Qualitative Methods for Quantitative People (with GenAI) is a course designed for individuals with a strong quantitative background who want to explore the power of qualitative analysis through the lens of Generative AI (GenAI). This course introduces foundational concepts of qualitative analysis, guiding learners through the process of interpreting concepts, experiences, and nuanced data. It emphasizes how qualitative insights complement quantitative methods, enabling more comprehensive decision-making.
Schenken Sie Ihrer Karriere Coursera Plus mit einem Rabatt von $160 , der jährlich abgerechnet wird. Sparen Sie heute.
Empfohlene Erfahrung
Was Sie lernen werden
Differentiate and apply qualitative and quantitative analysis in decision-making.
Use LLMs to enhance qualitative analysis, streamline data extraction, and compare with traditional search engines.
Develop multi-modal communication and assess the impact of context on decision-making.
Kompetenzen, die Sie erwerben
- Kategorie: Large Language Models
- Kategorie: Data Visualization
- Kategorie: Decision making
- Kategorie: Project Management
- Kategorie: Decision Making
- Kategorie: Qualitative Analysis
Wichtige Details
Zu Ihrem LinkedIn-Profil hinzufügen
September 2024
6 Aufgaben
Erfahren Sie, wie Mitarbeiter führender Unternehmen gefragte Kompetenzen erwerben.
Erwerben Sie ein Karrierezertifikat.
Fügen Sie diese Qualifikation zur Ihrem LinkedIn-Profil oder Ihrem Lebenslauf hinzu.
Teilen Sie es in den sozialen Medien und in Ihrer Leistungsbeurteilung.
In diesem Kurs gibt es 7 Module
We explore the integration of qualitative and quantitative analysis with a focus on how large language models (LLMs) can enhance various aspects of decision-making, resource allocation, and data-driven processes. Starting with an understanding of qualitative analysis for those accustomed to quantitative methods, we move through the creation and maintenance of "living documents," the incorporation of qualitative data into decision-making, and the critical role of time management in resource allocation. We conclude with a thought experiment that challenges us to consider different perspectives in decision-making. Throughout, we emphasize the balance between human judgment and AI assistance, ensuring that our strategies are both efficient and informed by diverse insights. By the end of this course, learners will be able to effectively integrate qualitative and quantitative data, utilizing large language models (LLMs) to enhance decision-making and resource allocation while maintaining a balanced approach between human judgment and AI assistance.
Das ist alles enthalten
1 Video
We explore the intersection of qualitative and quantitative analysis, particularly focusing on how large language models (LLMs) can enhance our ability to engage with qualitative data. We discuss the nuances of qualitative analysis, emphasizing its importance in understanding the 'why' and 'how' behind data. By contrasting it with quantitative methods, we highlight how LLMs provide us with new tools to analyze, interpret, and communicate complex qualitative insights efficiently.
Das ist alles enthalten
1 Video1 Aufgabe1 Diskussionsthema
We delve into the concept of "Living Documents," focusing on how we can use large language models (LLMs) to create, interact with, and continually refine our data-driven narratives. We explore how LLMs differ from traditional search engines, emphasizing their ability to predict and generate content rather than simply retrieve information. By guiding us through practical applications such as coding, knowledge curation, and query optimization, we aim to demonstrate how LLMs can enhance our productivity and creativity, transforming static documents into dynamic, evolving resources that adapt to our needs.
Das ist alles enthalten
1 Video1 Aufgabe1 Diskussionsthema
We explore how qualitative data, such as survey responses and human-in-the-loop interactions, can be systematically analyzed and synthesized to inform decisions that go beyond numerical insights. By examining case studies and applying practical tools like sentiment analysis and peer review, we aim to develop a nuanced understanding of how to balance quantitative metrics with qualitative feedback to achieve more holistic and effective decision-making outcomes.
Das ist alles enthalten
1 Video1 Aufgabe1 Diskussionsthema
We explore strategies for efficiently managing team dynamics, particularly in large and dynamic groups, where balancing skills, interests, and efforts is key. By leveraging large language models (LLMs), we can streamline tasks such as tracking progress, reviewing documents, and matching team members with appropriate roles. We also address the challenges of bias in data collection and interpretation, highlighting the need for careful, human oversight to ensure fairness and accuracy in our decision-making processes.
Das ist alles enthalten
1 Video1 Aufgabe1 Diskussionsthema
We examine how different perspectives can influence our decisions in daily activities, business, and life planning. By dissecting how we seek advice and make choices, we aim to understand the biases and influences that shape our decisions. Through interactive examples, we challenge ourselves to consider multiple viewpoints and recognize the complexity involved in even seemingly simple decisions.
Das ist alles enthalten
1 Video1 Aufgabe1 Diskussionsthema
As we conclude this module, it's time to apply what we've learned. The following test and project will challenge your understanding of the key concepts and your ability to integrate them into practical scenarios.
Das ist alles enthalten
1 Video1 Aufgabe1 peer review
Dozent
Empfohlen, wenn Sie sich für Data Analysis interessieren
University of California, Davis
University of Colorado System
Coursera Project Network
Coursera Instructor Network
Warum entscheiden sich Menschen für Coursera für ihre Karriere?
Neue Karrieremöglichkeiten mit Coursera Plus
Unbegrenzter Zugang zu über 7.000 erstklassigen Kursen, praktischen Projekten und Zertifikatsprogrammen, die Sie auf den Beruf vorbereiten – alles in Ihrem Abonnement enthalten
Bringen Sie Ihre Karriere mit einem Online-Abschluss voran.
Erwerben Sie einen Abschluss von erstklassigen Universitäten – 100 % online
Schließen Sie sich mehr als 3.400 Unternehmen in aller Welt an, die sich für Coursera for Business entschieden haben.
Schulen Sie Ihre Mitarbeiter*innen, um sich in der digitalen Wirtschaft zu behaupten.
Häufig gestellte Fragen
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
You will be eligible for a full refund until two weeks after your payment date, or (for courses that have just launched) until two weeks after the first session of the course begins, whichever is later. You cannot receive a refund once you’ve earned a Course Certificate, even if you complete the course within the two-week refund period. See our full refund policy.