Python for Data and AI
2-3 weeksSkills You'll Build
Python programming fundamentalsPandas for data manipulationDatabase connectivity in PythonSQLAlchemy and ORMsData processing pipelines
Database Administrator → AI Data Architect
Database Administrator to AI Data Architect: From SQL to Vector DBs
Your database expertise is invaluable in AI. This path transforms your understanding of data storage, indexing, and query optimization into AI data architecture skills. Learn to build the data infrastructure that powers AI systems, from vector databases to feature stores.
4-6 months
Prerequisites
- Experience in database administration (SQL Server, PostgreSQL, MySQL, etc.)
- Strong SQL and query optimization skills
- Understanding of indexing and performance tuning
- Experience with data modeling and schema design
- Familiarity with backup, recovery, and high availability
Your Learning Path
ML Fundamentals and Data for AI
3-4 weeksSkills You'll Build
Machine learning core conceptsHow models use dataFeature engineering basicsData quality for AITraining data management
Vector Databases and Embeddings
4-5 weeksSkills You'll Build
Embeddings and vector representationsVector database architecture (pgvector, Pinecone, Weaviate)Indexing strategies for vectors (HNSW, IVF)Query optimization for similarity searchHybrid search combining SQL and vectors
RAG Data Architecture
3-4 weeksSkills You'll Build
Data pipelines for RAG systemsDocument processing and chunkingMetadata management for retrievalData versioning for AIScaling vector data infrastructure
AI Data Infrastructure
3-4 weeksSkills You'll Build
Feature stores for MLData pipelines for AI applicationsCaching strategies for AIMonitoring data qualityDatabase selection for AI workloads
Portfolio and Career Transition
2-3 weeksSkills You'll Build
Building AI data architecture portfolioShowcasing data infrastructure expertiseAI data architect interviewsNetworking in AI data communityPositioning DBA experience for AI