Reminder: Today is the last day to enroll in Causal Modeling in Machine Learning.
Over the past few years, causality and causal modeling has become a very hot topic in machine learning.
Yoshua Bengio and other ML luminaries are excited about its potential to help address pressing issues like transparency and bias that limit our ability to use ML in many important areas.
One of the challenges facing those interested in learning about causality, however, is that most resources on the topic cater to the needs of statisticians or economists, as opposed to those of data scientists and machine learning engineers.
Last year we launched a course that addressed this challenge.
The Causal Modeling in Machine Learning course and study group with instructor Robert Ness is designed to be both practical and accessible. It provides depth for those students looking to bridge the gap between theory and the real world, while remaining accessible to those who simply want an overview of this important topic.
Through weekly live study groups, one-on-one office hours with Robert, and engaging course materials, students learn the fundamentals of causal reasoning as well as the tools of causal modeling—like graphical models and probabilistic programming. This will provide you with a solid understanding of the field and the ability to begin applying causal modeling to your own problems.
If you missed our inaugural session, here’s some good news: The Causal Modeling in Machine Learning course is currently open to new enrollees for a limited time.
Past students have raved about the course. They find Robert’s teaching style to be engaging, deeply knowledgeable, and inspiring. Here’s what a few past students had to say:
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“I liked the course very much. Robert did a great job of reaching out to students to understand their background and interest in the course. It was great how he then continued to use what he learned about the students to make the course relevant and engaging to everyone enrolled. I also like how he made a connection to new paradigms. It was really nice to feel that the course is up to date. There are a lot of machine learning courses but this course was really special.”
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“I loved the course. I learned a ton and Robert was very available to students. When I think about how much I would have paid at my university for a similar course, [the course] is a great value.”
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“The course materials are nice and engaging. They cover the core fundamentals and other topics in a very structured way. Also, the one-on-one check-ins with Robert were very helpful and motivating. It was great to get support and have my questions answered.”
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“Robert is a great teacher. There are not a lot of causal inference courses online. This course is the first I found that combines causal inference and machine learning. It does a great job of bridging the theoretical with what happens in the real world.”
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“I feel great about the impact the course had on me. It helped me grow in how I think about and approach problems.”
Every student we’ve spoken with told us that their tuition was well worth the investment.
This is your last chance to enroll in the summer session of the course. Robert will be closing enrollment for the course tonight, to ensure that those who have joined have an amazing experience.
