Start your 2022 by Learning AI

New year is coming! We are working hard to release brand new AI for Beginners Curriculum by the New Year, so that you can start off your 2022 by learning something new!

Some of you may know that one of the things I do is teach semester-long Artificial Intelligence course at the university. Now I am putting all the content from that course online into AI for Beginners curriculum, expanding it with the help of my colleagues and Student Ambassadors. The course is scheduled to be released in December.

Sign Up for AI for Beginners Learning Group

Starting February 2022, we are planning to run AI for Beginners Learning Group to go through the content of the curriculum together. We will be holding a series of weekly Q&A webinars, so that you can ask any questions that you have and provide the feedback on the content. We encourage you to sign up early to be the member of this learning group.

All communication in the Learning Group will be done via Global AI Community Slack channel. To be part of the group:

  1. Join Global AI Comminity Slack
  2. Join #ai-for-beginners channel in slack.

What you will get by signing up:

  • Early access to AI Curriculum and the announcement when it becomes available
  • Access to weekly Q&A webinars in Spring 2022
  • A chance to network within an international community of other students eager to learn AI

We hope it is going to be fun!

AI for Beginners: What to Expect

AI for Beginners would be a 24 lesson long comprehensive text-based course that will introduce you to the topic of AI in general, with special emphasis on Neural Networks and Deep Learning. You would have a set of executable Jupyter Notebooks full of content together with some exercises / labs for you to play with. The main topic covered in the curriculum include:

  • Overview of AI landscape and different approaches to intelligence.
  • GOFAI, symbolic reasoning and knowledge representation.
  • Neural networks and Neural frameworks: Tensorflow PyTorch.
  • Computer Vision: from simple convolution networks to object detection and semantic segmentation.
  • Natural Language Processing: from simple recurrent networks to modern transformer-based architectures.
  • Deep Reinforcement Learning
  • Other AI techniques, such as Genetic Algorithms and Multi-Agent Systems
  • AI Ethics

This curriculum does not include classical Machine Learning - we encourage you to study our Machine Learning for Beginners Curriculum to learn classical ML algorithms and libraries such as Scikit Learn.

Microsoft has already released a series of open curricula on GitHub, starting from Web Development for Beginners, followed by Machine Learning for Beginners and Data Science for Beginners.

Eager to Start? Go to Microsoft Learn Now

Large part of the upcoming curriculum is already available on Microsoft Learn as PyTorch Fundamentals and Tensorflow Fundamentals Learning Path. On Microsoft Learn, you also get access to GPU Compute sandbox environment that you can use to experiment with the code and to train your own models.

We are looking forward to see you in AI for Beginners Study Group!

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