{"id":18340,"date":"2023-05-01T12:15:06","date_gmt":"2023-05-01T12:15:06","guid":{"rendered":"https:\/\/nftandcrypto-news.com\/crypto\/5-free-artificial-intelligence-courses-and-certifications\/"},"modified":"2023-05-01T12:15:09","modified_gmt":"2023-05-01T12:15:09","slug":"5-free-artificial-intelligence-courses-and-certifications","status":"publish","type":"post","link":"https:\/\/nftandcrypto-news.com\/crypto\/5-free-artificial-intelligence-courses-and-certifications\/","title":{"rendered":"5 Free artificial intelligence courses and certifications"},"content":{"rendered":"

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Learning artificial intelligence (AI) is becoming increasingly important for both technical and non-technical professionals, as it has the potential to revolutionize various industries and provide innovative solutions to complex problems. With free AI courses and online certifications, individuals can acquire the necessary knowledge and skills to stay relevant in today\u2019s rapidly evolving job market.<\/p>\n

The Machine Learning Specialization by DeepLearning.AI and Stanford Online<\/h2>\n

The Machine Learning Specialization by DeepLearning.AI and Stanford Online is a foundational online program that provides a broad introduction to modern machine learning. This three-course specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field.<\/p>\n

Other notable instructors include Eddy Shyu, curriculum product manager at DeepLearning.AI; Aarti Bagul, a curriculum engineer; and Geoff Ladwig, another top instructor at DeepLearning.AI.<\/p>\n

The first course in the specialization is \u201cSupervised Machine Learning: Regression and Classification,\u201d which covers building machine learning models in Python using popular machine learning libraries NumPy and scikit-learn, and building and training supervised machine learning models for prediction and binary classification tasks, including linear regression and logistic regression.<\/p>\n

The second course is \u201cAdvanced Learning Algorithms,\u201d which teaches building and training a neural network with TensorFlow to perform multiclass classification, applying best practices for machine learning development so that your models generalize to data and tasks in the real world, and building and using decision trees and tree ensemble methods, including random forests and boosted trees.<\/p>\n

The third and final course is \u201cUnsupervised Learning, Recommenders, Reinforcement Learning,\u201d which covers using unsupervised learning techniques for unsupervised learning, including clustering and anomaly detection, building recommender systems with a collaborative filtering approach and a content-based deep learning method, and building a deep reinforcement learning model.<\/p>\n

By the end of this specialization, one will have mastered key concepts and gained practical know-how to quickly and powerfully apply machine learning to challenging real-world problems. If you\u2019re looking to break into AI or build a career in machine learning, the Machine Learning Specialization is a great place to start.<\/p>\n

CS50\u2019s Introduction to Artificial Intelligence with Python by Harvard University<\/h2>\n

CS50\u2019s Introduction to Artificial Intelligence with Python, offered by Harvard University, is an introductory course exploring modern artificial intelligence concepts and algorithms.\u00a0The course is free on edX, but students can purchase a verified certificate for an additional fee. The instructors for the course are Gordon McKay, professor of the practice of computer science at Harvard University; Brian Yu, senior preceptor in computer science at Harvard University; and David Malan.<\/p>\n

Students will dive into the ideas that give rise to technologies like game-playing engines, handwriting recognition and machine translation. This course teaches students how to incorporate machine learning concepts and algorithms into Python programs through a series of hands-on projects.<\/p>\n

Related: A brief history of artificial intelligence<\/em><\/strong><\/p>\n

Students will gain exposure to the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence and machine learning. By the end of the course, students will have experience in libraries for machine learning, and knowledge of artificial intelligence principles that will enable them to design intelligent systems of their own.<\/p>\n

AI For Everyone by Coursera in collaboration with\u00a0DeepLearning.AI<\/h2>\n

AI for Everyone\u00a0is an online course offered by Coursera in collaboration with DeepLearning.AI. This course is designed for non-technical learners who want to understand AI concepts and their practical applications. It provides an overview of AI and its impact on the world, covering the key concepts of machine learning, deep learning and neural networks.<\/p>\n

The course is taught by Andrew Ng, a renowned AI expert and founder of DeepLearning.AI. He is also a co-founder of Coursera and has previously taught popular online courses on machine learning, neural networks and deep learning.\u00a0The course consists of four modules, each covering a different aspect of AI. These are:<\/p>\n

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  • What is AI?<\/li>\n
  • Building AI projects<\/li>\n
  • Building AI in your company<\/li>\n
  • AI and society<\/li>\n<\/ul>\n

    The course is self-paced and takes approximately 10 hours to complete. It includes video lectures, quizzes and case studies that allow students to apply the concepts they have learned using popular programming languages such as Python.<\/p>\n

    The course is free to audit on Coursera, and financial aid is available for those who cannot afford the fee. A certificate of completion is also available for a fee.<\/p>\n

    Machine Learning Crash Course with TensorFlow APIs by Google<\/h2>\n

    The\u00a0Machine Learning Crash Course with TensorFlow APIs\u00a0is a free online course offered by Google. It\u2019s designed for beginners who want to learn about machine learning and how to use TensorFlow, which is a popular open-source library for building and deploying machine learning models.<\/p>\n

    The course covers the following topics:<\/p>\n

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    • Introduction to machine learning and TensorFlow<\/li>\n
    • Linear regression<\/li>\n
    • Classification<\/li>\n
    • Neural networks<\/li>\n
    • Regularization<\/li>\n
    • Training and validation<\/li>\n
    • Convolutional neural networks<\/li>\n
    • Natural language processing<\/li>\n
    • Sequence models<\/li>\n<\/ul>\n

      Throughout the course, you\u2019ll learn about different machine-learning techniques, and how to use TensorFlow application programming interfaces (APIs) to build and train models. The course also includes hands-on exercises and coding assignments, which will help you gain practical experience building and deploying machine learning models.<\/p>\n

      The course is available for free on Google\u2019s website, and is self-paced so that you can learn at your own speed. Upon completion, you\u2019ll receive a certificate of completion from Google.<\/p>\n

      Related:\u00a05 emerging trends in deep learning and artificial intelligence<\/em><\/strong><\/p>\n

      Introduction to AI by Intel<\/h2>\n

      The Intel\u00ae AI Fundamentals Course is an introductory-level course that teaches the fundamentals of artificial intelligence and its applications. It covers topics such as machine learning, deep learning, computer vision, natural language processing and more. The free and self-paced course includes modules that can be completed in any order. <\/p>\n

      The eight-week program includes lectures and exercises. Each week, students are expected to spend 90 minutes completing the coursework. The exercises are implemented in Python, so prior knowledge of the language is recommended, but students can also learn it along the way. <\/p>\n

      The course does not offer a certificate of completion, but students can earn badges for completing each module. The course is designed for software developers, data scientists and others interested in learning about AI.<\/p>\n

      Ready to join the AI revolution?<\/h2>\n

      By taking advantage of the above resources, individuals can become part of the growing AI industry and contribute to shaping its future. Additionally, the ChatGPT Prompt Engineering for Developers course, developed in collaboration with OpenAI, offers developers the opportunity to learn how to use large language models (LLMs) to build powerful applications in a cost-effective and efficient manner. The course is taught by two renowned experts in the field of AI: Isa Fulford and Andrew Ng.\u00a0<\/p>\n

      Whether a learner is a beginner or an advanced machine learning engineer, this course will provide the latest understanding of prompt engineering and best practices for using prompts for the latest LLM models. With hands-on experience, one will learn how to use LLM APIs for various tasks, including summarizing, inferring, transforming text and expanding, and building a custom chatbot. This course is free for a limited time, so don\u2019t miss out on the opportunity to join the AI revolution.<\/p>\n