This specialization is designed for post-graduate students interested in mastering social computing techniques to solve real-world problems. Through four in-depth courses, learners will explore key topics such as social network analysis, chatbot development, crowdsourcing, and AI performance optimization. You will learn to analyze social networks using R programming, create functional chatbots with AWS, and enhance AI models by leveraging crowdsourced data and machine learning techniques. By the end of the specialization, you will have practical experience applying advanced tools and methodologies across domains like social media analytics, conversational interfaces, and human-AI collaboration. This hands-on, industry-relevant learning path equips you with the skills needed to excel in social computing, artificial intelligence, and data-driven innovation.
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Social Computing Specialization
Master Applied Skills in Social Computing. Learn advanced techniques to analyze social networks, build chatbots, and enhance AI with crowdsourcing
Instructor: Ian McCulloh
Included with 
Recommended experience
Recommended experience
What you'll learn
Analyze social media dynamics using advanced techniques in social computing.
Explore graph theory and centrality measures in social network analysis.
Utilize crowdsourcing to enhance AI through reliable data annotation.
Build and optimize chatbots using AWS for diverse applications.
Overview
Skills you'll gain
- Research Design
- Data Collection
- Artificial Intelligence and Machine Learning (AI/ML)
- Applied Machine Learning
- Analytics
- Machine Learning Methods
- Machine Learning
- Social Sciences
- Statistical Modeling
- Sociology
- Network Analysis
- Statistical Analysis
- Graph Theory
- Data Ethics
- Trend Analysis
- Human Machine Interfaces
- Behavioral Economics
Tools you'll learn
What’s included
Add to your LinkedIn profile
Advance your subject-matter expertise
- Learn in-demand skills from university and industry experts
- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
- Earn a career certificate from Johns Hopkins University
Specialization - 4 course series
What you'll learn
Understand the basics of social computing and its relationship with social media and analytics.
Analyze how social media influences communication, behavior, and societal interactions.
Recognize how cognitive biases affect online behavior and the spread of information.
Explore how gamification enhances user motivation and improves social computing applications.
Skills you'll gain
What you'll learn
Learn to calculate and interpret key centrality measures to identify influential nodes in social networks.
Gain skills in applying statistical models to analyze relationships and dynamics within social networks.
Understand how foundational social theories inform network analysis and shape interpretations of social interactions.
Skills you'll gain
What you'll learn
Learn to construct and evaluate various machine learning classifiers and performance metrics.
Master the calculation and implications of Inter-Annotator Agreement (IAA) for data consistency.
Understand how to design and implement effective crowdsourcing tasks using Amazon Mechanical Turk.
Analyze crowdsourced data to enhance machine learning models and understand ethical considerations in AI.
Skills you'll gain
What you'll learn
Explore the history and mechanics of chatbots, enhancing your understanding of their design and function.
Construct and evaluate machine learning classifiers using BERT for effective text classification tasks.
Gain hands-on experience in creating and configuring functional chatbots using AWS Chatbot services.
Skills you'll gain
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
Instructor
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Frequently asked questions
The specialization is designed to be completed at your own pace, but on average, it is expected to take approximately 4 months to finish if you dedicate around 5 hours per week. However, as it is self-paced, you have the flexibility to adjust your learning schedule based on your availability and progress.
You are encouraged to take the courses in the recommended sequence to ensure a smoother learning experience, as each course builds on the knowledge and skills developed in the previous ones. However, you are not required to follow a specific order, and you can take the courses in the order that best suits your needs and prior knowledge.
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
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Financial aid available,