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    • Artificial Intelligence

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    1736 results for "artificial intelligence"

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      DeepLearning.AI, Stanford University

      Machine Learning

      Skills you'll gain: Machine Learning, Probability & Statistics, Machine Learning Algorithms, General Statistics, Theoretical Computer Science, Applied Machine Learning, Algorithms, Artificial Neural Networks, Regression, Econometrics, Computer Programming, Deep Learning, Python Programming, Statistical Programming, Mathematics, Tensorflow, Data Management, Data Structures, Statistical Machine Learning, Reinforcement Learning, Probability Distribution, Mathematical Theory & Analysis, Data Analysis, Data Mining, Linear Algebra, Computer Vision, Calculus, Feature Engineering, Bayesian Statistics, Operations Research, Research and Design, Strategy and Operations, Computational Logic, Accounting, Communication

      4.9

      (9.5k reviews)

      Beginner · Specialization · 1-3 Months

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      IBM Skills Network

      IBM Applied AI

      Skills you'll gain: Machine Learning, Cloud Computing, IBM Cloud, Python Programming, Data Analysis, Computer Vision, Computer Programming, Computer Science, Data Structures, Programming Principles, Algebra, Applied Machine Learning, Computational Thinking, Data Science, Computer Graphics, Theoretical Computer Science, Computer Graphic Techniques, Deep Learning, Natural Language Processing, Statistical Programming, Algorithms, Artificial Neural Networks, Machine Learning Software, Basic Descriptive Statistics, Computational Logic, Design and Product, Exploratory Data Analysis, Human Computer Interaction, Interactive Design, Other Web Frameworks, Product Design, Web Development, Application Development, Cloud API, Machine Learning Algorithms, Mathematical Theory & Analysis, Mathematics, Operating Systems, Software Engineering, Software Engineering Tools, Software Testing, Systems Design, Web Development Tools

      4.6

      (42.8k reviews)

      Beginner · Professional Certificate · 3-6 Months

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      DeepLearning.AI

      AI For Everyone

      Skills you'll gain: Machine Learning, Business Analysis, Applied Machine Learning, Business Transformation, Data Analysis, Data Model, Deep Learning, Exploratory Data Analysis, Forecasting, Human Computer Interaction, Natural Language Processing, People Analysis, Probability & Statistics, Reinforcement Learning, Statistical Analysis, Artificial Neural Networks, Machine Learning Algorithms

      4.8

      (37.9k reviews)

      Beginner · Course · 1-4 Weeks

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      IBM Skills Network

      Introduction to Artificial Intelligence (AI)

      Skills you'll gain: Applied Machine Learning, Data Science, Computer Vision, Deep Learning, Machine Learning, Machine Learning Algorithms

      4.7

      (10.5k reviews)

      Beginner · Course · 1-4 Weeks

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      University of Pennsylvania

      AI For Business

      Skills you'll gain: Machine Learning, Entrepreneurship, Leadership and Management, Strategy and Operations, Machine Learning Algorithms, Finance, Theoretical Computer Science, Data Management, Business Analysis, Human Resources, Marketing, Applied Machine Learning, Data Analysis, Algorithms, People Management, Sales, Artificial Neural Networks, Deep Learning, Computational Thinking, Computer Programming, Accounting, Regulations and Compliance, Strategy, Big Data, Data Mining, Data Warehousing, Feature Engineering, Natural Language Processing, Reinforcement Learning, Audit, BlockChain, Business Transformation, Clinical Data Management, Customer Analysis, Customer Relationship Management, Customer Success, Database Administration, Databases, Decision Making, Financial Analysis, Innovation, Operating Systems, People Analysis, Research and Design, Security Engineering, Software Security, System Security

      4.7

      (150 reviews)

      Beginner · Specialization · 3-6 Months

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      IBM Skills Network

      IBM AI Engineering

      Skills you'll gain: Machine Learning, Computer Programming, Python Programming, Computer Vision, Deep Learning, Statistical Programming, Artificial Neural Networks, Machine Learning Algorithms, Probability & Statistics, General Statistics, Regression, Applied Machine Learning, Apache, Data Management, Data Mining, Data Analysis, Statistical Analysis, Big Data, Algorithms, Theoretical Computer Science, Statistical Machine Learning, Computer Graphics, Dimensionality Reduction, Tensorflow, Computer Graphic Techniques, Basic Descriptive Statistics, Business Analysis, Correlation And Dependence, Databases, Mathematics, NoSQL, SQL, Econometrics, Estimation, Entrepreneurship, Machine Learning Software, Probability Distribution, Data Science, Data Structures, IBM Cloud, Supply Chain Systems, Supply Chain and Logistics

      4.6

      (16k reviews)

      Intermediate · Professional Certificate · 3-6 Months

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      Google

      Google Data Analytics

      Skills you'll gain: Data Analysis, Data Science, Statistical Programming, Business Analysis, SQL, Spreadsheet Software, Business, Data Visualization, Data Management, R Programming, Exploratory Data Analysis, Statistical Visualization, Communication, Statistical Analysis, Data Analysis Software, Business Communication, Data Structures, Data Visualization Software, Tableau Software, Big Data, Cloud Computing, Collaboration, Conflict Management, Critical Thinking, Customer Analysis, General Statistics, Leadership and Management, Plot (Graphics), Probability & Statistics, Small Data, Algorithms, Application Development, Budget Management, Computational Logic, Computer Architecture, Computer Networking, Computer Programming, Computer Programming Tools, Cryptography, Data Mining, Data Model, Database Administration, Database Design, Databases, Decision Making, Design and Product, Distributed Computing Architecture, Entrepreneurship, Extract, Transform, Load, Feature Engineering, Finance, Full-Stack Web Development, Interactive Data Visualization, Machine Learning, Mathematical Theory & Analysis, Mathematics, Network Security, Other Programming Languages, Problem Solving, Product Design, Programming Principles, Project Management, Research and Design, Security Engineering, Security Strategy, Software Engineering, Software Security, Storytelling, Theoretical Computer Science, Visual Design, Visualization (Computer Graphics), Web Development

      4.8

      (107.6k reviews)

      Beginner · Professional Certificate · 3-6 Months

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      IBM Skills Network

      AI Foundations for Everyone

      Skills you'll gain: Computer Science, Machine Learning, Applied Machine Learning, Data Science, Computational Thinking, Cloud Computing, IBM Cloud, Natural Language Processing, Computer Programming, Theoretical Computer Science, Deep Learning, Machine Learning Software, Computational Logic, Design and Product, Human Computer Interaction, Interactive Design, Product Design, Computer Vision, Machine Learning Algorithms, Software Engineering, Software Engineering Tools, Web Development, Web Development Tools

      4.7

      (12.7k reviews)

      Beginner · Specialization · 3-6 Months

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      Duke University

      AI Product Management

      Skills you'll gain: Machine Learning, Machine Learning Algorithms, Applied Machine Learning, Probability & Statistics, Regression, Human Computer Interaction, Data Analysis, Data Mining, Deep Learning, Leadership and Management, Business Psychology, Computer Networking, Database Administration, Databases, Finance, Network Security, Regulations and Compliance, Research and Design, Security Engineering, User Experience, User Experience Design, Artificial Neural Networks, Computer Vision, Natural Language Processing, Statistical Machine Learning, Algorithms, Data Management, Data Science, Data Structures, Design and Product, Econometrics, Entrepreneurship, Feature Engineering, General Statistics, Operating Systems, Product Management, Project Management, Strategy and Operations, Systems Design, Theoretical Computer Science

      4.7

      (181 reviews)

      Beginner · Specialization · 3-6 Months

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      DeepLearning.AI

      Deep Learning

      Skills you'll gain: Deep Learning, Machine Learning, Artificial Neural Networks, Python Programming, Statistical Programming, Machine Learning Algorithms, Linear Algebra, Applied Machine Learning, Statistical Machine Learning, Dimensionality Reduction, Feature Engineering, Probability & Statistics, Business Psychology, Entrepreneurship, Machine Learning Software, Computer Vision, Marketing, General Statistics, Natural Language Processing, Computer Programming, Leadership and Management, Project Management, Regression, Sales, Strategy, Strategy and Operations, Tensorflow, Differential Equations, Mathematics, Applied Mathematics, Decision Making, Supply Chain Systems, Supply Chain and Logistics, Advertising, Communication, Estimation, Forecasting, Mathematical Theory & Analysis, Statistical Visualization, Algorithms, Theoretical Computer Science, Bayesian Statistics, Calculus, Probability Distribution, Statistical Tests, Big Data, Computer Architecture, Computer Networking, Data Management, Human Computer Interaction, Network Architecture, User Experience, Algebra, Computational Logic, Computer Graphic Techniques, Computer Graphics, Data Structures, Data Visualization, Hardware Design, Interactive Design, Markov Model, Network Model

      4.8

      (138.4k reviews)

      Intermediate · Specialization · 3-6 Months

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      University of Washington

      Machine Learning

      Skills you'll gain: Machine Learning, Machine Learning Algorithms, Data Science, Statistical Machine Learning, Linear Algebra, Statistical Analysis, Data Mining, Regression, Applied Machine Learning, Feature Engineering, General Statistics, Natural Language Processing, Python Programming, Machine Learning Software, Statistical Tests, Data Analysis, Dimensionality Reduction, Statistical Programming, Deep Learning, Basic Descriptive Statistics, Probability & Statistics, Computer Vision, Statistical Visualization, Estimation, Probability Distribution, Correlation And Dependence, Forecasting, Big Data, Data Management, Algorithms, Bayesian Statistics, Business Analysis, Business Psychology, Computational Logic, Computational Thinking, Computer Architecture, Computer Graphic Techniques, Computer Graphics, Computer Programming, Data Structures, Distributed Computing Architecture, Entrepreneurship, Exploratory Data Analysis, Markov Model, Mathematical Theory & Analysis, Mathematics, Theoretical Computer Science

      4.6

      (15.9k reviews)

      Intermediate · Specialization · 3-6 Months

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      University of Washington, Microsoft

      Autonomous AI for Industry

      Skills you'll gain: Entrepreneurship, Leadership and Management, Marketing, Sales, Strategy, Strategy and Operations, Computer Networking, Decision Making, Deep Learning, Machine Learning, Network Model, Reinforcement Learning, Business Psychology, Innovation

      4.6

      (34 reviews)

      Beginner · Specialization · 3-6 Months

    Searches related to artificial intelligence

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    In summary, here are 10 of our most popular artificial intelligence courses


      Frequently Asked Questions about Artificial Intelligence

      • If you're interested in artificial intelligence and want to learn more for free, check out Coursera's course selection. Specifically, AI and the Business Future of Work provides a great introduction to AI in a business setting. If you're more technically-minded, try Introduction to Embedded Machine Learning to gain insights on machine learning algorithms and learn how to create solutions that can run on almost any platform. If you want to take advantage of the cloud, Master Machine Learning on AWS is also available. If you want to learn more on the Ethical Implications of AI. Finally, if you're keen to learn about putting AI models into embedded devices, have a look at Computer Vision with Embedded Machine Learning to gain an understanding and start making computer vision projects from where ever you are.‎

      • For those new to Artificial Intelligence, an excellent starting point is Coursera's AI for Everyone course, which will introduce the fundamentals of machine learning. Another excellent course is Coursera's Introduction to AI, which explores supervised and unsupervised learning and natural language processing in detail. There is also the UoL Machine Learning for All course which provides an extensive introduction to the basic concepts and tools in machine learning. Additionally, Coursera's Artificial Intelligence Marketing course will teach you how to use AI to drive business value. Lastly, Coursera's Introduction to AI in the Data Center course provides an introduction to AI principles in the context of the data center environment.‎

      • If you are looking for an advanced artificial intelligence course, consider taking Introduction to Tensorflow or Machine Learning with Python. You could also learn about the data lifecycle in production with Machine Learning: Data Lifecycle in Production, develop exploratory data analysis skills with IBM Exploratory Data Analysis for Machine Learning, or dive into Python Project for AI Application Development.‎

      • Artificial intelligence (AI) is a fast-growing branch of computer science focused on enabling computers to perform a wide range of tasks that previously required human intelligence. Today, AI is used to power a wide range of tasks, such as image recognition, language translation, and prioritization of email or business workflows. So, if you have a smartphone, chances are you use software with AI capabilities every day.

        AI is often discussed in tandem with the closely related concept of machine learning. Machine learning is the use of step-by-step processes called algorithms to allow computers to solve problems on their own - and, over time, get steadily better at doing so. Well-designed machine learning algorithms give computers the ability to solve a wide range of problems much more effectively and flexibly than if programmers had to provide detailed instructions for one specific use case.

        While machine learning is used to create many simple AI applications, this approach typically requires massive, clearly-defined datasets to properly “train” the program. To create more sophisticated AI applications, an advanced type of machine learning called deep learning is used. Deep learning uses artificial neural networks that, as its name implies, are patterned after the human brain and do not require such structured datasets and human guidance to be successful. Instead, the AI application can be fed diverse, unstructured datasets and learn itself how to achieve a specified goal.

        Even today’s most powerful deep learning approaches are not capable of mimicking the complexity and creativity of the human brain and its tens of billions of neurons. However, the field of artificial intelligence has made incredible strides in recent years, and is changing the way we live and work in ways that would have seemed outlandish a decade ago. Who knows what the next decade of progress in this exciting field will yield? Students learning skills in this area today may end up producing even more radical breakthroughs.‎

      • As artificial intelligence (AI) touches more and more areas of our daily lives, it is becoming useful to more and more career paths. Indeed, at least some background in this field is required for a growing number of jobs, and it can help give you a significant advantage over the competition in many others.

        Naturally, AI and its subfields are in very high demand for popular computer science jobs. Data scientists rely on machine learning and deep learning skills in their daily work, applying various data mining techniques to both structured and unstructured big data in order to produce valuable insights for a wide variety of businesses. Skills in natural language processing (NLP) are needed to create useful chatbots for customer service as well as voice-activated assistants like Amazon’s Alexa. And advanced AI skills can put you on the cutting edge of computer programming, working on teams seeking to achieve ambitious goals like self-driving cars or autonomous robots.

        A background in AI can help you in more and more jobs outside the realm of computer science, as well - it’s not much of an exaggeration to say that if a job requires human intelligence to do, artificial intelligence can help.

        For example, a familiarity with machine learning can help business analysts understand and use sophisticated tools for predicting movements in the market - or develop these tools themselves. Doctors and other healthcare professionals are leveraging AI to assist with diagnosing illnesses, prescribing treatments, and analyzing medical data. Even creative professionals in visual arts and music can take advantage of AI tools to help them generate images and melodies.‎

      • Coursera offers online courses in an incredibly wide range of computer science topics, and artificial intelligence is no exception. If you’re a computer science student interested in this fast-growing field, online courses can give you an introduction to AI and machine learning, or help you hone your Python skills for data science. More advanced learners can dive deep, with courses and Specializations in AI engineering and deep learning. Even non-computer scientists can benefit from courses geared towards their field, such as the use of machine learning for trading and other business professionals.

        Whatever your level of expertise and area of interest, online courses let you learn remotely on a flexible schedule and, typically, a lower cost than on-campus alternatives. And thanks to Coursera’s partnerships with top-ranked schools like Stanford University and Imperial College London, as well as industry leaders like IBM and Google Cloud, students can get all the advantages of online learning while still getting a high-quality education in this exciting field.‎

      • The skills or experience you may need to have before learning artificial intelligence (AI) includes having a solid knowledge of math, science, and computer science, specifically data science. You may want to have experience with advanced math, such as calculus and algebra, Bayesian algorithms, plus probability and statistics. In addition, a science background may be good to have for learning AI, including an understanding of physics, mechanics, cognitive learning theory, and language processing. It will also help to have a good command of computer science, including programming languages and tools such as Python, C++, and Java. Understanding the basic foundations of machine learning, deep learning, and neural networks may also be helpful to you before learning AI. If you already have some experience in software development, automotive manufacturing, and aerospace manufacturing fields, you may already have some necessary understanding of the way AI is applied in these industries.‎

      • The kind of people who are best suited for roles in AI are interested in highly scientific concepts and tools. People well suited to work in roles in AI feel comfortable experimenting with advanced technologies and concepts, such as machine learning, a part of AI that has given the world self-driving cars, for example. They also feel energized working with sophisticated pieces of software that can make decisions by analyzing data. In addition, the type of people well suited to work in roles in AI may want to learn to have the ability to build sophisticated pieces of equipment, such as robotics, which operate on internal software.‎

      • Learning artificial intelligence may be right for you if you plan on becoming an AI developer, machine learning engineer, data scientist, or research engineer or if you want your company to become better at using AI. In addition, learning AI may be beneficial if you are in the medical field, which AI is transforming when it comes to diagnosing, treating, and predicting outcomes. Learning AI may benefit you if you want to understand what AI realistically can and can't do and if you want to be able to spot opportunities to apply AI to your organization’s problems and know how to navigate the ethics of machine learning, along with other dimensions of AI.‎

      This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.
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