Course Outline

Advanced Analytics with Spark

Big Data in the Cloud

Case Studies and Best Practices

Data Processing with Apache Spark

Introduction to Google Colab and Apache Spark

Optimizing Big Data Workflows

Summary and Next Steps

Visualization and Collaboration in Google Colab

  • Integrating Colab with popular visualization libraries
  • Collaborative workflows with Colab notebooks
  • Sharing and exporting results
  • Integrating Google Colab with cloud-based tools
  • Using cloud storage for big data
  • Working with Spark in distributed cloud environments
  • Machine learning with Spark MLlib
  • Performing real-time data analysis
  • Distributed computing with Spark
  • Overview of Google Colab
  • Introduction to Apache Spark
  • Setting up Spark in Google Colab
  • Review of real-world big data applications
  • Case studies using Apache Spark and Colab
  • Best practices for big data analytics
  • Tuning Spark for performance
  • Optimizing memory and storage usage
  • Scaling workflows for large datasets
  • Working with RDDs and DataFrames
  • Loading and processing large datasets
  • Using Spark SQL for querying structured data

Requirements

Audience

  • Basic knowledge of data science concepts
  • Familiarity with Apache Spark
  • Python programming skills
  • Data scientists
  • Data engineers
  • Researchers working with big data
 14 Hours

Number of participants


Price per participant

Testimonials (5)

Upcoming Courses

Related Categories