practical applications and considerations of applying deep learning to Natural language processing (NLP).
Data Vizualization in Tableau [closed]
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 [closed]
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.
Intermediate Topics in Machine Learning and Deep Learning [closed]
8-11 am 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.
Deep Learning for Natural Language Processing - Part II [closed]
8-11 am PDT
This workshop will introduce common practical use cases where natural language processing (NLP) models are applied using the latest advances in deep learning (e.g. Transformer-based models such as BERT).