Subject – Machine Learning for Social Sciences and Social Media Analysis
Industry – Machine Learning and AI
Introduction:
Welcome to the eLearning course on Social Network Analysis and Community Detection, presented by T24Global Company. In this course, we will explore the fascinating field of social network analysis (SNA) and its application in the context of machine learning and artificial intelligence (AI).
Social Network Analysis has gained significant attention in recent years due to the exponential growth of online social platforms and the availability of vast amounts of social data. SNA involves studying the relationships and interactions between individuals, organizations, or entities in a network. By analyzing these connections, we can gain valuable insights into various social phenomena, such as information flow, influence, and community structures.
In this course, we will delve into the fundamental concepts of social network analysis, starting with an overview of network theory and its applications. We will explore different types of networks, including social networks, web networks, and biological networks, and understand how they can be represented and analyzed using graph theory.
Furthermore, we will discuss the importance of community detection in social network analysis. Communities are groups of nodes that are densely connected within themselves and sparsely connected to nodes outside the community. Detecting these communities can provide us with a deeper understanding of network structures, information diffusion, and social dynamics. We will explore various community detection algorithms, including modularity optimization, hierarchical clustering, and spectral clustering.
To fully leverage the power of social network analysis, we will integrate machine learning and AI techniques into the process. Machine learning algorithms can aid in identifying patterns, predicting behavior, and classifying nodes within a network. We will explore different machine learning approaches, such as supervised and unsupervised learning, and discuss their applications in social network analysis.
Throughout the course, we will provide hands-on experience with real-world datasets and practical examples. We will guide you through the process of data preprocessing, network visualization, and applying machine learning algorithms for social network analysis. By the end of the course, you will have gained the necessary knowledge and skills to analyze social networks, detect communities, and apply machine learning techniques in this domain.
Whether you are a data scientist, researcher, or professional seeking to enhance your understanding of social network analysis and its intersection with machine learning and AI, this course is designed to provide you with a comprehensive foundation. Join us on this exciting journey into the world of Social Network Analysis and Community Detection, and unlock the potential of network data in various domains.
NOTE – Post purchase, you can access your course at this URL – https://mnethhil.elementor.cloud/courses/social-network-analysis-and-community-detection/ (copy URL)
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Lessons Included