This course guides you through the process of transforming raw financial data into a clean, trustworthy dataset using Python and pandas. You’ll begin by exploring how to load data into a notebook environment and conduct quick inspections to identify structural issues, formatting inconsistencies, unusual numeric patterns, and missing values. Building on these observations, you’ll apply essential cleaning techniques used by analysts every day—fixing data types, standardizing text categories, resolving or documenting missingness, and removing duplicates. Through guided walkthroughs, hands-on prac

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Advanced Swift Techniques for iOS & Networking

In this course, you will master advanced networking techniques and Swift programming strategies for iOS development. You'll explore how to efficiently fetch and manage network data, build dynamic and interactive graphs using Swift Charts, and implement powerful data pipelines with Combine. These skills are crucial for developing data-driven, high-performance iOS applications. Throughout the course, you'll gain hands-on experience with real-world challenges like managing network data asynchronously and visualizing it with Swift Charts. By mastering these advanced techniques, you'll be able to

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Data Engineering with Delta Lake on Databricks

Build production-ready data pipelines using Delta Live Tables and the Medallion Architecture on Databricks. This hands-on course teaches you to design, implement, and monitor ETL workflows that transform raw data into reliable, business-ready datasets through a structured bronze-silver-gold layering pattern. This course is primarily aimed at first- and second-year undergraduates interested in engineering or science, along with professionals with an interest in programming. You will start by mastering DLT fundamentals — declarative pipeline syntax in both SQL and Python, streaming ingestion w

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