Case Studies and Life Sciences Applications

As the demand for data science and machine learning expertise in the life sciences sector grows, this course offers an opportunity to engage with industry experts. Participants will explore the unique challenges and opportunities in the life sciences context, learning how to apply data science for impactful solutions.

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At a glance

Qualification:

Kursbestätigung "Case Studies and Life Sciences Applications" (2 ECTS)

Start:

30.08.2024 09:00

Duration:

2 Tage

Location:

ZHAW Zürich, Building ZL, Lagerstrasse 41, 8004 Zürich (Show on Google Maps)
close to Zürich main station

Language of instruction:

English

Course dates:

30.08.2024, 09:00 - 17:00

29.11.2024, 09:00 - 17:00

Content

This course adopts a comprehensive approach to building machine learning solutions within a corporate setting. Attendees will receive a broad view of the data science pipeline, delve into advanced topics, and draw inspiration from life science application case studies. The programme spans two full-day sessions.

Day 1: The first day focuses on the advances data science can bring to life science applications. We will examine specific challenges and solutions relevant to the life sciences and gain insights from industry practitioners' presentations.

Day 2: The second day delves into advanced topics in machine learning operations (MLOps) and digital ethics.

Machine Learning Operations

Defining Machine Learning Operations best practices around data, code and model has become a key component in becoming data-driven organizations. In this introductory session participants will learn the essentials of MLOps and its significance.

Instructor: Dr. Nitin Kumar

Digital Ethics by Design

This session addresses how to make digital transformations and technologies ethical and trustworthy. Participants will overview current challenges in digital ethics and strategies for integrating ethics into digital transformation designs.

Instructor: Deepak Bansal

CAS in Digital Life Sciences

This module is part of the CAS in Digital Life Sciences continuing education programme. More information here: CAS in Digital Life Sciences