The two areas of specialization are data engineering (DE) and analytics technologies (AT). The data engineering specialization delves deeper into data warehousing, the creation of distributed web systems, and building generative AI applications such as NLP, LLM, LangChain, and LLM agents, which are the main differences between the two specializations.  

Common core

• DATA 220 – Mathematical Methods for Data Analytics
• DATA 228 – Big Data Technologies and Applications
• DATA 230 – Business Intelligence and Data Visualization
• DATA 245 – Machine Learning Technologies 
• DATA 255 – Deep Learning Technologies

Analytics Technologies

• DATA 225 – Database Systems for Analytics
• DATA 240 – Data Mining and Analytics
• DATA 265 – Large Language Model Applications

Data Engineering

• DATA 226 – Data Warehouse and Pipeline
• DATA 236 – Distributed Systems for Data Engineering
• DATA 266 – Generative Model Applications

According to the Silicon Valley survey, data engineering is one of the fastest-growing tech-oriented occupations recently. It was highlighted in the 2020 LinkedIn U.S. Emerging Jobs Report as one of the 15 most outstanding emerging jobs of the past five years. Data engineers play a pivotal role in bridging the gap between traditional data analytics and science positions and software and application developers.

Data engineers are crucial in managing and organizing data, creating systems to efficiently gather, store, and process large volumes of information. This field offers a dynamic career path, ideal for those who enjoy technology, continuous learning, and want to make a significant impact using data as oil across various industries.

View our course offerings in the curriculum. 

Source: https://www.interviewquery.com/p/job-market-update-january-2023