Chad Sanderson

Cohort 1

Master AI-Ready Data Infrastructure - 2

Discussing data product development, semantic layers, data APIs, and modern data modeling.

Data Products

Dive into data quality's impact on dependable AI, transform your approach to data management, and learn to build a culture of accountability

CEO and Co-founder of Gable.ai

Master AI-Ready Data Infrastructure

Digital Transformation Manager

Data Quality Evangelist

CTO & Data Strategist

Data Engineer

Data & AI Manager

Head of Data Engineering

"Garbage In, Garbage Out" - one of the most frightening phrases to anyone working on an AI project. The foundation of any successful AI initiative lies NOT just in the algorithms, but in the quality of underlying data infrastructure. This course introduces you to the transformative power of a scalable, high-quality, well-governed data infrastructure as the backbone of Artificial Intelligence and Machine Learning programs. You will learn: 💡 Architecting Scalable Data InfrastructureYou'll master designing and implementing a data infrastructure that's robust enough to support sophisticated AI and ML applications. From data lakes to modern data warehouses, understand how to design and manage infrastructures that can facilitate federated data access, analysis, and of course - AI. 💡 Mastering Data Quality for AILearn to navigate the challenges of managing data quality specifically tailored for applications that leverage AI/ML. What are the components of ensuring data pipelines are trustworthy, scalable, maintainable, and observable. We'll cover the principles of modern governance, observability, and CI/CD. 💡 Implementing Modern Data Management PracticesLearn the latest in data management strategies that facilitate seamless integration between data producers and consumers within AI ecosystems. How should data producers and data consumers work together to understand dependencies, change management, evolve data contracts, and prevent backward incompatible issues. 💡 Strategies for building data culture in your organizationDiscover strategies to instill a culture of data quality excellence within your organization, creating an environment where data integrity is a shared mission. By the End of This Course:You'll have a clear blueprint for building and managing data infrastructure that empowers AI initiatives. You'll be able to detect and remedy data quality issues, design scalable and secure data systems, and foster a culture that supports AI-driven innovation. Spanning 4 weeks with 4 live Zoom classes (recorded for your convenience), this course features sessions led by Chad Sanderson, CEO and co-founder of Gable.ai. Having led data platforms at Convoy, Microsoft, Oracle, and Sephora with a decade's worth of learning into a comprehensive 5-hour course. Note: This is NOT an engineering course. This course primarily focuses on architecture development, the principles of AI infrastructure, data &amp; AI product management, and organizational design.

Unlock the Potential of AI with High-Quality Data Infrastructure

Course syllabus

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Wednesdays and Fridays 

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August 21, 2024

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Weekly projects

Course schedule

Data Professionals and Practitioners: Data PMs, engineers, analysts, and scientists seeking to deepen their expertise.

Data managers, executives, consultants, and startup owners who aim to enhance their data infrastructure for AI initiatives in their company.

This course is NOT for beginners in the data field with less than 6 months of experience and those seeking hands-on engineering skills.

Who is this course for

What you’ll get out of this course:

Students will gain a deep understanding of the essential components of data infrastructure, including popular tools, gotchas, KPIs, conceptualizing data lakes to deploying modern data warehouses

Comprehensive Mastery of AI Data Infrastructure

Explore the forefront of next-generation data management principles, toolchains, and technology stacks.

Expertise in Modern Data Management 

You'll be equipped with strategies to foster a culture within your organization that prioritizes data quality, recognizes its pivotal role in successful AI initiatives, and encourages a mindset shift towards data-driven excellence.

Drive Organizational Change and Data-Centric Culture

his course equips you with the knowledge to not only understand but also advocate for and implement AI-ready data practices. You'll emerge as a leader who can bridge the gap between data teams and AI initiatives.

Become an AI-Ready Leader

Join a community of data and AI professionals from "Data Quality Camp". This group will serve as a valuable resource for collaboration, sharing best practices, and discussing innovative solutions to data infrastructure challenges.

Network of Like-Minded Professionals

You'll be well-prepared for the roles of the future, from AI strategy to data architecture, making you indispensable in the tech landscape

Future-Proof Your Career

Getting Buy-in for Your Data/ML Projects

CEO of Gable.ai, seasoned data leader and O'Reilly author.

Mark Freeman

Founder of On The Mark Data, 10+ yrs in data science, engineering and GTM

Learn to identify and align with the distinct goals of various data teams, ensuring your projects meet their priorities.

How to identify priorities in different data teams

Discover three methods to present the importance of your data initiatives, making them compelling to all stakeholders.

3 ways to communicate the value of your data project

Learn strategies how to overcome objections and gain support for your data projects.

Strategies to overcome resistance

The Role of Data Quality in AI

CEO of Gable.ai, seasoned data leader, and O'Reilly author

Learn how data quality is crucial for AI success, impacting decision-making and outcomes.

Understand the critical importance of data quality in AI

Explore the 5 most frequent data quality problems that can derail AI projects

5 common data quality issues

Discover foundational strategies and best practices for improving your data quality

Learn directly from Chad Sanderson

Chad Sanderson

Courses

Master AI-Ready Data Infrastructure

Lightning Lessons

Getting Buy-in for Your Data/ML Projects

The Role of Data Quality in AI

Resources

Data Products