Об этом курсе

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Курс 2 из 5 в программе
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Английский
Субтитры: Английский

Чему вы научитесь

  • 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.

Сертификат, ссылками на который можно делиться с другими людьми
Получите сертификат по завершении
100% онлайн
Начните сейчас и учитесь по собственному графику.
Курс 2 из 5 в программе
Гибкие сроки
Назначьте сроки сдачи в соответствии со своим графиком.
Начальный уровень
Прибл. 11 часов на выполнение
Английский
Субтитры: Английский

от партнера

Логотип Калифорнийский университет в Девисе

Калифорнийский университет в Девисе

Программа курса: что вы изучите

Неделя
1

Неделя 1

3 ч. на завершение

Getting Started and Big Data Opportunities

3 ч. на завершение
10 видео ((всего 94 мин.)), 3 материалов для самостоятельного изучения, 1 тест
10 видео
Course Introduction6мин
Big Data Overview2мин
What is "Big Data"?14мин
Digital Footprint5мин
Political Data-fusion and No-Sampling (Part 1)14мин
Political Data-fusion and No-Sampling (Part 2)3мин
Real-time11мин
Machine Learning5мин
Machine Learning Recommender Systems11мин
3 материала для самостоятельного изучения
About UCCSS10мин
A Note From UC Davis10мин
Optional/Complementary10мин
1 практическое упражнение
Module 1 Quiz30мин
Неделя
2

Неделя 2

3 ч. на завершение

Big Data Limitations

3 ч. на завершение
8 видео ((всего 52 мин.)), 1 материал для самостоятельного изучения, 3 тестов
8 видео
Big Data Limitations2мин
Footprint ≠ Representativeness10мин
Data ≠ Reality6мин
Meaning ≠ Meaningful4мин
Discrimination ≠ Personalization8мин
Correlation ≠ Causation6мин
Past ≠ Future10мин
1 материал для самостоятельного изучения
Welcome to Peer Review Assignments!10мин
2 практических упражнения
Natural Language Processing (NLP) Assignment Task5мин
Module 2 Quiz30мин
Неделя
3

Неделя 3

3 ч. на завершение

Artificial Intelligence

3 ч. на завершение
15 видео ((всего 105 мин.)), 1 материал для самостоятельного изучения, 1 тест
15 видео
A Short History of AI9мин
State of the Art5мин
The Most Intelligent Gamer4мин
Search and Robotics7мин
Vision and Machine Learning6мин
AI Challenges3мин
Moral Frames7мин
Predictions From Morals6мин
Moral Brain Signatures6мин
Computational fMRI11мин
(A Personal) History of Dialogue Systems6мин
The Art of Dialogue10мин
Making Conversations10мин
AI Telling Stories7мин
1 материал для самостоятельного изучения
Optional/Complementary10мин
1 практическое упражнение
Module 3 Quiz30мин
Неделя
4

Неделя 4

2 ч. на завершение

Research Ethics

2 ч. на завершение
13 видео ((всего 105 мин.)), 1 материал для самостоятельного изучения, 1 тест
13 видео
Origins: Unethical Medical Research8мин
Unethical Social Research10мин
Taking Responsibility12мин
The Common Rule8мин
Ethical Computational Social Science10мин
Concerns of an AI Pioneer5мин
Walker on Ethics10мин
Shelton on Ethics7мин
Language Acquisition (Complementary)6мин
Modeling Framework (Complementary)9мин
Computational Model (Complementary)6мин
Lessons Learned (Complementary)6мин
1 материал для самостоятельного изучения
Slaughterbots10мин
1 практическое упражнение
Module 4 Quiz30мин

Рецензии

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Специализация Computational Social Science: общие сведения

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

Часто задаваемые вопросы

  • 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.
  • Записавшись на курс, вы получите доступ ко всем курсам в специализации, а также возможность получить сертификат о его прохождении. После успешного прохождения курса на странице ваших достижений появится электронный сертификат. Оттуда его можно распечатать или прикрепить к профилю LinkedIn. Просто ознакомиться с содержанием курса можно бесплатно.

  • Когда вы оформите подписку, начнется семидневный бесплатный пробный период, в течение которого подписку можно отменить без штрафа. По истечении этого срока вы не сможете вернуть средства, но сможете отменить подписку в любой момент. Ознакомьтесь с нашей политикой возврата средств.

  • Да, Coursera предоставляет финансовую помощь учащимся, которые не могут оплатить обучение. Чтобы подать заявление, перейдите по ссылке "Финансовая помощь" слева под кнопкой "Зарегистрироваться". Заполните форму заявления. Если его примут, вы получите уведомление. Обратите внимание: этот шаг необходимо выполнить для каждого курса специализации, в том числе для дипломного проекта. Подробнее

  • 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.

  • Этот курс не приравнивается к зачету в университетах, однако некоторые вузы принимают сертификаты на свое усмотрение. Дополнительную информацию уточняйте в своем деканате. Онлайн-дипломы и сертификаты Mastertrack™ от Coursera позволяют получить зачеты.

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