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

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  1. Course content42 lessons
    1. CCASA TC CCASA Course Trailer Rev1
    2. CCASA TC CCASA Course Introduction Rev2
    3. CCASA TC Why Take CCASA Rev1
    4. CCASA TC Exam Domains Rev1
    5. CCASA TC IMportance of AI Solutions Rev1
    6. CCASA TC Course Resources Rev1
    7. CCASA TC Domain 1 Module 1 Rev1
    8. CCASA TC Module 1 Section 1.1 Rev1
    9. CCASA TC What is AIML Rev1
    10. CCASA TC What is Deep Learning Rev1
    11. CCASA TC What are ML Types Rev1
    12. CCASA TC Compare Ai ML Rev1
    13. CCASA TC AI Categories Rev1
    14. CCASA TC NLP Rev1
    15. CCASA TC Open Source Rev1
    16. CCASA TC Algorithms Rev1
    17. CCASA TC Program Languages Rev1
    18. CCASA TC Whiteboard – AI Overview Rev1
    19. CCASA TC Section 1.2 Value Proposition Rev1
    20. CCASA TC Key Benefits Rev1
    21. CCASA TC Business Processes Rev1
    22. CCASA TC Adoption Challenges Rev1
    23. CCASA TC AI Strategy Rev1
    24. CCASA TC Importance of Data Rev1
    25. CCASA TC Data Sources Rev1
    26. CCASA TC Whiteboard AI Value Roadmap Rev1
    27. CCASA TC Demo Google Cloud Rev1
    28. CCASA TC Demo Value generators Rev1
    29. CCASA TC Whiteboard AI Project Workflow Rev1
    30. CCASA TC Section 1.3 Value prop Rev1
    31. CCASA TC Key Players AI Rev1
    32. CCASA TC Key Players Cloud AI Rev1
    33. CCASA TC Trends Rev1
    34. CCASA TC AIML Growth Rev1
    35. CCASA TC Whiteboard AI Resume Filtering Workflow Rev1
    36. CCASA TC Whiteboard ML Workflow AWS Rev1
    37. CCASA TC Finance Use Case Rev1
    38. CCASA TC Module 1 Review Rev1
    39. CCASA TC Module 1 Review Questions Rev1
    40. CCASA TC Certification Process Rev1
    41. CCASA TC Course Closeout Rev1
    42. Resources

(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.