Course Outline
Introduction to Google Colab and Apache Spark
- Overview of Google Colab
- Introduction to Apache Spark
- Setting up Spark in Google Colab
Data Processing with Apache Spark
- Working with RDDs and DataFrames
- Loading and processing large datasets
- Using Spark SQL for querying structured data
Advanced Analytics with Spark
- Machine learning with Spark MLlib
- Performing real-time data analysis
- Distributed computing with Spark
Visualization and Collaboration in Google Colab
- Integrating Colab with popular visualization libraries
- Collaborative workflows with Colab notebooks
- Sharing and exporting results
Optimizing Big Data Workflows
- Tuning Spark for performance
- Optimizing memory and storage usage
- Scaling workflows for large datasets
Big Data in the Cloud
- Integrating Google Colab with cloud-based tools
- Using cloud storage for big data
- Working with Spark in distributed cloud environments
Case Studies and Best Practices
- Review of real-world big data applications
- Case studies using Apache Spark and Colab
- Best practices for big data analytics
Summary and Next Steps
Requirements
- Basic knowledge of data science concepts
- Familiarity with Apache Spark
- Python programming skills
Audience
- Data scientists
- Data engineers
- Researchers working with big data
Delivery Options
Private Group Training
Our identity is rooted in delivering exactly what our clients need.
- Pre-course call with your trainer
- Customisation of the learning experience to achieve your goals -
- Bespoke outlines
- Practical hands-on exercises containing data / scenarios recognisable to the learners
- Training scheduled on a date of your choice
- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from €4560 online delivery, based on a group of 2 delegates, €1440 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
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Public Training
Please see our public courses
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