Description
Applied Python Data Engineering Specialization, a practical Python data engineering training course published by Coursera Academy. Learn how to use data engineering to use big data for business strategy, data analysis, or machine learning and artificial intelligence. By completing this course, you’ll have the knowledge and skills to build efficient data pipelines, manage advanced platforms like Hadoop, Spark, Snowflake, Databricks, and Kubernetes, and tell stories with data through visualization. you will define You will explore big data concepts, distributed computing with Spark, Snowflake architecture, Databricks machine learning capabilities, Python techniques for data visualization, and critical methodologies such as DataOps. This course is designed for software engineers, developers, researchers and data scientists who want to strengthen their expertise in data science or machine learning, as well as for professionals interested in pursuing a career as a data-driven software engineer. A data scientist, or a data engineer working in the cloud, machine learning, business intelligence, or other fields. This specialization represents a project focused on using Databricks’ API to replicate an existing project. It provides hands-on experience working with Databricks to build a portfolio-ready data solution. You will use Python for a variety of data engineering tasks.
What you will learn
- Build scalable data pipelines (Hadoop, Spark, Snowflake, Databricks) for efficient data management.
- Creating machine learning workflows (PySpark, MLFlow) in Databricks for integrated model development and deployment.
- Implement DataOps/DevOps to streamline data engineering processes.
- Shaping and communicating data-driven insights and narratives through impactful visualizations with Python and data storytelling
Specifications of the Applied Python Data Engineering Specialization course
- Publisher: Coursera
- teacher : Kennedy Behrman
- English language
- Education level: Intermediate
- Number of courses: 3
- Duration of training: 5 months including 10 hours of work per week
Chapters of the Applied Python Data Engineering Specialization course
Course prerequisites
- Experience in working with Python, Git for version control, Docker for containerization and Kubernetes for deployment and scaling; also a strong foundation in linear algebra and statistics.
Pictures
Sample video
Installation guide
After Extract, view with your favorite Player.
English subtitle
Quality: 720p
download link
Spark, Hadoop, and Snowflake for Data Engineering
Virtualization, Docker, and Kubernetes for Data Engineering
Data Visualization with Python
File(s) password: www.downloadly.ir
Size
2.04 GB
Be the first to comment