À propos de ce cours

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Sous-titres : Anglais

Ce que vous allez apprendre

  • 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.

Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Niveau débutant
Approx. 11 heures pour terminer
Sous-titres : Anglais

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Logo Université de Californie à Davis

Université de Californie à Davis

Programme du cours : ce que vous apprendrez dans ce cours


Semaine 1

3 heures pour terminer

Getting Started and Big Data Opportunities

3 heures pour terminer
10 vidéos (Total 94 min), 3 lectures, 1 quiz
10 vidéos
Course Introduction6 min
Big Data Overview2 min
What is "Big Data"?14 min
Digital Footprint5 min
Political Data-fusion and No-Sampling (Part 1)14 min
Political Data-fusion and No-Sampling (Part 2)3 min
Real-time11 min
Machine Learning5 min
Machine Learning Recommender Systems11 min
3 lectures
About UCCSS10 min
A Note From UC Davis10 min
Optional/Complementary10 min
1 exercice pour s'entraîner
Module 1 Quiz30 min

Semaine 2

3 heures pour terminer

Big Data Limitations

3 heures pour terminer
8 vidéos (Total 52 min), 1 lecture, 3 quiz
8 vidéos
Big Data Limitations2 min
Footprint ≠ Representativeness10 min
Data ≠ Reality6 min
Meaning ≠ Meaningful4 min
Discrimination ≠ Personalization8 min
Correlation ≠ Causation6 min
Past ≠ Future10 min
1 lecture
Welcome to Peer Review Assignments!10 min
2 exercices pour s'entraîner
Natural Language Processing (NLP) Assignment Task5 min
Module 2 Quiz30 min

Semaine 3

3 heures pour terminer

Artificial Intelligence

3 heures pour terminer
15 vidéos (Total 105 min), 1 lecture, 1 quiz
15 vidéos
A Short History of AI9 min
State of the Art5 min
The Most Intelligent Gamer4 min
Search and Robotics7 min
Vision and Machine Learning6 min
AI Challenges3 min
Moral Frames7 min
Predictions From Morals6 min
Moral Brain Signatures6 min
Computational fMRI11 min
(A Personal) History of Dialogue Systems6 min
The Art of Dialogue10 min
Making Conversations10 min
AI Telling Stories7 min
1 lecture
Optional/Complementary10 min
1 exercice pour s'entraîner
Module 3 Quiz30 min

Semaine 4

2 heures pour terminer

Research Ethics

2 heures pour terminer
13 vidéos (Total 105 min), 1 lecture, 1 quiz
13 vidéos
Origins: Unethical Medical Research8 min
Unethical Social Research10 min
Taking Responsibility12 min
The Common Rule8 min
Ethical Computational Social Science10 min
Concerns of an AI Pioneer5 min
Walker on Ethics10 min
Shelton on Ethics7 min
Language Acquisition (Complementary)6 min
Modeling Framework (Complementary)9 min
Computational Model (Complementary)6 min
Lessons Learned (Complementary)6 min
1 lecture
Slaughterbots10 min
1 exercice pour s'entraîner
Module 4 Quiz30 min



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À propos du Spécialisation 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

Foire Aux Questions

  • L’accès à des vidéos de cours et des devoirs dépend de votre type d’inscription. Si vous suivez un cours en mode auditeur libre, vous pourrez voir la plupart des contenus de cours gratuitement. Pour accéder aux devoirs notés et obtenir un certificat, vous devrez acheter une expérience de certificat, pendant ou après avoir assister au cours en tant qu’auditeur libre. Si vous ne visualisez pas l’option auditeur libre :

    • Il est possible que le cours ne propose pas d’option auditeur libre. Vous pouvez en revanche accéder à un essai gratuit ou faire une demande d'aide financière.
    • Le cours propose peut-être « Cours complet, aucun certificat » à la place. Cette option vous permet de voir tous les contenus de cours, de soumettre les évaluations requises et d'obtenir une note finale. Cependant, vous ne pourrez pas acheter une expérience de certificat.
  • Lorsque vous vous inscrivez au cours, vous bénéficiez d'un accès à tous les cours de la Spécialisation, et vous obtenez un Certificat lorsque vous avez réussi. Votre Certificat électronique est alors ajouté à votre page Accomplissements. À partir de cette page, vous pouvez imprimer votre Certificat ou l'ajouter à votre profil LinkedIn. Si vous souhaitez seulement lire et visualiser le contenu du cours, vous pouvez accéder gratuitement au cours en tant qu'auditeur libre.

  • Si vous vous abonnez, vous bénéficiez d'une période d'essai gratuite de 7 jours, durant laquelle vous pouvez annuler votre abonnement sans pénalité. Ensuite, nous n'accordons plus de remboursements, mais vous pouvez annuler votre abonnement à tout instant. Consultez notre politique de remboursement complète.

  • Oui, Coursera offre une Aide Financière aux étudiants qui n'ont pas les moyens d'acquitter les frais. Demandez-la en cliquant sur le lien Aide Financière sous le bouton S'inscrire situé à gauche. Vous devrez remplir un formulaire de demande et vous serez averti(e) si elle est acceptée. Vous devrez répéter cette procédure pour chaque cours de la Spécialisation, y compris pour le Projet Final. En savoir plus.

  • 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.

  • Ce Cours n'est pas associé à des crédits universitaires, mais certaines universités peuvent décider d'accepter des Certificats de Cours pour des crédits. Vérifiez-le auprès de votre établissement pour en savoir plus. Les Diplômes en ligne et les Certificats Mastertrack™ sur Coursera apportent la possibilité d'obtenir des crédits universitaires.

D'autres questions ? Visitez le Centre d'Aide pour les Etudiants.