Cloudera Data Platform: Designing Edge to AI Applications on Hybrid Data Cloud

Cloudera Data Platform: Designing Edge to AI Applications on Hybrid Data Cloud is a specialized training course designed to provide professionals with the expertise to architect and implement end-to-end Edge to AI solutions across hybrid data cloud environments. This course covers leveraging Cloudera’s cutting-edge tools to build scalable applications that span from edge devices to AI models deployed in the cloud. Learn how to integrate data from IoT devices, process data in real-time, and deploy machine learning models using the Cloudera Data Platform (CDP). You will also explore how to manage data flow, optimize edge computing resources, and ensure seamless hybrid cloud integration for powerful AI-driven solutions.

Schedule & Fee
Learning Objectives
Prerequisites
Target Audience
Course Modules
FAQs

Schedule	Learners	Course Fee (Incl. of all Taxes)	Register Your Interest
December 22^nd - 25^th 09:00 AM - 05:00 PM (CST) Live Virtual Classroom (Duration : 32 Hours) Guaranteed-to-Run		10% Off $1,600 $1,440 Fast Filling! Hurry Up.
December 27^th - 04^th 09:00 AM - 05:00 PM (CST) Live Virtual Classroom (Duration : 32 Hours)		10% Off $1,600 $1,440
January 05^th - 08^th 09:00 AM - 05:00 PM (CST) Live Virtual Classroom (Duration : 32 Hours)		20% Off $1,600 $1,280
January 10^th - 18^th 09:00 AM - 05:00 PM (CST) Live Virtual Classroom (Duration : 32 Hours)		20% Off $1,600 $1,280
January 12^th - 15^th 09:00 AM - 05:00 PM (CST) Live Virtual Classroom (Duration : 32 Hours)		20% Off $1,600 $1,280
January 19^th - 28^th 06:00 AM - 10:00 PM (CST) Live Virtual Classroom (Duration : 32 Hours)		20% Off $1,600 $1,280
January 26^th - 29^th 09:00 AM - 05:00 PM (CST) Live Virtual Classroom (Duration : 32 Hours) Guaranteed-to-Run		20% Off $1,600 $1,280

Course Prerequisites

Understanding of cloud computing concepts (AWS, Azure, Google Cloud, or hybrid environments)
Familiarity with machine learning and AI concepts
Basic knowledge of big data technologies and Hadoop ecosystem
Experience with distributed systems and data management tools (HDFS, YARN, Kafka, etc.)
Prior exposure to Cloudera products or similar big data platforms is helpful but not required

Learning Objectives

By the end of this course, participants will be able to:

Design and implement scalable Edge to AI architectures in hybrid cloud environments
Integrate and process real-time data from IoT devices and edge devices into the cloud
Build and deploy machine learning models for both edge and cloud-based applications
Ensure robust data security, governance, and privacy across distributed systems
Monitor and optimize the performance of Edge to AI solutions in Cloudera Data Platform
Scale and manage applications for maximum efficiency in a hybrid data cloud environment

Target Audience

This course is ideal for professionals involved in building AI-powered applications, managing data in hybrid cloud environments, and leveraging edge-to-cloud solutions. The target audience includes:

Solution Architects
Cloud Engineers
Data Engineers
Machine Learning Engineers
Data Scientists
IoT and Edge Computing Professionals
AI Application Developers
IT Infrastructure and Cloud Operations Teams

Course Modules

Introduction to Edge to AI Architecture on Hybrid Data Cloud
- Overview of Edge to AI concept and its importance in modern cloud solutions
- Key components of Cloudera Data Platform and Hybrid Data Cloud architecture
- Understanding the role of edge devices, cloud, and AI in hybrid environments
Building Hybrid Data Clouds with Cloudera
- Configuring and managing hybrid data cloud environments using CDP
- Integration of on-premise and cloud systems for seamless data flow
- Best practices for building and managing distributed hybrid cloud infrastructures
Data Collection and Management from Edge Devices
- Collecting data from IoT sensors and edge devices using Cloudera DataFlow
- Processing and transforming data from edge devices in real-time
- Managing data storage, retrieval, and synchronization between edge and cloud
Processing Real-Time Data at the Edge with Cloudera
- Using Cloudera tools like Apache Flink and Kafka for real-time data processing
- Implementing real-time analytics and monitoring at the edge
- Ensuring high-performance data pipelines for edge-to-cloud communication
Designing AI Models for Edge and Cloud Deployment
- Developing AI and machine learning models using Cloudera Data Science Workbench (CDSW)
- Training models with edge-based data and scaling model training in the cloud
- Deploying machine learning models to edge devices for on-premise AI processing
Data Governance, Security, and Privacy in Hybrid Cloud
- Managing data privacy, security, and governance across edge and cloud environments
- Applying regulatory compliance frameworks (GDPR, CCPA) for hybrid architectures
- Data encryption, access control, and secure deployment of AI models
Monitoring and Optimizing Edge to AI Applications
- Monitoring edge-to-cloud applications in real-time using Cloudera tools
- Identifying bottlenecks and optimizing data flows for performance
- Enhancing scalability and availability of AI applications across hybrid cloud systems
Scaling Edge to AI Solutions on Cloudera
- Techniques for scaling applications and workloads from edge to cloud
- Implementing auto-scaling mechanisms and resource management strategies
- Utilizing Cloudera's advanced cloud management tools for efficient resource allocation

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What Our Learners Are Saying

The training, courseware, and lab experience were insightful and valuable. Keep up the great work and learning experience!

Nitish A. Anand – Accenture

Course: SC-200: Microsoft Security Operations Analyst
Date: 15th Jan 2025

The instructor was professional and very content.

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Course: MD-102: Microsoft 365 Endpoint Administrator
Date: 20th Dec 2024

The instructor was so knowledgeable & humble. Rare to find someone so confident but so down to earth these days. So appreciative to him.”

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Course: AZ-700: Designing and Implementing Microsoft Azure Networking Solutions
Date: 31st July 2024

Instructor is experienced and knowledgeable in guiding.

Dharshini Mahalaxmi – Dr. MGR Education and Research Institute, Chennai, India

Course: SC-300: Microsoft Identity and Access Administrator
Date: 4th May 2024