Certified Cloud AI Solutions Architect (CCASA) AI/ML Overview

(Beginner/Intermediate) Ready to architect the future with AI in the cloud? Buckle up for Certified Cloud AI Solutions Architect (CCASA), a dynamic and hands-on journey into the core of artificial intelligence and machine learning, specifically tailored for the power and scalability of cloud environments.

Forget dry theory – we'll dive headfirst into the exciting world of AI, demystifying the nuances between AI, ML, and the magic of deep learning.

You'll explore a universe of real-world applications, from revolutionizing healthcare to transforming finance and beyond, gaining a practical understanding of how these technologies are reshaping industries.

Ever wondered how machines learn? We'll unravel the mysteries of supervised, unsupervised, and reinforcement learning, equipping you with the knowledge to choose the right approach for any challenge. And as the AI landscape evolves at lightning speed, we'll chart the course through cutting-edge concepts like Generative AI, Predictive AI, and the intriguing potential of Agentic AI.

But it's not just about the "what" – it's about the "why." You'll learn to articulate the compelling value proposition of AI/ML solutions, identifying the tangible benefits they bring to businesses while also navigating the potential pitfalls and the critical role of data.

Finally, we'll navigate the bustling AI/ML ecosystem, pinpointing the key players, familiarizing you with essential tools and platforms, and ensuring you stay ahead of the curve with the latest trends and breakthroughs.

CCASA isn't just a course; it's your launchpad to becoming a sought-after cloud AI architect, capable of designing and implementing intelligent solutions that drive innovation and transform businesses. Are you ready to build the future, one intelligent cloud solution at a time?

Note: This course is Course One of Three Course for the CCASA certification.

Course 1- Domain 1 – AI/ML Fundamentals

Course 2 – Domain 2 – Solutions Development and Proposals

Course 3 – Domain 3 - Customer Relationship Management

Expected Learning Outcomes

At the end of the course, the learners will be able to be acquainted with the following.

1.1 Core Concepts:

· Define AI, ML, and Deep Learning (DL) and their key differences.

· Explain common AI/ML use cases and applications across various industries.

· Describe different types of machine learning (supervised, unsupervised, reinforcement learning).

· Define and differentiate between Generative AI, Predictive AI, Agentic AI, and others.

1.2 AI/ML Value Proposition:

· Articulate the benefits of AI/ML solutions for businesses.

· Identify potential challenges and limitations of AI/ML adoption.

· Explain the importance of data in AI/ML solutions.

1.3 AI/ML Landscape:

· Identify key players in the AI/ML market (cloud providers, technology vendors, etc.).

· Recognize standard AI/ML tools, platforms, and frameworks.

· Stay updated on emerging trends and advancements in AI/ML.

Who should take this course and certification exam.

· Anyone that is in a Solutions Architect or presales role or who may want to become AI/ML Aware.

· Anyone that has 1 year of cloud computing experience.

· Anyone that wants to prove they are competent in AI/ML focused technical cloud solutions should consider obtaining the CCASA certification.

· Anyone who wants to learn more about, AI/ML cloud computing architecture, solutioning and cost management.