Concept
Hayes AT command set
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Introduces collaborative data science tools like Jupyter notebooks, Docker, and Git, emphasizing data versioning and containerization.
Introduction to Data Stream Processing
Covers the fundamentals of data stream processing, including tools like Apache Storm and Kafka, key concepts like event time and window operations, and the challenges of stream processing.
General Introduction to Big Data
Covers data science tools, Hadoop, Spark, data lake ecosystems, CAP theorem, batch vs. stream processing, HDFS, Hive, Parquet, ORC, and MapReduce architecture.
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Covers the basics of Spark DataFrames, their advantages, performance comparison with RDDs, and practical demos.
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Covers collaborative data science tools, big data concepts, Spark, and data stream processing, with tips for the final project.
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Covers best practices and guidelines for big data, including data lakes, architecture, challenges, and technologies like Hadoop and Hive.
Understanding ROC Curves
Explores the ROC curve, True Positive Rate, False Positive Rate, and prediction probabilities in classification models.