Explore the world of Artificial Intelligence (AI) with our 12-week, 24-lesson curriculum! It includes practical lessons, quizzes, and labs. The curriculum is beginner-friendly and covers tools like TensorFlow and PyTorch, as well as ethics in AI.
What you will learn
In this curriculum, you will learn:
- Different approaches to Artificial Intelligence, including the “good old” symbolic approach with Knowledge Representation and reasoning (GOFAI).
- Neural Networks and Deep Learning, which are at the core of modern AI. We will illustrate the concepts behind these important topics using code in two of the most popular frameworks.
- Neural Architectures for working with images and text. We will cover recent models but may be a bit lacking in the state-of-the-art.
- Less popular AI approaches, such as Genetic Algorithms and Multi-Agent Systems.
Each lesson contains
- Pre-reading material
- Executable Jupyter Notebooks, which are often specific to the framework. The executable notebook also contains a lot of theoretical material, so to understand the topic you need to go through at least one version of the notebook.
- Labs available for some topics, which give you an opportunity to try applying the material you have learned to a specific problem.
- Some sections contain links to MS Learn modules that cover related topics.
What we will not cover in this curriculum:
- Business cases of using AI in Business. Consider taking Introduction to AI for business users learning path on Microsoft Learn, or AI Business School, developed in cooperation with INSEAD.
- Classic Machine Learning, which is well described in our Machine Learning for Beginners Curriculum.
- Practical AI applications built using Cognitive Services. For this, we recommend that you start with modules Microsoft Learn for vision, natural language processing, Generative AI with Azure OpenAI Service and others.
- Specific ML Cloud Frameworks, such as Azure Machine Learning, Microsoft Fabric, or Azure Databricks. Consider using Build and operate machine learning solutions with Azure Machine Learning and Build and Operate Machine Learning Solutions with Azure Databricks learning paths.
- Conversational AI and Chat Bots. There is a separate Create conversational AI solutions learning path, and you can also refer to this blog post for more detail.
- Deep Mathematics behind deep learning. For this, we would recommend Deep Learning by Ian Goodfellow, Yoshua Bengio and Aaron Courville, which is also available online at https://www.deeplearningbook.org/.
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