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  • Google Machine Learning

Results for "google machine learning"


  • G

    Google Cloud

    Preparing for Google Cloud Certification: Machine Learning Engineer

    Skills you'll gain: Feature Engineering, MLOps (Machine Learning Operations), Model Optimization, Generative AI, Google Cloud Platform, Model Deployment, Tensorflow, Generative AI Agents, Google Gemini, Model Training, Dataflow, Big Data, Keras (Neural Network Library), Machine Learning, Generative Model Architectures, Data Preprocessing, Machine Learning Software, CI/CD, Model Evaluation, Cloud Computing

    ★ 4.4 (4.9K) · Intermediate · Professional Certificate · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • G

    Google Cloud

    Introduction to AI and Machine Learning on Google Cloud

    Skills you'll gain: Generative AI, Generative AI Agents, Google Gemini, Google Cloud Platform, Generative Model Architectures, MLOps (Machine Learning Operations), Prompt Engineering, Tensorflow, AI Workflows, Cloud Infrastructure, Applied Machine Learning, Artificial Intelligence, Data Infrastructure, Multimodal Prompts, Model Deployment, Model Training, Machine Learning, Model Evaluation, Supervised Learning

    ★ 4.6 (326) · Beginner · Course · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • G

    Google Cloud

    Machine Learning on Google Cloud

    Skills you'll gain: Feature Engineering, Model Optimization, Generative AI, Model Deployment, Tensorflow, Generative AI Agents, Google Gemini, Model Training, Keras (Neural Network Library), Machine Learning, Generative Model Architectures, Data Preprocessing, Machine Learning Software, MLOps (Machine Learning Operations), Google Cloud Platform, Model Evaluation, Applied Machine Learning, Data Cleansing, Data Quality, Cloud Computing

    ★ 4.4 (3.8K) · Intermediate · Specialization · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • G

    Google Cloud

    Advanced Machine Learning on Google Cloud

    Skills you'll gain: Model Deployment, Model Optimization, Convolutional Neural Networks, Google Cloud Platform, Natural Language Processing, Tensorflow, MLOps (Machine Learning Operations), Large Language Modeling, Reinforcement Learning, Model Training, Transfer Learning, Computer Vision, Keras (Neural Network Library), Systems Design, Applied Machine Learning, Image Analysis, AI Personalization, Cloud Deployment, Recurrent Neural Networks (RNNs), Machine Learning

    ★ 4.5 (1.5K) · Advanced · Specialization · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • D
    S

    Multiple educators

    Machine Learning

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Machine Learning Methods, Model Training, Applied Machine Learning, Machine Learning Algorithms, Transfer Learning, Machine Learning, Jupyter, Data Ethics, Decision Tree Learning, Model Evaluation, Responsible AI, Tensorflow, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Classification Algorithms

    ★ 4.9 (39K) · Beginner · Specialization · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • G

    Google

    The Nuts and Bolts of Machine Learning

    Skills you'll gain: Feature Engineering, Decision Tree Learning, Applied Machine Learning, Supervised Learning, Advanced Analytics, Statistical Machine Learning, Machine Learning, Machine Learning Algorithms, Unsupervised Learning, Machine Learning Methods, Model Training, Random Forest Algorithm, Model Optimization, Data Analysis, Predictive Modeling, Model Evaluation, Python Programming, Performance Tuning, Classification Algorithms

    ★ 4.8 (617) · Advanced · Course · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered

What brings you to Coursera today?

  • G

    Google Cloud

    Machine Learning Operations (MLOps) on Google Cloud

    Skills you'll gain: MLOps (Machine Learning Operations), Model Evaluation, Model Deployment, AI Orchestration, AI Workflows, Generative AI, Google Cloud Platform, Data Modeling, Continuous Monitoring, Data Pipelines, Model Training, Feature Engineering, Model Optimization, DevOps, Agentic Workflows, Generative AI Agents, Data Store, Continuous Deployment, Forecasting, Metadata Management

    ★ 4 (496) · Intermediate · Specialization · 3 - 6 Months

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • B

    Board Infinity

    Machine Learning and Deep Learning for Software Engineers

    Skills you'll gain: Feature Engineering, Model Evaluation, Model Deployment, Fine-tuning, Data Preprocessing, Model Training, Deep Learning, Machine Learning Methods, Model Optimization, Scikit Learn (Machine Learning Library), PyTorch (Machine Learning Library), Scalability, Hugging Face, Docker (Software), Supervised Learning, Machine Learning Algorithms, Applied Machine Learning, Application Deployment, Software Development, Machine Learning

    Intermediate · Specialization · 1 - 3 Months

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • G

    Google Cloud

    Data Engineering, Big Data, and Machine Learning on GCP

    Skills you'll gain: Dashboard Creation, Model Deployment, Feature Engineering, PySpark, Data Import/Export, Big Data, Apache Spark, Apache Hadoop, Dashboard, Data Architecture, Data Governance, Apache Kafka, Data Store, Cloud Services, Cloud Deployment, Metadata Management, Data Storage, Data Quality, Data Cleansing, Machine Learning Methods

    ★ 4.6 (4.4K) · Intermediate · Specialization · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • D

    DeepLearning.AI

    Supervised Machine Learning: Regression and Classification

    Skills you'll gain: Supervised Learning, Applied Machine Learning, Jupyter, Scikit Learn (Machine Learning Library), Machine Learning, Model Training, NumPy, Machine Learning Algorithms, Predictive Modeling, Classification Algorithms, Feature Engineering, Artificial Intelligence, Model Evaluation, Data Preprocessing, Python Programming, Logistic Regression, Model Optimization, Regression Analysis, Algorithms

    ★ 4.9 (32K) · Beginner · Course · 1 - 4 Weeks

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • G

    Google Cloud

    Digital Transformation Using AI/ML with Google Cloud

    Skills you'll gain: Business Transformation, Innovation, Digital Transformation, Serverless Computing, Cloud Services, Data Ethics, Cloud Infrastructure, Google Cloud Platform, Culture Transformation, Application Programming Interface (API), Technology Strategies, Cloud Security, Data Mapping, Applied Machine Learning, Hybrid Cloud Computing, Data Strategy, Model Training, Cloud Platforms, Image Analysis, Infrastructure As A Service (IaaS)

    ★ 4.7 (7.6K) · Beginner · Specialization · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • I

    IBM

    Machine Learning with Python

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Model Evaluation, Regression Analysis, Scikit Learn (Machine Learning Library), Machine Learning Methods, Applied Machine Learning, Model Training, Statistical Machine Learning, Predictive Modeling, Machine Learning Algorithms, Machine Learning, Dimensionality Reduction, Decision Tree Learning, Python Programming, Logistic Regression, Model Optimization, Predictive Analytics, Classification Algorithms

    ★ 4.7 (18K) · Intermediate · Course · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
1234…825

In summary, here are 10 of our most popular google machine learning courses

  • Preparing for Google Cloud Certification: Machine Learning Engineer: Google Cloud
  • Introduction to AI and Machine Learning on Google Cloud: Google Cloud
  • Machine Learning on Google Cloud: Google Cloud
  • Advanced Machine Learning on Google Cloud: Google Cloud
  • Machine Learning: DeepLearning.AI
  • The Nuts and Bolts of Machine Learning: Google
  • Machine Learning Operations (MLOps) on Google Cloud: Google Cloud
  • Machine Learning and Deep Learning for Software Engineers: Board Infinity
  • Data Engineering, Big Data, and Machine Learning on GCP: Google Cloud
  • Supervised Machine Learning: Regression and Classification : DeepLearning.AI

Frequently Asked Questions about Google Machine Learning

Google Machine Learning is a powerful tool developed by Google that uses artificial intelligence to create systems that can learn and improve from experience without being explicitly programmed. It focuses on developing computer programs that can access and use data to learn for themselves. This tool is used in various sectors of technology and business to analyze data and predict future trends. Someone interested in building Google Machine Learning skills must learn about algorithms, data analysis, programming, and statistics. ‎

  1. Machine Learning Engineer: These individuals design, implement, and deploy scalable machine learning solutions using platforms like TensorFlow. They might work on anything from refining search algorithms to designing new recommendation systems.

  2. Data Scientist: While closely related to ML engineers, data scientists often focus more on data exploration, hypothesis testing, and deriving insights from vast amounts of data. They might use Google's ML tools to analyze data and develop predictive models.

  3. Research Scientist (AI/ML): Especially prevalent at Google, these roles focus on advancing the frontier of machine learning. They'll develop new algorithms, refine existing ones, and work on practical and theoretical challenges in the field.

  4. ML Solutions Architect: These professionals might work with business stakeholders to design ML-based solutions for specific business problems, ensuring that the technical solution aligns with business goals.

  5. Technical Program Manager (Machine Learning): They oversee ML projects, ensuring resources, timelines, and stakeholders are aligned. They also work to bridge the gap between technical and non-technical teams.

  6. AI Product Manager: These individuals guide the strategy and development of AI-driven products, ensuring that they meet user needs while being technically feasible.

  7. Cloud Engineer specializing in ML services: With Google Cloud offering specialized services for machine learning (like AI Platform), there's demand for cloud engineers who specialize in setting up, deploying, and managing ML services on the cloud.

  8. Application Developer with ML focus: Developers who incorporate ML features into apps, websites, or other software products. They might use Google's pre-trained models or APIs, like Vision API or Natural Language API, for specific functionalities. ‎

To get started with Google Machine Learning on Coursera:

ML Foundations: Enroll in introductory machine learning courses on Coursera, focusing on core concepts and techniques. Google's Frameworks: Dive into courses that cover Google's ML tools, especially TensorFlow and Google Cloud ML Engine. Hands-on Learning: Choose courses that provide practical exercises utilizing Google's machine learning platforms and technologies. Earn Certifications: Complete course materials and assessments to obtain certificates, showcasing your proficiency in Google's ML ecosystem. ‎

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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