Über diesen Kurs

89,787 kürzliche Aufrufe
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100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
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Stufe „Anfänger“
Ca. 11 Stunden zum Abschließen
Englisch
Untertitel: Englisch

Was Sie lernen werden

  • Define and discuss big data opportunities and limitations.

  • Work with IBM Watson and analyze a personality through Natural Language Programming (NLP).

  • Examine how AI is used through case studies.

  • Examine and discuss the roles ethics play in AI and big data.

Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Stufe „Anfänger“
Ca. 11 Stunden zum Abschließen
Englisch
Untertitel: Englisch

von

University of California, Davis-Logo

University of California, Davis

Lehrplan - Was Sie in diesem Kurs lernen werden

Woche
1

Woche 1

3 Stunden zum Abschließen

Getting Started and Big Data Opportunities

3 Stunden zum Abschließen
10 Videos (Gesamt 94 min), 3 Lektüren, 1 Quiz
10 Videos
Course Introduction6m
Big Data Overview2m
What is "Big Data"?14m
Digital Footprint5m
Political Data-fusion and No-Sampling (Part 1)14m
Political Data-fusion and No-Sampling (Part 2)3m
Real-time11m
Machine Learning5m
Machine Learning Recommender Systems11m
3 Lektüren
About UCCSS10m
A Note From UC Davis10m
Optional/Complementary10m
1 praktische Übung
Module 1 Quiz30m
Woche
2

Woche 2

3 Stunden zum Abschließen

Big Data Limitations

3 Stunden zum Abschließen
8 Videos (Gesamt 52 min), 1 Lektüre, 3 Quiz
8 Videos
Big Data Limitations2m
Footprint ≠ Representativeness10m
Data ≠ Reality6m
Meaning ≠ Meaningful4m
Discrimination ≠ Personalization8m
Correlation ≠ Causation6m
Past ≠ Future10m
1 Lektüre
Welcome to Peer Review Assignments!10m
2 praktische Übungen
Natural Language Processing (NLP) Assignment Task5m
Module 2 Quiz30m
Woche
3

Woche 3

3 Stunden zum Abschließen

Artificial Intelligence

3 Stunden zum Abschließen
15 Videos (Gesamt 105 min), 1 Lektüre, 1 Quiz
15 Videos
A Short History of AI9m
State of the Art5m
The Most Intelligent Gamer4m
Search and Robotics7m
Vision and Machine Learning6m
AI Challenges3m
Moral Frames7m
Predictions From Morals6m
Moral Brain Signatures6m
Computational fMRI11m
(A Personal) History of Dialogue Systems6m
The Art of Dialogue10m
Making Conversations10m
AI Telling Stories7m
1 Lektüre
Optional/Complementary10m
1 praktische Übung
Module 3 Quiz30m
Woche
4

Woche 4

2 Stunden zum Abschließen

Research Ethics

2 Stunden zum Abschließen
13 Videos (Gesamt 105 min), 1 Lektüre, 1 Quiz
13 Videos
Origins: Unethical Medical Research8m
Unethical Social Research10m
Taking Responsibility12m
The Common Rule8m
Ethical Computational Social Science10m
Concerns of an AI Pioneer5m
Walker on Ethics10m
Shelton on Ethics7m
Language Acquisition (Complementary)6m
Modeling Framework (Complementary)9m
Computational Model (Complementary)6m
Lessons Learned (Complementary)6m
1 Lektüre
Slaughterbots10m
1 praktische Übung
Module 4 Quiz30m

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Über den Spezialisierung Computational Social Science

For more information please view the Computational Social Science Trailer Digital technology has not only revolutionized society, but also the way we can study it. Currently, this is taken advantage of by the most valuable companies in Silicon Valley, the most powerful governmental agencies, and the most influential social movements. What they have in common is that they use computational tools to understand, and ultimately influence human behavior and social dynamics. An increasing part of human interaction leaves a massive digital footprint behind. Studying it allows us to gain unprecedented insights into what society is and how it works, including its intricate social networks that had long been obscure. Computational power allows us to detect hidden patterns through analytical tools like machine learning and to natural language processing. Finally, computer simulations enable us to explore hypothetical situations that may not even exist in reality, but that we would like to exist: a better world. This specialization serves as a multidisciplinary, multi-perspective, and multi-method guide on how to better understand society and human behavior with modern research tools. This specialization gives you easy access to some of the exciting new possibilities of how to study society and human behavior. It is the first online specialization collectively taught by Professors from all 10 University of California campuses....
Computational Social Science

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 enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. 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.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

  • These are some of the reflections shared by students who have worked through the content of the Specialization on Computational Social Science:

    • "Highly enjoyable and most importantly, giving me exceptionally important skills to fulfill my job requirements at a new position in Munich. You may be interested to know the impact of your course on salary and in my case, the knowledge and certification gained adds about another Euro 20.000 on the annual salary (taking it to about Euro 120.000 p.a.)."

    • "My overall impression of this was: I can't wait to use this for other stuff!!"

    • "Best course I have taken. I wish more online courses structured like this would be offered."

    • "The fact that these tools are so easily usable and attainable is incredible in my mind. Not only do we have access to them like we have access to things like Facebook and Twitter, but they're FREE."

    • "I absolutely think that these tools could be used in my future jobs, or even as a personal reflection. If you scrape and analyze the comments/reactions that your business gets on Youtube, Twitter, Instagram, etc., what does their language use say about how they interact with your brand — or what your brand brings out in them?"

    • "Wow, this is cool and fun stuff. Even though I may not pursue anything social-science related in the near future, it is still nice to learn and get to experience all of these tools that computational social science offers and benefits in all kinds of careers and fields of study."

    • "I particularly enjoyed the web-scraping for some reason. It feels very advanced although its very easy. ...It seems to be a very fast and efficient way of grabbing data."

    • "I enjoyed playing around with machine learning! ...It was also amazing to me how quickly it was able to grasp and learn our input in seconds. It makes me wonder how much more technology will advance in these next few years... It's scary but fascinating."

    • "The most interesting aspect was the fact that these tools are all free and online. In the past, only researchers at well-funded universities had access to programs like the ones we used in all of our labs. But now, even someone without much technical knowledge on complex software can use these tools."

    • "I am so surprised that these tools are available to anyone through a simple download, and even more so that they are very user friendly and easy to learn how to navigate. I plan on starting a clothing line company in the future and I think it will be really helpful for me to be able to analyze so much online data."

    • "As an Environmental Policy Analysis and Planning major, I was fascinated to learn that there is a feasible way to simulate policy implementation and impact multiple times within a short span of time."

    • "UCCSS has allowed me to feel more confident in my abilities with a computer and to better understand companies like Facebook or Twitter. ...these tools really are powerful but also dangerous. ...It allows powerful individuals to manipulate ideas."

    • "Throughout the course, the content was challenging, but when it was finally applied to the labs at the end of each module, it was really rewarding to see everything play out. It was even more rewarding when it made sense too! ... I'm really glad I took this course! It was definitely a challenge, but I'm glad I got to experience and learn about so many topics I never knew even existed."

    • "It was fun seeing the results of the code that I made, and I never thought that I would be doing something like this in my life. The results also showed me what the society would look like.... Social network analysis and web scraping could be the tools that I use in my future job as all the internship that I'm looking now all related to social media or digital media."

    • "My career aspiration is to be a digital marketing expert. These computational tools have enormous implications for the field."

    • "I really really loved that this class let me learn hands-on and gave me experience with tools that have real world application and combine STEM & social science. I think that a lot of these tools are useful far beyond homework activities."

    • "I did my MA in Social Work in India. I am trying to make a come-back in my field after a long career break. I had been hearing Big Data and Data Science everywhere and wondered if there is a link between these and Social Sciences. This specialization gave me needed answers and is helping me to gain very useful skills... Thank you so much for bringing this specialization. You are a very good instructor and made these courses are a smooth sail."

  • This Specialization on Computational Social Science is the result of a collective effort with contributions from Professors from all 10 campuses of the University of California. It is coordinated by Martin Hilbert, from UC Davis, and counts with lectures from:

    1) UC Berkeley: Joshua Blumenstock, Prof. iSchool; Stuart Russell, Professor of Computer Science and Engineering.

    2) UC Davis: Martin Hilbert, Prof., Dpt. of Communication & Seth Frey, Prof., Dpt. of Communication & Cynthia Gates, Director of the IRB.

    3) UC Irvine: Lisa Pearl, Prof. Cognitive Sciences.

    4) UC Los Angeles: PJ Lamberson, Assistant Prof. Communication Studies.

    5) UC Merced: Paul Smaldino, Prof. Cognitive and Information Sciences.

    6) UC Riverside: Christian Shelton, Prof. Computer Science.

    7) UC San Diego: James Fowler, Prof. Global Public Health and Political Science.

    8) UC San Francisco: Maria Glymour, Associate Prof. School of Medicine, Social Epidemiology & Biostatistics.

    9) UC Santa Barbara: René Weber, Prof. Dpt. of Communication & Media Neuroscience Lab (with Frederic Hopp).

    10) UC Santa Cruz: Marilyn Walker, Prof. Computer Science, Director, Computational Media.

Haben Sie weitere Fragen? Besuchen Sie das Hilfe-Center für Teiln..