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Artificial Intelligence - Beginner Level

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Starting an AI course as a beginner can be both exciting and overwhelming due to the vast amount of resources available. Here is a structured pathway to help you get started, focusing on building a strong foundation before moving on to more complex topics: 1. Introduction to AI and Machine Learning Objective: Understand the basics of AI and machine learning, different types of learning (supervised, unsupervised, reinforcement), and their applications. Course Recommendation: "AI For Everyone" by Andrew Ng on Coursera. This course is designed for non-technical people to understand AI's capabilities, limitations, and how it can be applied to various industries. 2. Programming Basics Objective: Learn a programming language that is widely used in AI, such as Python. Course Recommendation: "Python for Everybody" on Coursera or "Automate the Boring Stuff with Python" by Al Sweigart (available free online). These courses are great for absolute beginners. 3. Mathematics for AI Objective: Brush up on or learn the essential mathematics for AI, including algebra, calculus, and statistics. Course Recommendation: "Mathematics for Machine Learning" by Imperial College London on Coursera. This course trio (Linear Algebra, Multivariate Calculus, and PCA) lays the mathematical groundwork necessary for deeper AI study. 4. Deep Learning and Neural Networks Objective: Dive into the specifics of neural networks and deep learning, understanding how they work and how to implement them. Course Recommendation: "Deep Learning Specialization" by Andrew Ng on Coursera. It covers neural networks, deep learning, structuring machine learning projects, convolutional networks, sequence models, and more. 5. Practical Projects Objective: Apply what you've learned in real-world projects to solve problems using AI and machine learning. Course Recommendation: Participate in Kaggle competitions or work on projects.

You can also join this program via the mobile app. Go to the app


AED 500.00


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