Introduction
Explore the world of Artificial Intelligence with the AI for Beginners course by GitHub Microsoft. This comprehensive curriculum provides a step-by-step introduction to AI, covering topics like Symbolic AI, Neural Networks, Computer Vision, Natural Language Processing, and more. Read on to learn how this course can help kickstart your AI journey.
Artificial Intelligence is one of the most exciting and rapidly growing fields in technology, and there is a growing demand for individuals who can work with AI applications. If you're a beginner looking to dive into the world of AI, look no further than the AI for Beginners course by GitHub Microsoft. In this blog post, we'll explore this comprehensive curriculum and how it can help you embark on your AI journey.
Keywords: AI for Beginners, GitHub Microsoft, Artificial Intelligence, curriculum, Symbolic AI, Neural Networks, Computer Vision, Natural Language Processing
Course Overview
The AI for Beginners course is structured as a curriculum, covering various topics and providing hands-on labs and resources. The course is divided into six major sections: Introduction to AI, Symbolic AI, Introduction to Neural Networks, Computer Vision, Natural Language Processing, and Other AI Techniques. Each section encompasses several lessons, which are further divided into subtopics.
Who is this course for?
The AI for Beginners course is tailored for everyone who are new to the field, making it ideal for beginners with an interest in AI. The course assumes minimal prior knowledge, ensuring that participants can grasp the fundamentals and build a solid foundation for further exploration of AI. Whether you are a student, professional, or an AI enthusiast, this course will provide you with the necessary knowledge to embark on your AI journey.
Here is an overview of the course structure:
Section I - Introduction to AI:
Lesson 1: Introduction and History of AI
Section II - Symbolic AI:
Lesson 2: Knowledge Representation and Expert Systems
Section III - Introduction to Neural Networks:
Lesson 3: Perceptron
Lesson 4: Multi-Layered Perceptron and Creating our own Framework
Lesson 5: Intro to Frameworks (PyTorch/TensorFlow) and Overfitting
Section IV - Computer Vision:
Lesson 6: Intro to Computer Vision. OpenCV
Lesson 7: Convolutional Neural Networks
Lesson 8: Pre-trained Networks and Transfer Learning
Lesson 9: Autoencoders and VAEs
Lesson 10: Generative Adversarial Networks
Lesson 11: Object Detection
Lesson 12: Semantic Segmentation. U-Net
Section V - Natural Language Processing:
Lesson 13: Text Representation. Bow/TF-IDF
Lesson 14: Semantic word embeddings. Word2Vec and GloVe
Lesson 15: Language Modeling. Training your own embeddings
Lesson 16: Recurrent Neural Networks
Lesson 17: Generative Recurrent Networks
Lesson 18: Transformers. BERT.
Lesson 19: Named Entity Recognition
Lesson 20: Large Language Models, Prompt Programming, and Few-Shot Tasks
Section VI - Other AI Techniques:
Lesson 21: Genetic Algorithms
Lesson 22: Deep Reinforcement Learning
Lesson 23: Multi-Agent Systems
Section VII - AI Ethics:
Lesson 24: AI Ethics and Responsible AI
The course also offers additional extras, such as multi-modal networks, AI ethics, and responsible AI.
Practical Labs and Resources
To enhance the learning experience, the AI for Beginners course provides laboratory exercises and hands-on practice using widely used AI frameworks like PyTorch and TensorFlow. Students will have the opportunity to gain practical experience in computer vision, natural language processing, and other AI techniques. The labs are designed to reinforce the theoretical concepts covered in the lessons and provide a deeper understanding of AI applications.
Check this video for detailed information
Conclusion
The AI for Beginners course by GitHub Microsoft provides a comprehensive introduction to the exciting world of AI. With practical labs, resources, and a step-by-step curriculum, this course is designed to cater to individuals who are new to AI. By taking this course, individuals can gain the necessary knowledge and skills to start working on AI applications. If you're interested in AI and want to learn more, take the AI for Beginners course by GitHub Microsoft today.
References
GitHub Microsoft AI for Beginners course: https://microsoft.github.io/AI-For-Beginners/
GitHub Repository: https://github.com/microsoft/AI-For-Beginners/tree/main
Free Downloadable PDF Curriculum: https://microsoft.github.io/etc/pdf/readme.pdf
GitHub Microsoft responsible AI Principles: https://learn.microsoft.com/en-us/ai/?WT.mc_id=academic-77998-cacaste
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