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Explores the landscape of big data, memory importance in online services, challenges faced by memory systems, emerging DRAM technologies, and storage-class memory.
Covers data science tools, Hadoop, Spark, data lake ecosystems, CAP theorem, batch vs. stream processing, HDFS, Hive, Parquet, ORC, and MapReduce architecture.
Explores quantum memories, including photon echoes, AFC quantum memory, and spin-wave storage, covering coherent light-matter interactions and optical data storage challenges.
Offers a comprehensive introduction to Data Science, covering Python, Numpy, Pandas, Matplotlib, and Scikit-learn, with a focus on practical exercises and collaborative work.
Explores Magnetic Random Access Memory (MRAM) advantages, spin transport, magnetoresistance, HDD reading-writing, and spin-polarized currents for memory writing.
