Online Course – Certified Professional Certificate in Data Engineering from DeepLearning.AI

Learn the principles of effective data engineering. Develop your skills in the required data engineering area and explore how you can deliver real business value by implementing a set of principles and strategies for developing data systems.

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קורס אונליין - תעודה מקצועית מוסמכת בהנדסת נתונים של DeepLearning.AI

Professional Certificate

Beginners

No prior knowledge required

Time to complete the course

7-day free trial

No unnecessary risks

Skills you will acquire in the course

Translating stakeholder needs into system requirements and selecting the appropriate tools for building the system.
Building data pipelines for product recommendation on AWS – both in batches and live streaming.
Apply principles of good data architecture to assess the security, performance, reliability, and scalability of data systems on AWS.
Investigating different types of source systems and solving common connection problems.
Using tools like infrastructure and pipes as code to coordinate, automate, and manage data pipelines.
Designing data door and water door storage architectures for various cases.
Investigating the impact of data storage choices on query performance and costs.
Model and transform data for analytics and machine learning uses and compare central processing frameworks like Pandas to distributed processing frameworks like Spark.
Submitting the data to interested parties for business analysis and machine learning uses.

What you will learn in the course

Courses for which the course is suitable

Data Engineer
Data Analyst
Machine Learning Expert
Data Systems Developer
Data Project Manager
Business Analyst
Data Pipeline Developer
Data Architecture Specialist
Cloud Solutions Developer

Vocational Certificate – Series of 4 Courses

The DeepLearning.AI Data Engineering Professional Certificate is a comprehensive online program for data engineers and professionals looking to start or expand their careers.

Organizations of all sizes and industries are collecting and generating data at an ever-increasing rate. Within these organizations, every team, from management, sales and marketing, finance and operations, product and engineering, to customer service, can derive insights and value from organizational data. Whether the end use is data science, machine learning, or analytics, data engineering is what enables raw data to be transformed into value for the business. As a result, the role of a data engineer is one of the most in-demand careers in technology today.

During this program, you will learn the fundamentals of data engineering and gain practical experience in designing and implementing data architectures using AWS and open source tools.

Led by industry expert Joe Rice, co-author of Data Engineering Fundamentals, this certificate will give you the tools and knowledge to thrive in a high-demand field, with an emphasis on ingesting, processing, transforming, storing, and presenting data to interested parties to advance organizational and business goals. The hands-on labs were developed in collaboration with AWS and Factored.AI to provide you with authentic experience building data systems in the cloud.

With this certificate, you will have the tools to advance your career in data engineering.

Hands-on Learning Project

In this program, A:

You will translate stakeholder needs into system requirements and select the appropriate tools for building the system.
Build data pipelines for product recommendations on AWS – both in batches and live streaming.
Apply principles of good data architecture to assess the security, performance, reliability, and scalability of data systems on AWS.
You will explore different types of source systems and solve common connection problems.
You will use tools like Infrastructure and Pipes as Code to coordinate, automate, and monitor your data pipelines.
You will design data door and water door storage architectures for various cases.
You will explore the impact of data storage choices on query performance and costs.
You will model and transform data for analytics and machine learning uses and compare central processing frameworks like Pandas and distributed processing frameworks like Spark.
Submit your data to interested parties for business analysis and machine learning uses.

Details of the courses that make up the specialization

Introduction to Data Engineering

Duration: 17 hours

Understanding the data engineering lifecycle and basic details.
Collecting requirements from interested parties and developing them into system requirements.
Design and implement data pipelines in AWS kits.

Source, data acquisition and pipeline systems

Duration: 34 hours

Collecting requirements from interested parties and developing them into system requirements.
Implementing data ingestion processes based on packages and streams on AWS.
Integrating aspects of information security, data management, and DataOps into the data systems it provides.

Data storage and queries

Duration: 22 hours

Designing storage architectures for various scenarios, and selecting appropriate technologies to implement these architectures.
Practice common query patterns and identify ways to improve query performance and increase the value of your data systems.

Data Modeling, Transformation, and Servicing

Duration: 27 hours

Model and transform data based on the needs of interested parties to deliver business value.
Choosing the appropriate tools for data processing according to your architectural design.
Data processing for batch analytics and data pipelines for machine learning using distributed and non-distributed processing frameworks.

These courses offer a wide range of skills and knowledge acquisition in the field of data engineering, and are intended for anyone interested in developing their knowledge and skills in the field.