Distributed Computing: Challenges and Solutions

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Handling Data: Data Models and Wrangling

Explores data handling fundamentals, including models, sources, and wrangling, emphasizing the importance of understanding and addressing data problems.

Image Processing Techniques: Seam Carving and Pixel Manipulation

Discusses image processing techniques, focusing on seam carving and pixel manipulation in Python programming.

Data Warehouses and Data Lakes

Covers data warehouses, data lakes, OLTP vs. OLAP, data quality, and the Data Lakehouse concept.

Python Programming: Dictionaries and Classes

Introduces Python programming concepts, focusing on dictionaries and classes, including their definitions, usage, and practical examples.

Advanced Types in C: Enums, Typedefs, and Structs

Discusses advanced types in C, including enumerated types, typedefs, and structures, with practical examples to illustrate their usage.

Data Warehouses: Introduction and Challenges

Covers the introduction and challenges of data warehouses, including integrating data, managing metadata, and optimizing query performance.

Analytics on Data at Rest and Data in Motion

Explores combining data at rest with data in motion, emphasizing the Lambda architecture complexities and quality assessment of streams and batches.

Data Science for Engineers: Part 2

Explores data manipulation, exploration, and visualization in data science projects using Python.