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Starts 3 June 2025 14:35

Ends 3 June 2025

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Machine Learning and Big Data Magic with Node.js and Google Cloud

Explore machine learning APIs for image analysis, text processing, and speech recognition in Node.js. Learn to integrate Google Cloud services for powerful AI capabilities in your applications.
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Overview

Explore machine learning APIs for image analysis, text processing, and speech recognition in Node.js. Learn to integrate Google Cloud services for powerful AI capabilities in your applications.

Syllabus

  • Introduction to Machine Learning and Big Data
  • Overview of machine learning concepts
    Introduction to big data
    Applications of AI and big data in contemporary software
  • Setting Up the Environment
  • Installing and configuring Node.js
    Overview of Google Cloud platform
    Setting up Google Cloud environment and SDK
  • Understanding Machine Learning APIs
  • Introduction to Google Cloud AI APIs
    Accessing and using APIs with Node.js
    Authentication and API key management
  • Image Analysis with Node.js and Google Cloud
  • Using the Vision API for image analysis
    Building a Node.js application for image recognition
    Advanced features of the Vision API
  • Text Processing with Machine Learning
  • Using Natural Language API for entity and sentiment analysis
    Implementing text processing in Node.js
    Advanced NLP features and customization
  • Speech Recognition and Processing
  • Introduction to Speech-to-Text API
    Building a Node.js application for speech recognition
    Enhancing applications with text-to-speech capabilities
  • Integrating AI Services into Web Applications
  • Best practices for integrating AI services in Node.js applications
    Handling data and performance considerations
    Deploying AI-enabled applications on Google Cloud
  • Working with Big Data in Google Cloud
  • Introduction to BigQuery and data warehousing
    Using Node.js to query and analyze large datasets
    Integrating BigQuery into applications for real-time analytics
  • Security and Ethical Considerations
  • Secure access and data management
    Privacy, fairness, and bias in AI applications
  • Final Project
  • Designing a comprehensive AI-enabled application
    Integrating multiple Google Cloud products and services
    Presentation and peer review of projects
  • Course Review and Future Directions
  • Summary of key concepts
    Emerging trends in AI and big data
    Resources for further learning and exploration

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