Covers the basics of scientific programming for engineers, emphasizing the importance of GIT for collaborative work and providing insights into challenges in scientific software development.
Explores data handling fundamentals, including models, sources, and wrangling, emphasizing the importance of understanding and addressing data problems.
Discusses advanced Spark optimization techniques for managing big data efficiently, focusing on parallelization, shuffle operations, and memory management.
