About This Course

This comprehensive course is designed for individuals aiming to enhance their data engineering skills specifically focused on managing big data platforms like Hadoop, Spark, and Snowflake, and integrating machine learning operations using modern tools such as MLflow and Databricks. Students will also improve their project management and workflow skills through methodologies like Kaizen, DevOps, and DataOps.

What You Will Learn

• Optimize and manage data platforms like Hadoop, Spark, and Snowflake.
• Execute complex data analytics and machine learning tasks with Databricks.
• Enhance your Python data science skills using PySpark.
• Manage the full lifecycle of machine learning projects with MLflow.
• Implement effective workflow and project management methodologies in data engineering.

Prerequisites

No prerequisites are required for this course, making it accessible to beginners who are interested in data engineering.

Course Coverage

• Introduction to major big data platforms: Hadoop, Spark, Snowflake
• Databricks for data analytics and machine learning
• Python data science enhancement with PySpark
• End-to-end machine learning lifecycle management with MLflow
• Application of Kaizen, DevOps, and DataOps in project management

Target Audience

This course is ideal for current and aspiring data scientists and engineers, as well as software developers and engineers looking to expand their expertise in data management.

Real-World Applications

Upon completing this course, learners will be equipped to handle real-world data engineering challenges, optimize workflow efficiency in big data projects, and implement scalable data management solutions in a variety of industries.

Syllabus

• Module 1: Introduction to PySpark - Introduction to big data platforms, hands-on with PySpark and Spark SQL.
• Module 2: Understanding Snowflake - Detailed exploration of Snowflake, its architecture and operations including creating and managing data tables.
• Module 3: Working with Azure Databricks and MLFlow - Comprehensive guide to using Databricks for data processing and MLFlow for machine learning operations.
• Module 4: DataOps and Operations Methodologies - Application of Kaizen, DevOps, and DataOps in enhancing data operations and project management.