Data Pipelines Courses and Certifications

Coursera Career Certificate

AI Model Development & Deployment

Unlock the skills to architect, optimize, and deploy production-ready machine learning systems with hands-on experience in PyTorch, TensorFlow, FastAPI, and AWS SageMaker.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course

Starweaver

GenAI Data Engineering and RAG Systems

Master advanced data engineering techniques to build enterprise-grade RAG systems that transform raw data into intelligent, context-aware AI applications with vector databases.

• Coursera
• 6 hours 49 minutes
• Self-Paced
• Paid Course

Coursera Career Certificate

Gradient to Production: MLOps & Model Serving

Master the full MLOps stack—from data pipelines to model deployment—using FastAPI, Docker, Kubernetes, and Airflow, and learn to ship, monitor, and maintain ML systems in production.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 15 courses

Packt

Building Modern Data Applications Using Databricks Lakehouse

Master Databricks Lakehouse to build scalable data applications with Delta Live Tables, Unity Catalog governance, and Terraform deployment for production-ready pipelines.

• Coursera
• 11 hours 13 minutes
• Self-Paced
• Paid Course

Coursera

Map Data Flows Fast

Master systematic visualization of data pipelines through comprehensive flow diagrams that map sources, transformations, and destinations for better engineering decisions.

• Coursera
• 1 hour 18 minutes
• Self-Paced
• Paid Course

Coursera Career Certificate

Geospatial Visualization, Cloud & Real-Time Pipelines

Master geospatial visualization, cloud computing, and real-time pipelines—build ETL workflows, interactive maps, PostGIS queries, and live GPS dashboards for production-ready GIS systems.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 7 courses

Coursera Career Certificate

Pipeline Architects: Data Engineering to Lakehouse

Master end-to-end data engineering, from ingestion to lakehouse delivery, using Python, SQL, Airflow, dbt, Snowflake, Kafka, and Delta Lake to build production-ready pipelines at enterprise scale.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 10 courses

Coursera Career Certificate

Vision & Audio AI Systems

Master production-ready AI systems that unify visual and audio data through advanced multimodal techniques, ETL pipelines, fusion algorithms, and transformer fine-tuning.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 2 courses

Coursera

Fine-tune Multimodal Models with Transfer Learning

Master transformer-based multimodal AI systems integrating text and image processing with PyTorch/TensorFlow, implementing fusion mechanisms and advanced fine-tuning strategies.

• Coursera
• 1 hour 45 minutes
• Self-Paced
• Paid Course

Coursera

Debug Python Pipelines: Root Causes

Master systematic debugging approaches to diagnose Python pipeline failures, analyze stack traces, and resolve multithreading issues in production environments.

• Coursera
• 1 hour 42 minutes
• Self-Paced
• Paid Course

Coursera

Design Real-Time Architectures with Spark & Kafka

Master real-time data pipelines using Apache Spark & Kafka for scalable streaming systems with fault tolerance, performance tuning, and production deployment strategies.

• Coursera
• 3 hours 39 minutes
• Self-Paced
• Paid Course

Coursera

AI Data: Analyze, Govern, Plan

Master AI data pipeline diagnostics, governance standards, and workflow planning through real-world scenarios including GDPR compliance and bottleneck resolution.

• Coursera
• 2 hours 13 minutes
• Self-Paced
• Paid Course

Google BigQuery for Data and ML Engineers

Master BigQuery's serverless architecture, advanced SQL, and ML capabilities to build efficient data pipelines and deploy models for real-world data engineering projects.

• Coursera
• 6 hours 2 minutes
• Self-Paced
• Paid Course

Edureka

Data Engineering Workflow Orchestration with Airflow

Master Apache Airflow to design, build, and deploy production-ready data pipelines with operators, sensors, TaskFlow API, CI/CD integration, and advanced DAG optimization techniques.

• Coursera
• 9 hours 46 minutes
• Self-Paced
• Paid Course

Confluent: Clickstream Data Analysis Pipeline Using ksqlDB

This is a self-paced lab that takes place in the Google Cloud console. This lab will cover how to create a clickstream data analysis pipeline using ksqlDB.

• Coursera
• 1 hour
• Self-Paced
• Paid Course