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Section 04 · A. Build the foundation

SQL & Data Engineering Essentials

Almost every AI/ML/data role runs a live SQL round: pull, join, aggregate and window over data — with correct grain and NULL awareness.

24topics126interview Q&A99practice problems24videos

Topics in this section

Each topic pairs a video with the theory, interview questions & answers, and practice problems whose solutions unlock as you complete them.

04.1
Core SQL — SELECT, filter, sort & clause order
Video7 Q&A5 practice20 min
04.2
JOINs & relationships
Video7 Q&A5 practice20 min
04.3
Aggregation & GROUP BY / HAVING
Video5 Q&A4 practice22 min
04.4
Window functions
Video5 Q&A4 practice26 min
04.5
CTEs & subqueries
Video5 Q&A4 practice22 min
04.6
NULLs, dedupe & data quality
Video5 Q&A4 practice22 min
04.7
Data engineering — ETL/ELT, pipelines & performance
Video5 Q&A4 practice24 min
04.8
Database design & normalisation
Video5 Q&A4 practice22 min
04.9
Indexing & query performance
Video5 Q&A4 practice24 min
04.10
Transactions, ACID & concurrency
Video5 Q&A4 practice24 min
04.11
NoSQL, warehouses & big data
Video5 Q&A4 practice24 min
04.12
Analytics engineering & SQL for ML
Video5 Q&A4 practice24 min
04.13
Advanced SQL patterns
Video5 Q&A4 practice24 min
04.14
Query planning & optimization internals
Video5 Q&A4 practice24 min
04.15
Apache Spark & distributed compute
Video5 Q&A4 practice26 min
04.16
Streaming data systems
Video5 Q&A4 practice26 min
04.17
Dimensional modeling deep-dive
Video5 Q&A4 practice24 min
04.18
Lakehouse table formats
Video5 Q&A4 practice24 min
04.19
Orchestration & DataOps
Video5 Q&A4 practice24 min
04.20
Data governance, security & privacy
Video5 Q&A4 practice24 min
04.21
Change data capture & replication
Video5 Q&A4 practice24 min
04.22
Real-time OLAP engines
Video5 Q&A4 practice24 min
04.23
Data pipelines for AI & LLM systems
Video7 Q&A5 practice26 min
04.24
Cost & performance at scale (FinOps for data)
Video5 Q&A4 practice24 min