Explores Big Data generation, storage, processing, and dimensions, along with challenges in data analytics, cloud computing elasticity, and security.
Covers the fundamentals of data stream processing, including real-time insights, industry applications, and practical exercises on Kafka and Spark Streaming.
Introduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.
Covers Spark Data Frames, distributed collections of data organized into named columns, and the benefits of using them over RDDs.
