ARCH-492: Architecting Cloudera Edge to AI Course Overview

Prerequisites for ARCH-492: Architecting Cloudera Edge to AI Course

To ensure you gain the maximum benefit from the ARCH-492 course, it is recommended that participants have the following foundational knowledge and experience:

• Basic Understanding of Big Data Technologies:
  • Familiarity with popular Big Data and streaming technologies such as HDFS, Spark, Kafka, Hive/Impala.
• Experience with Data Formats and Relational Databases:
  • Knowledge of various data formats and experience with relational database management systems.
• Conceptual Knowledge of Data Processing:
  • Understanding of the basic concepts of batch and stream data processing.
• Technical Background:
  • Experience in roles such as architects, developer team leads, big data developers, data engineers, senior analysts, dev ops admins, or machine learning developers.
• General IT and Software Development Knowledge:
  • Basic awareness of IT infrastructure, software architecture, and security principles.

Please note that detailed API-level knowledge is not necessary, as the focus of the course will be on designing and architecting solutions rather than programming.

If you meet these prerequisites, you're ready to take the next step in advancing your skills in architecting edge to AI applications with Cloudera Data Platform

Target Audience for ARCH-492: Architecting Cloudera Edge to AI

ARCH-492: Architecting Cloudera Edge to AI is a 4-day advanced workshop focused on building big data architecture for edge to AI applications using Cloudera Data Platform.

• Architects
• Developer Team Leads
• Big Data Developers
• Data Engineers
• Senior Analysts
• DevOps Administrators
• Machine Learning Developers
• Professionals with knowledge in HDFS, Spark, Kafka, Hive/Impala
• Those interested in designing and developing big data and streaming applications on CDP

Learning Objectives - What you will Learn in this ARCH-492: Architecting Cloudera Edge to AI?

1. Course Introduction: The ARCH-492: Architecting Cloudera Edge to AI course is a comprehensive 4-day workshop designed to equip participants with advanced knowledge and practical skills for designing scalable, fault-tolerant, and secure big data architectures, extending from edge devices to AI applications.

2. Learning Objectives and Outcomes:

• Understanding Cloudera Data Platform (CDP): Grasp the fundamentals and advanced features of the Cloudera Data Platform.
• Big Data Architecture: Learn the principles of big data architecture including data formats, transformations, and transactions.
• Scalable Applications: Develop the ability to design applications that can scale out efficiently using Spark, HDFS, Kafka, and other technologies.
• Fault-Tolerant Systems: Understand and implement principles of fault-tolerant distributed systems, including replications and group consistency.
• Security and Privacy: Learn to implement robust security architectures using tools like Knox and Ranger, including setting security policies and conducting threat analysis.
• Real-time and Batch Processing: Gain insights into real-time, near real-time, and batch processing, with an emphasis on data consistency and processing guarantees.
• Machine Learning Integration: Learn to integrate and optimize machine learning pipelines within big data architectures.