657: How to Learn Data Engineering
Super Data Science: ML & AI Podcast with Jon Krohn
00:00
Transitioning from Data Analyst to Data Engineer in AI/ML
The chapter explores the appeal of data engineering for individuals transitioning from data analytics to AI/ML, emphasizing the need for coding languages like Python and SQL. It delves into the importance of understanding machine learning processes and collaborating effectively with data scientists when creating data pipelines. The discussion also covers various data engineering tools, such as FastAPI, MongoDB, Kafka, Spark, Snowflake, and Databricks, highlighting their significance in the industry and the evolving role of data engineers towards analytics engineering.
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