Covers the basics of image processing using Fiji software, focusing on managing files and applying filters.
Covers data science tools, Hadoop, Spark, data lake ecosystems, CAP theorem, batch vs. stream processing, HDFS, Hive, Parquet, ORC, and MapReduce architecture.
Covers the fundamentals of file systems, focusing on managing persistent blocks efficiently and implementing file system APIs.
Covers data wrangling techniques using Hadoop, focusing on row versus column-oriented databases, popular storage formats, and HBase-Hive integration.
Introduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.
