"Artificial Intelligence Fundamentals: A Comprehensive Guide to AI and its Applications" is a comprehensive course designed for those who are interested in learning about the exciting and rapidly evolving field of artificial intelligence. This course offers a deep dive into the core concepts, algorithms, and applications of AI, providing students with a comprehensive understanding of the subject matter.
The course starts by exploring the history of AI, from its early beginnings to its current state of development. Students will learn about the different branches of AI, including machine learning, deep learning, computer vision, and natural language processing. They will also be introduced to the mathematical and statistical foundations of AI, including linear algebra, probability, and optimization.
As the course progresses, students will learn about the various algorithms and techniques used in AI, such as supervised and unsupervised learning, decision trees, neural networks, and convolutional neural networks. They will also be introduced to popular AI tools and libraries, such as TensorFlow, PyTorch, and Keras.
In addition to the technical aspects of AI, the course also covers its real-world applications, including self-driving cars, natural language processing, and computer vision. Students will learn how AI is being used in different industries, such as healthcare, finance, and e-commerce, and they will also get to explore various case studies and projects.
By the end of the course, students will have a strong understanding of the fundamental theories and techniques behind AI, as well as the ability to apply their knowledge to real-world problems. They will also have the skills to start building their own AI models and applications.
Whether you're an aspiring AI engineer, data scientist, or simply curious about the cutting-edge technology, this course is for you. With its comprehensive curriculum, hands-on projects, and expert instructors, you'll have everything you need to take your AI skills to the next level.
What will i learn?
- Fundamentals of AI: You will gain a solid understanding of the key concepts, theories, and techniques behind AI, including machine learning, deep learning, computer vision, and natural language processing.
- Hands-on experience: You will have the opportunity to apply your knowledge through hands-on projects and exercises, building your own AI models and applications.
- Computer with a reliable internet connection: You will need a computer with a stable internet connection to access the course materials, videos, and any additional resources.
- Programming knowledge: A basic understanding of programming concepts and experience with a programming language such as Python is recommended.
- Basic understanding of mathematics, including algebra, probability, and statistics.
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Basics of calculus-functions ,limits, continuity, derivatives intuition
01:10:00
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Derivatives definition, differentiability, maxima and minima
00:40:00
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Coordinate Geometry & gradients
01:00:00
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problem solving session
00:30:00
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Fish sorting example, how to approach a ML problem, representing data with a hyperplane ,brute force approach for finding optimal w vector
01:00:00
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Coordinate geometry to linear algebra conversion and linear algebra rules
01:05:00
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Half spaces, training and testing phase
00:45:00
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Artificial intelligence
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Artificial intelligence
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Artificial intelligence
00:45:00
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Artificial intelligence
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Artificial intelligence
01:15:00
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Artificial intelligence
01:10:00
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Artificial intelligence
01:10:00
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Artificial intelligence class
00:30:00
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Artificial intelligence class
01:15:00
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Artificial intelligence class
01:05:00
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Artificial intelligence class
01:10:00
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Artificial intelligence class
00:30:00
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Artificial intelligence class
01:05:00
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Artificial intelligence class
00:55:00
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Artificial intelligence class
00:55:00
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Artificial intelligence class
00:50:00
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Artificial intelligence class
00:55:00
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Artificial intelligence class
00:30:00
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Artificial intelligence class
01:00:00
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Artificial intelligence class
00:55:00
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Artificial intelligence class
01:00:00
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Artificial intelligence class
00:30:00
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Artificial intelligence class
01:00:00
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Artificial intelligence class
00:50:00
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Artificial intelligence class
00:50:00
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Artificial intelligence class
00:50:00
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Artificial intelligence class
00:50:00
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Artificial intelligence class
00:45:00
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Artificial intelligence class
00:35:00
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Artificial intelligence class
00:40:00
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