Diploma in Data Engineering for AI
High-throughput data pipelines, vector databases, lakehouse architecture, and real-time feature stores for enterprise AI.
Diploma in Data Engineering for AI is a self-paced online intermediate diploma in data-engineering from Altaris AI Academy. Tuition is $399 CAD (payable in three interest-free instalments), most students finish in about 6 months at 11 hours a week, and graduates receive a 18-credit, employer-verifiable diploma. 30-day money-back guarantee.
About this program
Learn to build the high-volume, low-latency data infrastructure that powers production AI systems. Master modern data lakehouses, streaming pipelines, vector indexing, and data quality frameworks.
Who this program is for
- →Working professionals moving into data-engineering roles
- →Analysts, developers, and product people leveling up on applied AI
- →Canadian residents seeking a verifiable diploma credential
Topics you'll cover
6 modules across 6 months — 28 lessons in total.
Full syllabus
Module 1 · Module 1: Modern Lakehouse & Columnar Storage▾
- L1Columnar formats (Parquet, Arrow) and lakehouse fundamentals
- L2Table formats: Apache Iceberg vs. Delta Lake table specifications
- L3High-performance SQL engines: Trino, DuckDB, and Snowflake
- L4Partitioning, compaction, and data maintenance strategies
- L5Module 1 Capstone: Lakehouse architecture for multi-terabyte analytics
Module 2 · Module 2: Streaming & Real-Time Data Ingestion▾
- L1Apache Kafka topologies, partition keys, and consumer groups
- L2Stream processing with Apache Flink and PySpark Streaming
- L3Change Data Capture (CDC) with Debezium and Postgres
- L4Backpressure handling and exactly-once processing semantics
- L5Module 2 Capstone: Real-time user event pipeline with sub-second ingestion
Module 3 · Module 3: Transformation, dbt & Data Orchestration▾
- L1Data transformation modeling with dbt and SQLMesh
- L2Workflow orchestration with Dagster and Apache Airflow
- L3Data contracts and automated schema migration validation
- L4Automated testing with Great Expectations and Soda Core
- L5Module 3 Capstone: Modular dbt transformation suite with automated test gates
Module 4 · Module 4: Vector Storage & Feature Stores at Scale▾
- L1Vector indexing mechanics (IVF-PQ, HNSW) at millions of embeddings
- L2Distributed vector databases: Qdrant, Milvus, and pgvector tuning
- L3Online/offline feature store architecture with Feast
- L4Data versioning and dataset snapshotting with DVC
- L5Module 4 Capstone: Scalable vector database cluster with automated re-indexing
Module 5 · Module 5: Data Governance, Security & PIPEDA Compliance▾
- L1Automated metadata discovery and data lineage with OpenLineage
- L2Column-level and row-level security masking for sensitive PII
- L3PIPEDA compliance: right to be forgotten and data retention policies
- L4Cost instrumentation and query performance optimization
- L5Module 5 Capstone: Auditable enterprise governance and anonymization engine
Module 6 · Module 6: Capstone Practicum & Infrastructure Defense▾
- L1Production deployment on cloud infrastructure
- L2Load testing and failure recovery benchmarking
- L3Live architectural review with principal data architects
What you'll be able to do
- ●Architect modern Iceberg and Delta Lakehouse data platforms
- ●Build real-time streaming pipelines with Apache Kafka and Flink
- ●Deploy scalable vector storage and semantic search indices
- ●Implement automated data quality testing with Great Expectations and dbt
- ●Build high-performance feature stores with Feast and Redis
- ●Ensure PIPEDA-compliant data lineage and access governance
Career paths after graduation
Frequently asked questions
How much does the Diploma in Data Engineering for AI cost?▾
Tuition is $399 CAD, paid once by invoice: apply online, we review your application and email an invoice, and your program opens once it is paid. A 30-day refund window applies from your enrollment date.
How long is the Diploma in Data Engineering for AI program?▾
Self-paced. Most students complete it in 6 months at roughly 7 hours per week, but you can go faster or slower — you keep lifetime access.
What are the prerequisites?▾
Proficiency in SQL (joins, window functions, CTEs) and Python; Understanding of relational databases and basic cloud infrastructure
What credential does the program award?▾
Graduates receive the Altaris AI Academy Diploma in data-engineering — a verifiable credential with a unique certificate number you can publish on LinkedIn and that any employer can verify at altarisai.org/verify. Employer acceptance is determined by each employer; it is not a regulated professional designation.
What is the refund policy?▾
Full refund within 30 days of enrollment, no questions asked. After day 30, prorated refunds are available per our Refund Policy.
Who teaches the program?▾
Working Canadian AI practitioners — not academics. Every module is built and reviewed by a lead instructor working in the field today.