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Advanced Architectures Data, AI, and Modernization

Packt via Coursera

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Overview

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Explore advanced topics in solution architecture, including data engineering, machine learning, generative AI, legacy modernization, and essential soft skills for career growth. Prepare to lead complex projects and drive innovation in your organization. This course covers the latest advancements in data engineering, machine learning, and generative AI architectures, providing learners with the expertise to design intelligent and data-driven solutions. It also addresses strategies for modernizing legacy systems and creating comprehensive architecture documentation. The course concludes with a focus on the soft skills that distinguish successful solutions architects, empowering you to excel in dynamic technical environments. Learners progress through a series of in-depth modules that combine theoretical frameworks with practical architectural guidance. The course emphasizes clarity, real-world relevance, and actionable insights to support professional development. This course is part three of a three-course Specialization designed to build a complete and cohesive understanding of the subject. While it offers valuable skills on its own, you'll gain the most benefit by progressing through all three courses as a structured learning journey. This course is based on Solutions Architect's Handbook, by Saurabh Shrivastava and Neelanjali Srivastav. Packt is one of the world's most prolific publishers of cutting-edge technical content. For over two decades we've made it our mission to curate and publish the knowledge of only the very best technical experts. We focus on real-world courses that help our customers get the job done, with coverage that extends across a wide range of established and cutting-edge technical topics. If you're an individual or an organisation that embraces learning by doing, Packt is the perfect fit for you.

Syllabus

  • Data Engineering for Solution Architecture
    • This module covers the fundamentals of data engineering, including big data architecture, data ingestion, storage options, and processing technologies. Learners will gain insights into choosing the right tools for data pipelines and understanding the differences between relational and non-relational databases. The module also explores modern data storage solutions like data lakes and lakehouses.
  • Machine Learning Architecture
    • This module covers key aspects of building and managing machine learning architectures, including model pipelines, cloud integration, evaluation techniques, and interpretability. Learners will gain an understanding of how to design scalable and efficient ML systems while addressing real-world challenges like overfitting and deployment.
  • Generative AI Architecture
    • This module provides an in-depth exploration of generative AI architecture, covering core components like FMs, GANs, VAEs, and transformer models. It also explains how to implement and optimize these systems for real-world applications, including cloud integration and avoiding common pitfalls like model hallucinations.
  • Rearchitecting Legacy Systems
    • This module explores the challenges of maintaining legacy systems, strategies for modernization, and cloud migration techniques. Learners will gain insights into security risks, modernization approaches, and the benefits of cloud-based solutions for system upgrades. The content equips professionals with practical knowledge to make informed decisions about system rearchitecture.
  • Solution Architecture Document
    • This module provides an in-depth overview of Solution Architecture Documents, covering their purpose, structure, and key sections such as business context, data architecture, and appendices. Learners will gain the skills to create and structure SADs effectively for various project types, including new product development, modernization, and cloud migration.
  • Learning Soft Skills to Become a Better Solutions Architect
    • This module focuses on developing essential soft skills for solutions architects, including communication, adaptability, and leadership. Learners will explore how to take ownership, engage in hands-on problem-solving, and align with organizational goals. By the end, they will be equipped to lead effectively in dynamic technical environments.

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Packt - Course Instructors

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