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    1708 Ergebnisse für „artificial intelligence“

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      University of Colorado Boulder

      Machine Learning: Theory and Hands-on Practice with Python

      Kompetenzen, die Sie erwerben: Machine Learning, Statistical Machine Learning, Machine Learning Algorithms, Probability & Statistics, Python Programming, Statistical Programming, Regression, Deep Learning, Data Analysis, Artificial Neural Networks, Applied Machine Learning, Correlation And Dependence, Statistical Analysis, Statistical Tests, Exploratory Data Analysis, Algorithms, Reinforcement Learning, Theoretical Computer Science, Basic Descriptive Statistics, Data Mining, Feature Engineering, General Statistics, Natural Language Processing, Data Management, Data Structures, Dimensionality Reduction

      3.1

      (27 Bewertungen)

      Intermediate · Specialization · 3-6 Months

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      IBM Skills Network

      IBM Data Science

      Kompetenzen, die Sie erwerben: Python Programming, Data Science, Data Analysis, Data Structures, Statistical Programming, Machine Learning, Data Mining, Regression, Machine Learning Algorithms, Data Visualization, General Statistics, Basic Descriptive Statistics, SQL, Applied Machine Learning, Statistical Analysis, Computer Programming Tools, Data Analysis Software, Machine Learning Software, Software Visualization, Databases, Programming Principles, Exploratory Data Analysis, Computer Programming, Statistical Visualization, Algebra, Data Management, Database Theory, Data Visualization Software, R Programming, Statistical Machine Learning, Statistical Tests, Deep Learning, Probability & Statistics, Database Application, Extract, Transform, Load, Plot (Graphics), Devops Tools, SPSS, Estimation, Interactive Data Visualization, Algorithms, Database Administration, Geovisualization, Reinforcement Learning, Theoretical Computer Science, Big Data, Business Analysis, Computational Logic, Correlation And Dependence, Econometrics, Entrepreneurship, Marketing, Mathematical Theory & Analysis, Mathematics, Spreadsheet Software, Storytelling, Supply Chain Systems, Supply Chain and Logistics, Writing

      4.6

      (106.1k Bewertungen)

      Beginner · Professional Certificate · 3-6 Months

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      Google Cloud

      Preparing for Google Cloud Certification: Machine Learning Engineer

      Kompetenzen, die Sie erwerben: Machine Learning, Cloud Computing, Google Cloud Platform, Computer Programming, Cloud Platforms, Statistical Programming, Python Programming, Data Management, Applied Machine Learning, Feature Engineering, Tensorflow, Deep Learning, Entrepreneurship, Probability & Statistics, DevOps, Data Analysis, Big Data, Artificial Neural Networks, Business Psychology, Computer Architecture, Data Visualization, Exploratory Data Analysis, Regression, SQL, Statistical Visualization, Theoretical Computer Science, Data Science, Kubernetes, Apache, Basic Descriptive Statistics, Bayesian Statistics, Computational Thinking, Computer Networking, Data Model, Data Structures, Distributed Computing Architecture, Extract, Transform, Load, General Statistics, Hardware Design, Machine Learning Algorithms, Machine Learning Software, Network Security, Performance Management, Security Engineering, Security Strategy, Statistical Machine Learning, Strategy and Operations, Algorithms, Business Analysis, Cloud Applications, Cloud Infrastructure, Cloud Storage, Data Analysis Software, Data Architecture, Data Warehousing, Database Application, Databases, Dimensionality Reduction, Full-Stack Web Development, Information Technology, Natural Language Processing, Statistical Analysis, Web Development

      4.6

      (25k Bewertungen)

      Intermediate · Professional Certificate · 3-6 Months

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      Imperial College London

      Master of Science in Machine Learning and Data Science

      Erwerben Sie ein Zertifikat

      Degree · 1-4 Years

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      University of California San Diego

      Internet of Things and AI Cloud

      Kompetenzen, die Sie erwerben: Computer Networking, Internet Of Things, Computer Graphics, Computer Architecture, Human Computer Interaction, Interactive Design, Network Architecture, Software Engineering, Software-Defined Networking, Machine Learning, Computer Programming, Computer Vision, Computational Logic, Computer Graphic Techniques, Mathematical Theory & Analysis, Mathematics, Theoretical Computer Science, Android Development, Application Development, Applied Machine Learning, Java Programming, Machine Learning Software, Mobile Development Tools, Networking Hardware, Operating Systems, Software Testing, Accounting, Algorithms, Communication, Data Visualization, General Statistics, Interactive Data Visualization, Javascript, Journalism, Leadership and Management, Mobile Development, Probability & Statistics, Security Engineering, System Programming, Web Development

      4.2

      (1.7k Bewertungen)

      Intermediate · Specialization · 3-6 Months

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      SAS

      Machine Learning Rock Star – the End-to-End Practice

      Kompetenzen, die Sie erwerben: Machine Learning, Data Analysis, Machine Learning Algorithms, Big Data, Business Analysis, Data Management, General Statistics, Probability & Statistics, Statistical Analysis, Accounting, Algorithms, Applied Machine Learning, Deep Learning, Entrepreneurship, Exploratory Data Analysis, Financial Analysis, Market Research, Plot (Graphics), Regression, Research and Design, Strategy and Operations, Theoretical Computer Science, Data Science

      4.8

      (164 Bewertungen)

      Beginner · Specialization · 3-6 Months

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      EDHEC Business School

      Investment Management with Python and Machine Learning

      Kompetenzen, die Sie erwerben: Finance, Computer Programming, Investment Management, Python Programming, Statistical Programming, Data Analysis, Machine Learning, Probability & Statistics, Data Analysis Software, Machine Learning Algorithms, Algorithms, Theoretical Computer Science, Data Mining, Natural Language Processing, Risk Management, Applied Machine Learning, Regression, Mathematics, Network Analysis, Leadership and Management, Accounting, Business Analysis, Computer Science, Financial Analysis, Statistical Analysis

      4.6

      (1.6k Bewertungen)

      Beginner · Specialization · 3-6 Months

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      Microsoft

      Microsoft Azure AI Fundamentals AI-900 Exam Prep

      Kompetenzen, die Sie erwerben: Machine Learning, Cloud Computing, Microsoft Azure, Natural Language Processing, Computer Vision, Machine Learning Algorithms, Probability & Statistics, Theoretical Computer Science, Algorithms, General Statistics, Computer Graphics, Human Computer Interaction, Interactive Design, Regression

      4.7

      (386 Bewertungen)

      Beginner · Specialization · 3-6 Months

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      University of Illinois at Urbana-Champaign

      Strategic Leadership and Management

      Kompetenzen, die Sie erwerben: Leadership and Management, Entrepreneurship, Marketing, Sales, Strategy and Operations, Strategy, Human Resources, Business Psychology, Organizational Development, Communication, Leadership Development, Research and Design, Budget Management, Finance, Negotiation, Collaboration, Decision Making, Investment Management, Adaptability, Business Development, Change Management, Culture, Market Research, Performance Management, Business Analysis, Business Communication, Business Design, Business Process Management, Conflict Management, Creativity, Human Learning, Human Resources Operations, Innovation, Mergers & Acquisitions, People Development, Planning, Problem Solving

      4.8

      (8.3k Bewertungen)

      Beginner · Specialization · 3-6 Months

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      Johns Hopkins University

      Data Science: Statistics and Machine Learning

      Kompetenzen, die Sie erwerben: R Programming, Statistical Programming, General Statistics, Statistical Analysis, Data Analysis, Machine Learning, Probability & Statistics, Statistical Tests, Data Science, Machine Learning Software, Basic Descriptive Statistics, Bayesian Statistics, Correlation And Dependence, Econometrics, Estimation, Linear Algebra, Regression, Exploratory Data Analysis, Theoretical Computer Science, Data Visualization, Interactive Data Visualization, Natural Language Processing, Probability Distribution, Plot (Graphics), Machine Learning Algorithms, Algorithms, Applied Machine Learning, Business Analysis

      4.4

      (7k Bewertungen)

      Intermediate · Specialization · 3-6 Months

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      New York University

      Machine Learning and Reinforcement Learning in Finance

      Kompetenzen, die Sie erwerben: Machine Learning, Finance, Machine Learning Algorithms, Mathematics, Algorithms, Probability & Statistics, Theoretical Computer Science, Applied Mathematics, Calculus, General Statistics, Investment Management, Applied Machine Learning, Artificial Neural Networks, Business Analysis, Data Analysis, Deep Learning, Financial Analysis, Machine Learning Software, Tensorflow, Advertising, Communication, Computer Programming, Entrepreneurship, Marketing, Markov Model, Operations Research, Python Programming, Research and Design, Statistical Machine Learning, Strategy and Operations

      3.7

      (770 Bewertungen)

      Intermediate · Specialization · 3-6 Months

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      University of Washington

      Machine Learning

      Kompetenzen, die Sie erwerben: 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

      (15.8k Bewertungen)

      Intermediate · Specialization · 3-6 Months

    Suchanfragen mit Bezug zu artificial intelligence

    artificial intelligence in healthcare
    artificial intelligence in marketing
    artificial intelligence: an overview
    artificial intelligence (ai) education for teachers
    artificial intelligence and legal issues
    artificial intelligence: ethics & societal challenges
    artificial intelligence on microsoft azure
    artificial intelligence for breast cancer detection
    1234…84

    Zusammenfassend sind hier 10 unserer beliebtesten artificial intelligence Kurse

    • Machine Learning: Theory and Hands-on Practice with Python: University of Colorado Boulder
    • IBM Data Science: IBM Skills Network
    • Preparing for Google Cloud Certification: Machine Learning Engineer: Google Cloud
    • Master of Science in Machine Learning and Data Science: Imperial College London
    • Internet of Things and AI Cloud: University of California San Diego
    • Machine Learning Rock Star – the End-to-End Practice: SAS
    • Investment Management with Python and Machine Learning: EDHEC Business School
    • Microsoft Azure AI Fundamentals AI-900 Exam Prep: Microsoft
    • Strategic Leadership and Management: University of Illinois at Urbana-Champaign
    • Data Science: Statistics and Machine Learning: Johns Hopkins University

    Häufig gestellte Fragen zum Thema Künstliche Intelligenz

    • 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.‎

    Diese häufig gestellten Fragen dienen nur zu Informationszwecken. Den Lernenden wird empfohlen, eingehender zu recherchieren, ob Kurse und andere angestrebte Qualifikationen wirklich ihren persönlichen, beruflichen und finanziellen Vorstellungen entsprechen.
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