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Artificial intelligence (AI) has a long history of continuously expanding and changing. It is consequently critical to keep up with the newest advances in the sector. Whether you are an AI practitioner or an aspiring professional, here are the 5 best AI courses to learn from the best specialists.
1.Foundations of Artificial Intelligence: Learn about the history of AI and how it is used to tackle real-world challenges. This course will provide a solid basis for a career working with Artificial Intelligence systems. It will assist you in learning Python, the most popular language for constructing AI applications. Finish your learning with a Python data visualization project.
2.AI Foundations for Everyone: This specialization consists of three courses. It is intended for individuals with little or no prior experience with AI, and no programming abilities are necessary. It will introduce you to IBM Watson AI services, which allow companies to apply pre-built AI smarts to their products and solutions swiftly.
3.Deep Learning specialization: Deeplearning.AI says: If you want to get into AI, this Specialization, which consists of five courses, will assist you. You will master the fundamentals of Deep Learning, how to construct neural networks, and how to lead successful machine learning projects. RNNs, Xavier/He initialization, LSTM, Adam, Dropout, Batch Norm, Convolutional networks, and other topics will be covered.
4.Artificial Intelligence (AI): This course will give a thorough grasp of the fundamental strategies for developing intelligent computer systems and an awareness of how AI is applied to challenges. You will study the history of AI, intelligent agents, state-space problem representations, uninformed and heuristic searches, game-playing, logical agents, and constraint fulfillment issues.
5.CS50s Introduction to Artificial Intelligence and Python: This course will help you solve significant real-world challenges and secure your career's future. Students study the theory underlying graph search algorithms, classification, optimization, reinforcement learning, and other subjects in artificial intelligence and machine learning through hands-on projects that they incorporate into their Python applications.
