Overview

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One plan covers every Professional Certificate on Coursera.

Build practical expertise in AI-powered data engineering using Snowflake, generative AI, and modern cloud data architecture. You will learn how data engineers design, build, improve, and manage intelligent data pipelines that support analytics, AI applications, and enterprise decision-making. You will begin by exploring the modern data engineering landscape, the role of generative AI, and Snowflake as a cloud data platform. Using the GlobalMart environment, you will build basic pipelines and use AI to understand datasets, generate SQL, explain pipeline code, assess data quality, and support schema mapping. You will also organise multi-source data through Bronze, Silver, and Gold layers and create reliable transformation and documentation workflows. You will then explore intelligent data access using embeddings, semantic search, and retrieval-augmented generation. You will combine structured and unstructured data, build a RAG assistant for data knowledge, and enable natural language analytics over trusted data. You will also prepare pipelines for production by implementing error handling, retry logic, logging, monitoring, evaluation, governance, access control, and orchestration with Snowflake Tasks. By the end of this course, you will be able to: - Explain modern data engineering concepts and the role of generative AI. - Build and manage data pipelines using Snowflake. - Organise data using Bronze, Silver, and Gold architecture. - Use AI for schema understanding, transformation, profiling, and quality checks. - Generate and explain SQL and pipeline code using generative AI. - Build semantic search and RAG workflows for enterprise data. - Combine structured and unstructured data for intelligent analytics. - Implement monitoring, governance, evaluation, and workflow orchestration. - Deploy a production-ready AI-enhanced data engineering solution. Designed for aspiring data engineers, data analysts, cloud professionals, software developers, and students entering the data field, the course prepares you to build reliable, scalable, and intelligent data solutions using Snowflake and generative AI.

Syllabus

Foundations of AI-Enhanced Data Engineering

Discover the foundations of AI-enhanced data engineering, Snowflake, and Generative AI-driven workflows. Explore basic data pipelines, natural language interactions, AI-assisted profiling, and responsible AI practices. Develop the knowledge needed to create intelligent, reliable, and scalable data engineering solutions.

AI-Enhanced Data Ingestion, Transformation and Quality

Apply AI-assisted techniques to build reliable ingestion workflows and prepare trusted multi-source data. Explore schema mapping, layered storage, transformation, quality checks, and automated documentation. Create accurate, scalable, and AI-ready Bronze, Silver, and Gold data pipelines.

Intelligent Data Access with Generative AI

Analyze intelligent data access using Generative AI, embeddings, semantic search, and RAG. Combine structured and unstructured data through trusted retrieval and natural language analytics. Build AI-powered solutions that deliver accurate, relevant, and context-aware insights.

Production, Governance, and Enterprise Deployment

Create production-ready AI-enhanced data workflows using orchestration, governance, monitoring, and evaluation. Strengthen operational resilience through access control, error handling, automation, and AI output validation. Deploy secure, scalable, and trustworthy data engineering solutions for enterprise environments.