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    • Artificial Intelligence

    Artificial Intelligence Courses Online

    Master artificial intelligence for advanced problem-solving. Learn about machine learning, neural networks, and AI applications.

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    Explore the AI Course Catalog

    • G

      Google Cloud

      Work with Gemini Models in BigQuery - 简体中文

      Skills you'll gain: Applied Machine Learning, Big Data, Business Intelligence, Generative AI, Customer Relationship Management, Predictive Modeling, Artificial Intelligence and Machine Learning (AI/ML), SQL, Prompt Engineering, Data Analysis, Python Programming

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Responsible AI for Developers: Interpretability & Transparency - 한국어

      Skills you'll gain: Data Ethics, Artificial Intelligence, Applied Machine Learning, Data Analysis, Data Visualization Software, Exploratory Data Analysis, Machine Learning, Technical Documentation, Software Documentation

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Responsible AI for Developers: Privacy & Safety - 한국어

      Skills you'll gain: Information Privacy, Data Ethics, Personally Identifiable Information, Google Cloud Platform, Secure Coding, Cloud Security, Data Security, Safety and Security, Artificial Intelligence, Generative AI, Machine Learning

      Intermediate · Course · 1 - 3 Months

    • G

      Google Cloud

      Build, Train and Deploy ML Models with Keras on Google Cloud - Italiano

      Skills you'll gain: Tensorflow, Keras (Neural Network Library), Google Cloud Platform, Data Processing, Data Cleansing, Data Transformation, Scalability, Feature Engineering, Data Pipelines, MLOps (Machine Learning Operations), Deep Learning, Artificial Neural Networks, Machine Learning, Application Programming Interface (API)

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      G

      Google Cloud

      Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation - 日本語版

      Skills you'll gain: Generative AI, Continuous Monitoring, MLOps (Machine Learning Operations), Google Cloud Platform, Data Quality, Predictive Modeling, Machine Learning Methods, Machine Learning, Natural Language Processing

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Modernizing Data Lakes & Data Warehouses with GCP - 한국어

      Skills you'll gain: Google Cloud Platform, Data Lakes, Data Warehousing, Cloud Engineering, Cloud Storage, Data Infrastructure, Cloud Solutions, Data Pipelines, Data Architecture, Big Data, Business Intelligence, SQL, Scalability

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      G

      Google Cloud

      Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation - 简体中文

      Skills you'll gain: Generative AI, Continuous Monitoring, MLOps (Machine Learning Operations), Predictive Modeling, Applied Machine Learning, Google Cloud Platform, Machine Learning, A/B Testing, Natural Language Processing

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Gemini in Gmail - Português Brasileiro

      Skills you'll gain: Gmail, Google Workspace, Generative AI, Artificial Intelligence

      Beginner · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Work with Gemini Models in BigQuery - 日本語版

      Skills you'll gain: Customer Relationship Management, Google Cloud Platform, Generative AI, Big Data, Predictive Modeling, Prompt Engineering, Artificial Intelligence and Machine Learning (AI/ML), SQL, Data Analysis

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Responsible AI for Developers: Privacy & Safety - 日本語版

      Skills you'll gain: Information Privacy, Google Cloud Platform, Data Security, Secure Coding, Personally Identifiable Information, Generative AI, Cloud Security, Artificial Intelligence, Threat Modeling, Data Loss Prevention, Safety and Security, Data Governance, Security Controls, Encryption, Key Management, Identity and Access Management

      Intermediate · Course · 1 - 3 Months

    • G

      Google Cloud

      Responsible AI for Developers: Privacy & Safety - Українська

      Skills you'll gain: Information Privacy, Cloud Security, Personally Identifiable Information, Google Cloud Platform, Generative AI, Data Security, Security Controls, Open Source Technology, Safety and Security, Artificial Intelligence, Machine Learning Methods

      Intermediate · Course · 1 - 3 Months

    • G

      Google Cloud

      Responsible AI for Developers: Interpretability & Transparency - 日本語版

      Skills you'll gain: Data Ethics, Artificial Intelligence, Software Visualization, Data Integrity, Data Governance, Data Quality, Applied Machine Learning, Machine Learning, Technical Documentation

      Intermediate · Course · 1 - 4 Weeks

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

    • Work with Gemini Models in BigQuery - 简体中文: Google Cloud
    • Responsible AI for Developers: Interpretability & Transparency - 한국어: Google Cloud
    • Responsible AI for Developers: Privacy & Safety - 한국어: Google Cloud
    • Build, Train and Deploy ML Models with Keras on Google Cloud - Italiano: Google Cloud
    • Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation - 日本語版: Google Cloud
    • Modernizing Data Lakes & Data Warehouses with GCP - 한국어: Google Cloud
    • Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation - 简体中文: Google Cloud
    • Gemini in Gmail - Português Brasileiro: Google Cloud
    • Work with Gemini Models in BigQuery - 日本語版: Google Cloud
    • Responsible AI for Developers: Privacy & Safety - 日本語版: Google Cloud

    Frequently Asked Questions about Artificial Intelligence

    • Strong mathematics foundation (calculus, linear algebra, probability)
    • Basic programming experience (typically Python)
    • Understanding of basic statistics
    • However, there are also introductory courses specifically designed for beginners with no technical background. These courses focus on AI concepts and applications before diving into technical implementation.‎
    • Broader coverage of intelligence simulation (natural language processing, computer vision, robotics)
    • Focus on decision-making and reasoning systems
    • Coverage of symbolic AI and knowledge representation
    • Ethics and philosophical implications of AI
    • Machine learning courses focus more specifically on algorithms that learn from data. Many learners find it beneficial to start with machine learning before moving to broader AI topics.‎
    • Building and deploying AI models
    • Working with popular AI frameworks (TensorFlow, PyTorch)
    • Implementing natural language processing systems
    • Developing computer vision applications
    • Creating autonomous decision-making systems
    • Ethical AI development and deployment
    • Projects are designed to mirror real-world scenarios you'll encounter in AI roles.‎

    AI expertise opens doors to various roles:

    • AI Engineer/Developer
    • Machine Learning Engineer
    • Natural Language Processing (NLP) Specialist
    • Computer Vision Engineer
    • AI Research Scientist
    • AI Ethics Consultant
    • AI Product Manager
    • The field continues to grow with new specializations emerging regularly. Many courses include guidance on career paths and job preparation. Use this decision tree guide to explore AI career paths.‎

    Yes, Coursera offers a variety of free courses across many topics, including artificial intelligence. While you can access most course materials for free by auditing the courses, this does not include graded assignments or a completion certificate. For those looking to obtain a certificate to showcase their learning or enhance their professional profile, Coursera provides the option to purchase the course. Additionally, Coursera offers free trials or financial aid to learners who qualify, making certifications more accessible to everyone.‎

    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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