Course Outline
Introduction to Big Data Ecosystems
- Overview of big data technologies and architectural designs
- Comparison of batch processing versus real-time processing
- Strategies for scalable data storage
Advanced Data Processing with Apache Spark
- Optimising Spark jobs for peak performance
- Advanced transformations and actions
- Implementation of structured streaming
Machine Learning at Scale
- Techniques for distributed model training
- Hyperparameter tuning across large datasets
- Deploying models within big data environments
Deep Learning for Big Data
- Integration of TensorFlow and PyTorch with Spark
- Building distributed deep learning training pipelines
- Applications in image, text, and time-series analysis
Real-Time Analytics and Data Streaming
- Utilising Apache Kafka for streaming data ingestion
- Exploration of stream processing frameworks
- Monitoring and alerting mechanisms in real-time systems
Data Governance, Security, and Ethics
- Data privacy and compliance requirements
- Access control and encryption in big data systems
- Ethical considerations in large-scale analytics
Integrating Big Data with Business Intelligence
- Data visualisation and dashboarding for big data
- Connecting big data pipelines to BI tools
- Driving business outcomes through advanced analytics
Summary and Next Steps
Requirements
- A robust understanding of data analysis and statistical modelling concepts.
- Proficiency in data processing tools and programming languages such as Python, R, or Scala.
- Familiarity with distributed computing frameworks such as Hadoop or Spark.
Target Audience
- Data scientists seeking to master large-scale data processing and predictive analytics.
- Senior analysts looking to design and implement advanced analytical workflows.
- R&D professionals focused on developing innovative, data-driven solutions.
Testimonials (3)
Learning that the QGIS and a tool that can used by other different professionals such land survey
Bame Duncan Koko - Bentel Technologies (Pty) Ltd
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How to use open satellites data for real applications
Tshering Dorji - Druk Holding and Investments
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Hands-on examples allowed us to get an actual feel for how the program works. Good explanations and integration of theoretical concepts and how they relate to practical applications.
