Stanford University to Offer Free Online Course in Machine Learning

Stanford University will offer an online Machine Learning with Graphs course in the fall of 2022. The training will be free of charge for anyone who wishes to attend. Lectures will be held on Tuesday and Thursday, from 1:30 pm to 3 pm in the NVIDIA auditorium. Stanford professors will keep posting the lecture slides and assignments online as the course progresses. The complete schedule and details on the course can be found at the official website:

Anyone having a basic understanding of computer science principles sufficient to write a reasonably non-trivial computer programme can apply for the course. As per the eligibility criteria, one should be familiar with the fundamentals of probability theory and have a basic knowledge of linear algebra to understand the online course.

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In the online course, students will be trained to grasp complicated data that may be represented as a graph of relationships between objects as part of the course. These networks are critical for modelling social, technical, and biological systems.

The course focuses on the computational, algorithmic, and modelling challenges associated with massive graph analysis. Students are taught machine learning techniques and data mining tools that could provide insights into a variety of networks by studying the underlying graph structure and its properties.

The course covers the following topics: representation learning and graph neural networks; algorithms for the world wide web; reasoning over knowledge graphs; influence maximisation; disease outbreak detection; and social network analysis.

The machine learning course by Stanford University was the most popular course in 2021, according to Coursera – one of India’s leading ed-tech platforms. In 2020, ‘Science of Wellbeing by Yale University was the most opted for the course by learners on the platform.

How to learn math – a course which teaching approaches to learn the subject is also among of the most favourite online courses offered by Stanford followed by artificial intelligence: principles and techniques.

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