talk-data.com

Pre-registration is REQUIRED. Add to your calendar - https://hubs.li/Q03fWl8B0

AI is transforming business, but it also introduces risks that traditional oversight methods weren’t built to handle. Boards and leadership teams are increasingly tasked with managing AI-driven risks, from compliance challenges to reputational concerns.

In this session, we’ll break down how to evolve risk management and internal assessment practices to address the unique challenges of AI and generative AI. You’ll learn practical strategies for identifying vulnerabilities, aligning with emerging regulations, and building governance frameworks that enable responsible AI adoption.

This talk is designed for business executives and data leaders looking to strengthen their AI risk management approach. We’ll cover key audit considerations, evolving standards, and the tools and credentials that can help position you as a trusted advisor in the AI era.

Speaker: Cal Al-Dhubaib, Head of AI & Data Science at Further

Cal Al-Dhubaib is a globally recognized data scientist, entrepreneur, and innovator in responsible artificial intelligence, specializing in heavily regulated sectors such as healthcare, energy, and defense. He leads AI and Data Science at Further, a privacy-first data, analytics, and AI company supporting over 100 of the Fortune 500. Cal founded and scaled Pandata, known for responsible AI design and development. Under his guidance, Pandata worked with high-profile clients including Cleveland Clinic, Progressive Insurance, and Parker Hannifin, leading to its acquisition by Further in 2024.

Cal frequently speaks on topics including AI ethics, change management, data literacy, and the unique challenges of implementing AI solutions in regulated industries. His insights have been featured in noteworthy publications including Forbes, Nasdaq, VentureBeat, and Open Data Science. Cal has been recognized by Crain’s Cleveland as a Notable Immigrant Leader, Entrepreneur, Technology Executive, and most recently 40 under 40.

ODSC Links: • Get free access to more talks/trainings like this at Ai+ Training platform: https://hubs.li/H0Zycsf0 • ODSC blog: https://opendatascience.com/ • Facebook: https://www.facebook.com/OPENDATASCI • Twitter: https://twitter.com/_ODSC & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science • Slack Channel: https://hubs.li/Q038cQBy0 • Code of conduct: https://odsc.com/code-of-conduct/

Pre-registration is REQUIRED. Add to your calendar - https://hubs.li/Q03fWl8B0

AI is transforming business, but it also introduces risks that traditional oversight methods weren’t built to handle. Boards and leadership teams are increasingly tasked with managing AI-driven risks, from compliance challenges to reputational concerns.

In this session, we’ll break down how to evolve risk management and internal assessment practices to address the unique challenges of AI and generative AI. You’ll learn practical strategies for identifying vulnerabilities, aligning with emerging regulations, and building governance frameworks that enable responsible AI adoption.

This talk is designed for business executives and data leaders looking to strengthen their AI risk management approach. We’ll cover key audit considerations, evolving standards, and the tools and credentials that can help position you as a trusted advisor in the AI era.

Speaker: Cal Al-Dhubaib, Head of AI & Data Science at Further

Cal Al-Dhubaib is a globally recognized data scientist, entrepreneur, and innovator in responsible artificial intelligence, specializing in heavily regulated sectors such as healthcare, energy, and defense. He leads AI and Data Science at Further, a privacy-first data, analytics, and AI company supporting over 100 of the Fortune 500. Cal founded and scaled Pandata, known for responsible AI design and development. Under his guidance, Pandata worked with high-profile clients including Cleveland Clinic, Progressive Insurance, and Parker Hannifin, leading to its acquisition by Further in 2024.

Cal frequently speaks on topics including AI ethics, change management, data literacy, and the unique challenges of implementing AI solutions in regulated industries. His insights have been featured in noteworthy publications including Forbes, Nasdaq, VentureBeat, and Open Data Science. Cal has been recognized by Crain’s Cleveland as a Notable Immigrant Leader, Entrepreneur, Technology Executive, and most recently 40 under 40.

ODSC Links: • Get free access to more talks/trainings like this at Ai+ Training platform: https://hubs.li/H0Zycsf0 • ODSC blog: https://opendatascience.com/ • Facebook: https://www.facebook.com/OPENDATASCI • Twitter: https://twitter.com/_ODSC & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science • Slack Channel: https://hubs.li/Q038cQBy0 • Code of conduct: https://odsc.com/code-of-conduct/

Pre-registration is REQUIRED. Add to your calendar - https://hubs.li/Q03fWl8B0

AI is transforming business, but it also introduces risks that traditional oversight methods weren’t built to handle. Boards and leadership teams are increasingly tasked with managing AI-driven risks, from compliance challenges to reputational concerns.

In this session, we’ll break down how to evolve risk management and internal assessment practices to address the unique challenges of AI and generative AI. You’ll learn practical strategies for identifying vulnerabilities, aligning with emerging regulations, and building governance frameworks that enable responsible AI adoption.

This talk is designed for business executives and data leaders looking to strengthen their AI risk management approach. We’ll cover key audit considerations, evolving standards, and the tools and credentials that can help position you as a trusted advisor in the AI era.

Speaker: Cal Al-Dhubaib, Head of AI & Data Science at Further

Cal Al-Dhubaib is a globally recognized data scientist, entrepreneur, and innovator in responsible artificial intelligence, specializing in heavily regulated sectors such as healthcare, energy, and defense. He leads AI and Data Science at Further, a privacy-first data, analytics, and AI company supporting over 100 of the Fortune 500. Cal founded and scaled Pandata, known for responsible AI design and development. Under his guidance, Pandata worked with high-profile clients including Cleveland Clinic, Progressive Insurance, and Parker Hannifin, leading to its acquisition by Further in 2024.

Cal frequently speaks on topics including AI ethics, change management, data literacy, and the unique challenges of implementing AI solutions in regulated industries. His insights have been featured in noteworthy publications including Forbes, Nasdaq, VentureBeat, and Open Data Science. Cal has been recognized by Crain’s Cleveland as a Notable Immigrant Leader, Entrepreneur, Technology Executive, and most recently 40 under 40.

ODSC Links: • Get free access to more talks/trainings like this at Ai+ Training platform: https://hubs.li/H0Zycsf0 • ODSC blog: https://opendatascience.com/ • Facebook: https://www.facebook.com/OPENDATASCI • Twitter: https://twitter.com/_ODSC & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science • Slack Channel: https://hubs.li/Q038cQBy0 • Code of conduct: https://odsc.com/code-of-conduct/

Pre-registration is REQUIRED. Add to your calendar - https://hubs.li/Q03fWl8B0

AI is transforming business, but it also introduces risks that traditional oversight methods weren’t built to handle. Boards and leadership teams are increasingly tasked with managing AI-driven risks, from compliance challenges to reputational concerns.

In this session, we’ll break down how to evolve risk management and internal assessment practices to address the unique challenges of AI and generative AI. You’ll learn practical strategies for identifying vulnerabilities, aligning with emerging regulations, and building governance frameworks that enable responsible AI adoption.

This talk is designed for business executives and data leaders looking to strengthen their AI risk management approach. We’ll cover key audit considerations, evolving standards, and the tools and credentials that can help position you as a trusted advisor in the AI era.

Speaker: Cal Al-Dhubaib, Head of AI & Data Science at Further

Cal Al-Dhubaib is a globally recognized data scientist, entrepreneur, and innovator in responsible artificial intelligence, specializing in heavily regulated sectors such as healthcare, energy, and defense. He leads AI and Data Science at Further, a privacy-first data, analytics, and AI company supporting over 100 of the Fortune 500. Cal founded and scaled Pandata, known for responsible AI design and development. Under his guidance, Pandata worked with high-profile clients including Cleveland Clinic, Progressive Insurance, and Parker Hannifin, leading to its acquisition by Further in 2024.

Cal frequently speaks on topics including AI ethics, change management, data literacy, and the unique challenges of implementing AI solutions in regulated industries. His insights have been featured in noteworthy publications including Forbes, Nasdaq, VentureBeat, and Open Data Science. Cal has been recognized by Crain’s Cleveland as a Notable Immigrant Leader, Entrepreneur, Technology Executive, and most recently 40 under 40.

ODSC Links: • Get free access to more talks/trainings like this at Ai+ Training platform: https://hubs.li/H0Zycsf0 • ODSC blog: https://opendatascience.com/ • Facebook: https://www.facebook.com/OPENDATASCI • Twitter: https://twitter.com/_ODSC & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science • Slack Channel: https://hubs.li/Q038cQBy0 • Code of conduct: https://odsc.com/code-of-conduct/

To access this webinar, please register here: https://hubs.li/Q02y4Xjd0

Topic: "Designing AI for Trust - How To Create Value While Setting The Right Guardrails"

Speaker: Cal Al-Dhubaib, Head of AI & Data Science at Further

Cal Al-Dhubaib is a globally recognized data scientist, entrepreneur, and innovator in responsible artificial intelligence, specializing in heavily regulated sectors such as healthcare, energy, and defense. He leads AI and Data Science at Further, a privacy-first data, analytics, and AI company servicing over 100 of the Fortune 500. Cal founded and scaled Pandata, known for responsible AI design and development. Under his guidance, Pandata worked with high-profile clients including Cleveland Clinic, Progressive Insurance, and Parker Hannifin, leading to its acquisition by Further in March of 2024.

Cal frequently speaks on topics including AI ethics, change management, data literacy, and the unique challenges of implementing AI solutions in regulated industries. His insights have been featured in noteworthy publications such as Forbes, Nasdaq, VentureBeat, CDO Magazine, and Open Data Science. Cal has been recognized by Crain’s Cleveland as a Notable Immigrant Leader, Entrepreneur, and Technology Executive.

Abstract: As AI becomes integral to business strategy, many organizations are navigating the complex interplay between technical innovation, creating business value, and managing risk. In many cases challenges arise with human adoption, alignment with business values, risk management processes, and unexpectedly costly data curation efforts.

With a focus on business and technical leaders responsible for bringing AI solutions to life, we will draw from best practices in designing and deploying AI solutions across mission-critical sectors such as healthcare, energy, and financial services, where trust is critical.

Participants will walk away with some practical tools to lead their organizations in developing and deploying AI solutions that are not only technically sound but also widely trusted.

ODSC Links: • Get free access to more talks/trainings like this at Ai+ Training platform: https://hubs.li/H0Zycsf0 • ODSC blog: https://opendatascience.com/ • Facebook: https://www.facebook.com/OPENDATASCI • Twitter: https://twitter.com/_ODSC & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science • Slack Channel: https://hubs.li/Q02w1GKB0 • Code of conduct: https://odsc.com/code-of-conduct/

To access this webinar, please register here: https://hubs.li/Q02y4Xjd0

Topic: "Designing AI for Trust - How To Create Value While Setting The Right Guardrails"

Speaker: Cal Al-Dhubaib, Head of AI & Data Science at Further

Cal Al-Dhubaib is a globally recognized data scientist, entrepreneur, and innovator in responsible artificial intelligence, specializing in heavily regulated sectors such as healthcare, energy, and defense. He leads AI and Data Science at Further, a privacy-first data, analytics, and AI company servicing over 100 of the Fortune 500. Cal founded and scaled Pandata, known for responsible AI design and development. Under his guidance, Pandata worked with high-profile clients including Cleveland Clinic, Progressive Insurance, and Parker Hannifin, leading to its acquisition by Further in March of 2024.

Cal frequently speaks on topics including AI ethics, change management, data literacy, and the unique challenges of implementing AI solutions in regulated industries. His insights have been featured in noteworthy publications such as Forbes, Nasdaq, VentureBeat, CDO Magazine, and Open Data Science. Cal has been recognized by Crain’s Cleveland as a Notable Immigrant Leader, Entrepreneur, and Technology Executive.

Abstract: As AI becomes integral to business strategy, many organizations are navigating the complex interplay between technical innovation, creating business value, and managing risk. In many cases challenges arise with human adoption, alignment with business values, risk management processes, and unexpectedly costly data curation efforts.

With a focus on business and technical leaders responsible for bringing AI solutions to life, we will draw from best practices in designing and deploying AI solutions across mission-critical sectors such as healthcare, energy, and financial services, where trust is critical.

Participants will walk away with some practical tools to lead their organizations in developing and deploying AI solutions that are not only technically sound but also widely trusted.

ODSC Links: • Get free access to more talks/trainings like this at Ai+ Training platform: https://hubs.li/H0Zycsf0 • ODSC blog: https://opendatascience.com/ • Facebook: https://www.facebook.com/OPENDATASCI • Twitter: https://twitter.com/_ODSC & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science • Slack Channel: https://hubs.li/Q02w1GKB0 • Code of conduct: https://odsc.com/code-of-conduct/

To access this webinar, please register here: https://hubs.li/Q02y4Xjd0

Topic: "Designing AI for Trust - How To Create Value While Setting The Right Guardrails"

Speaker: Cal Al-Dhubaib, Head of AI & Data Science at Further

Cal Al-Dhubaib is a globally recognized data scientist, entrepreneur, and innovator in responsible artificial intelligence, specializing in heavily regulated sectors such as healthcare, energy, and defense. He leads AI and Data Science at Further, a privacy-first data, analytics, and AI company servicing over 100 of the Fortune 500. Cal founded and scaled Pandata, known for responsible AI design and development. Under his guidance, Pandata worked with high-profile clients including Cleveland Clinic, Progressive Insurance, and Parker Hannifin, leading to its acquisition by Further in March of 2024.

Cal frequently speaks on topics including AI ethics, change management, data literacy, and the unique challenges of implementing AI solutions in regulated industries. His insights have been featured in noteworthy publications such as Forbes, Nasdaq, VentureBeat, CDO Magazine, and Open Data Science. Cal has been recognized by Crain’s Cleveland as a Notable Immigrant Leader, Entrepreneur, and Technology Executive.

Abstract: As AI becomes integral to business strategy, many organizations are navigating the complex interplay between technical innovation, creating business value, and managing risk. In many cases challenges arise with human adoption, alignment with business values, risk management processes, and unexpectedly costly data curation efforts.

With a focus on business and technical leaders responsible for bringing AI solutions to life, we will draw from best practices in designing and deploying AI solutions across mission-critical sectors such as healthcare, energy, and financial services, where trust is critical.

Participants will walk away with some practical tools to lead their organizations in developing and deploying AI solutions that are not only technically sound but also widely trusted.

ODSC Links: • Get free access to more talks/trainings like this at Ai+ Training platform: https://hubs.li/H0Zycsf0 • ODSC blog: https://opendatascience.com/ • Facebook: https://www.facebook.com/OPENDATASCI • Twitter: https://twitter.com/_ODSC & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science • Slack Channel: https://hubs.li/Q02w1GKB0 • Code of conduct: https://odsc.com/code-of-conduct/

To access this webinar, please register here: https://hubs.li/Q02y4Xjd0

Topic: "Designing AI for Trust - How To Create Value While Setting The Right Guardrails"

Speaker: Cal Al-Dhubaib, Head of AI & Data Science at Further

Cal Al-Dhubaib is a globally recognized data scientist, entrepreneur, and innovator in responsible artificial intelligence, specializing in heavily regulated sectors such as healthcare, energy, and defense. He leads AI and Data Science at Further, a privacy-first data, analytics, and AI company servicing over 100 of the Fortune 500. Cal founded and scaled Pandata, known for responsible AI design and development. Under his guidance, Pandata worked with high-profile clients including Cleveland Clinic, Progressive Insurance, and Parker Hannifin, leading to its acquisition by Further in March of 2024.

Cal frequently speaks on topics including AI ethics, change management, data literacy, and the unique challenges of implementing AI solutions in regulated industries. His insights have been featured in noteworthy publications such as Forbes, Nasdaq, VentureBeat, CDO Magazine, and Open Data Science. Cal has been recognized by Crain’s Cleveland as a Notable Immigrant Leader, Entrepreneur, and Technology Executive.

Abstract: As AI becomes integral to business strategy, many organizations are navigating the complex interplay between technical innovation, creating business value, and managing risk. In many cases challenges arise with human adoption, alignment with business values, risk management processes, and unexpectedly costly data curation efforts.

With a focus on business and technical leaders responsible for bringing AI solutions to life, we will draw from best practices in designing and deploying AI solutions across mission-critical sectors such as healthcare, energy, and financial services, where trust is critical.

Participants will walk away with some practical tools to lead their organizations in developing and deploying AI solutions that are not only technically sound but also widely trusted.

ODSC Links: • Get free access to more talks/trainings like this at Ai+ Training platform: https://hubs.li/H0Zycsf0 • ODSC blog: https://opendatascience.com/ • Facebook: https://www.facebook.com/OPENDATASCI • Twitter: https://twitter.com/_ODSC & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science • Slack Channel: https://hubs.li/Q02w1GKB0 • Code of conduct: https://odsc.com/code-of-conduct/

To access this webinar, please register here: https://hubs.li/Q02y4Xjd0

Topic: "Designing AI for Trust - How To Create Value While Setting The Right Guardrails"

Speaker: Cal Al-Dhubaib, Head of AI & Data Science at Further

Cal Al-Dhubaib is a globally recognized data scientist, entrepreneur, and innovator in responsible artificial intelligence, specializing in heavily regulated sectors such as healthcare, energy, and defense. He leads AI and Data Science at Further, a privacy-first data, analytics, and AI company servicing over 100 of the Fortune 500. Cal founded and scaled Pandata, known for responsible AI design and development. Under his guidance, Pandata worked with high-profile clients including Cleveland Clinic, Progressive Insurance, and Parker Hannifin, leading to its acquisition by Further in March of 2024.

Cal frequently speaks on topics including AI ethics, change management, data literacy, and the unique challenges of implementing AI solutions in regulated industries. His insights have been featured in noteworthy publications such as Forbes, Nasdaq, VentureBeat, CDO Magazine, and Open Data Science. Cal has been recognized by Crain’s Cleveland as a Notable Immigrant Leader, Entrepreneur, and Technology Executive.

Abstract: As AI becomes integral to business strategy, many organizations are navigating the complex interplay between technical innovation, creating business value, and managing risk. In many cases challenges arise with human adoption, alignment with business values, risk management processes, and unexpectedly costly data curation efforts.

With a focus on business and technical leaders responsible for bringing AI solutions to life, we will draw from best practices in designing and deploying AI solutions across mission-critical sectors such as healthcare, energy, and financial services, where trust is critical.

Participants will walk away with some practical tools to lead their organizations in developing and deploying AI solutions that are not only technically sound but also widely trusted.

ODSC Links: • Get free access to more talks/trainings like this at Ai+ Training platform: https://hubs.li/H0Zycsf0 • ODSC blog: https://opendatascience.com/ • Facebook: https://www.facebook.com/OPENDATASCI • Twitter: https://twitter.com/_ODSC & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science • Slack Channel: https://hubs.li/Q02w1GKB0 • Code of conduct: https://odsc.com/code-of-conduct/

To access this webinar, please register here: https://hubs.li/Q02y4Xjd0

Topic: "Designing AI for Trust - How To Create Value While Setting The Right Guardrails"

Speaker: Cal Al-Dhubaib, Head of AI & Data Science at Further

Cal Al-Dhubaib is a globally recognized data scientist, entrepreneur, and innovator in responsible artificial intelligence, specializing in heavily regulated sectors such as healthcare, energy, and defense. He leads AI and Data Science at Further, a privacy-first data, analytics, and AI company servicing over 100 of the Fortune 500. Cal founded and scaled Pandata, known for responsible AI design and development. Under his guidance, Pandata worked with high-profile clients including Cleveland Clinic, Progressive Insurance, and Parker Hannifin, leading to its acquisition by Further in March of 2024.

Cal frequently speaks on topics including AI ethics, change management, data literacy, and the unique challenges of implementing AI solutions in regulated industries. His insights have been featured in noteworthy publications such as Forbes, Nasdaq, VentureBeat, CDO Magazine, and Open Data Science. Cal has been recognized by Crain’s Cleveland as a Notable Immigrant Leader, Entrepreneur, and Technology Executive.

Abstract: As AI becomes integral to business strategy, many organizations are navigating the complex interplay between technical innovation, creating business value, and managing risk. In many cases challenges arise with human adoption, alignment with business values, risk management processes, and unexpectedly costly data curation efforts.

With a focus on business and technical leaders responsible for bringing AI solutions to life, we will draw from best practices in designing and deploying AI solutions across mission-critical sectors such as healthcare, energy, and financial services, where trust is critical.

Participants will walk away with some practical tools to lead their organizations in developing and deploying AI solutions that are not only technically sound but also widely trusted.

ODSC Links: • Get free access to more talks/trainings like this at Ai+ Training platform: https://hubs.li/H0Zycsf0 • ODSC blog: https://opendatascience.com/ • Facebook: https://www.facebook.com/OPENDATASCI • Twitter: https://twitter.com/_ODSC & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science • Slack Channel: https://hubs.li/Q02w1GKB0 • Code of conduct: https://odsc.com/code-of-conduct/

To access this webinar, please register here: https://hubs.li/Q01_8X6V0

Topic: “Preparing for your First Enterprise Large Language Model (LLM) Application”

Speaker#1: Nicolas Decavel-Bueff, Data Science Consultant at Pandata

He is an SF-based Data Scientist who has delivered valuable solutions across a broad spectrum of industries. His accomplishments range from employing natural language processing models in logistics to leading teams in the development of vital models in the utility sector. His work with diverse tools has consistently created quantifiable business impact. Equipped with a Master's in Data Science from the University of San Francisco, Nicolas blends academic rigor and practical experience to address complex business challenges.

Speaker#2: Parham Parvizi, Founder of Data Stack Academy and Tura.io

Parham is a founding member of Tura.io and DataStack.Academy. Tura is a group of professional Cloud Data Engineers and Architects while Data Stack Academy is the most comprehensive Data Engineering bootcamp; training the future of Cloud Data Engineers. In his 20 years as Data Engineer and Cloud/Big Data Solution Architect, he has been an Apache Software Foundation contributor and an early adopter and contributor to open source Big Data projects as Map Reduce and Hive. Prior to Tura Labs, he was a product manager at Pivotal and one of the initial members of Talend. Prior to Tura Labs, he was a product manager at Pivotal and one of the initial members of Talend. As a Data Advisor and consultant, Parham’s has had the opportunity and pleasure to work with nearly every fortune 100 company over the years. From managing thousands node clusters to optimizing data task that you are familiar with behind the scenes.

Speaker#3: Cal Al-Dhubaib, Founder & AI Strategist at Pandata

Cal is a globally recognized data scientist, entrepreneur, and innovator in responsible artificial intelligence, specializing in high-risk sectors such as healthcare, energy, and defense. He is the founder and CEO of Pandata, a consulting company that helps organizations to design and develop AI-driven solutions for complex business challenges, with an emphasis on responsible AI. Their clients include globally recognized organizations like the Cleveland Clinic, Progressive Insurance, University Hospitals, and Parker Hannifin. Cal frequently speaks on topics including AI ethics, change management, data literacy, and the unique challenges of implementing AI solutions in high-risk industries. His insights have been featured in noteworthy publications such as Forbes, Ohiox, the Marketing AI Institute, Open Data Science, and AI Business News. Cal has also received recognition among Crain’s Cleveland Notable Immigrant Leaders, Notable Entrepreneurs, and most recently, Notable Technology Executives.

Abstract:

Amid the growing accessibility of performant Large Language Models (LLMs) like GPT-4 and Llama-2, and a burgeoning range of commercial licenses, enterprises are now forging the first wave of LLM-driven applications. This session will begin by addressing the challenges with LLMs such as defining clear success criteria for an LLM project and understanding different approaches to LLM work.

We’ll further address technical challenges such as memory handling, input quality control ("garbage in, garbage out"), and the complexities of embeddings. A comparison of different approaches from using Retrieval-Augmented Generation (RAG) to training or fine-tuning on top of a variety of different LLMs.

Through real-world examples we will discuss practical approaches to risk management, ethical considerations, and the ideal team composition for an LLM project. In addition, we’ll discuss a variety of tools that form the modern LLM application development stack. Join us to demystify LLM applications and equip your organization with the knowledge to succeed.

ODSC Links:

• Get free access to more talks/trainings like this at Ai+ Training platform:

https://hubs.li/H0Zycsf0

• ODSC blog: https://opendatascience.com/

• Facebook: https://www.facebook.com/OPENDATASCI

• Twitter: https://twitter.com/_ODSC & @odsc

• LinkedIn: https://www.linkedin.com/company/open-data-science

• Slack Channel: https://hubs.li/Q01_Yrgb0

• Code of conduct: https://odsc.com/code-of-conduct/

To access this webinar, please register here: https://hubs.li/Q01_8X6V0

Topic: “Preparing for your First Enterprise Large Language Model (LLM) Application”

Speaker#1: Nicolas Decavel-Bueff, Data Science Consultant at Pandata

He is an SF-based Data Scientist who has delivered valuable solutions across a broad spectrum of industries. His accomplishments range from employing natural language processing models in logistics to leading teams in the development of vital models in the utility sector. His work with diverse tools has consistently created quantifiable business impact. Equipped with a Master's in Data Science from the University of San Francisco, Nicolas blends academic rigor and practical experience to address complex business challenges.

Speaker#2: Parham Parvizi, Founder of Data Stack Academy and Tura.io

Parham is a founding member of Tura.io and DataStack.Academy. Tura is a group of professional Cloud Data Engineers and Architects while Data Stack Academy is the most comprehensive Data Engineering bootcamp; training the future of Cloud Data Engineers. In his 20 years as Data Engineer and Cloud/Big Data Solution Architect, he has been an Apache Software Foundation contributor and an early adopter and contributor to open source Big Data projects as Map Reduce and Hive. Prior to Tura Labs, he was a product manager at Pivotal and one of the initial members of Talend. Prior to Tura Labs, he was a product manager at Pivotal and one of the initial members of Talend. As a Data Advisor and consultant, Parham’s has had the opportunity and pleasure to work with nearly every fortune 100 company over the years. From managing thousands node clusters to optimizing data task that you are familiar with behind the scenes.

Speaker#3: Cal Al-Dhubaib, Founder & AI Strategist at Pandata

Cal is a globally recognized data scientist, entrepreneur, and innovator in responsible artificial intelligence, specializing in high-risk sectors such as healthcare, energy, and defense. He is the founder and CEO of Pandata, a consulting company that helps organizations to design and develop AI-driven solutions for complex business challenges, with an emphasis on responsible AI. Their clients include globally recognized organizations like the Cleveland Clinic, Progressive Insurance, University Hospitals, and Parker Hannifin. Cal frequently speaks on topics including AI ethics, change management, data literacy, and the unique challenges of implementing AI solutions in high-risk industries. His insights have been featured in noteworthy publications such as Forbes, Ohiox, the Marketing AI Institute, Open Data Science, and AI Business News. Cal has also received recognition among Crain’s Cleveland Notable Immigrant Leaders, Notable Entrepreneurs, and most recently, Notable Technology Executives.

Abstract:

Amid the growing accessibility of performant Large Language Models (LLMs) like GPT-4 and Llama-2, and a burgeoning range of commercial licenses, enterprises are now forging the first wave of LLM-driven applications. This session will begin by addressing the challenges with LLMs such as defining clear success criteria for an LLM project and understanding different approaches to LLM work.

We’ll further address technical challenges such as memory handling, input quality control ("garbage in, garbage out"), and the complexities of embeddings. A comparison of different approaches from using Retrieval-Augmented Generation (RAG) to training or fine-tuning on top of a variety of different LLMs.

Through real-world examples we will discuss practical approaches to risk management, ethical considerations, and the ideal team composition for an LLM project. In addition, we’ll discuss a variety of tools that form the modern LLM application development stack. Join us to demystify LLM applications and equip your organization with the knowledge to succeed.

ODSC Links:

• Get free access to more talks/trainings like this at Ai+ Training platform:

https://hubs.li/H0Zycsf0

• ODSC blog: https://opendatascience.com/

• Facebook: https://www.facebook.com/OPENDATASCI

• Twitter: https://twitter.com/_ODSC & @odsc

• LinkedIn: https://www.linkedin.com/company/open-data-science

• Slack Channel: https://hubs.li/Q01_Yrgb0

• Code of conduct: https://odsc.com/code-of-conduct/

To access this webinar, please register here: https://hubs.li/Q01_8X6V0

Topic: “Preparing for your First Enterprise Large Language Model (LLM) Application”

Speaker#1: Nicolas Decavel-Bueff, Data Science Consultant at Pandata

He is an SF-based Data Scientist who has delivered valuable solutions across a broad spectrum of industries. His accomplishments range from employing natural language processing models in logistics to leading teams in the development of vital models in the utility sector. His work with diverse tools has consistently created quantifiable business impact. Equipped with a Master's in Data Science from the University of San Francisco, Nicolas blends academic rigor and practical experience to address complex business challenges.

Speaker#2: Parham Parvizi, Founder of Data Stack Academy and Tura.io

Parham is a founding member of Tura.io and DataStack.Academy. Tura is a group of professional Cloud Data Engineers and Architects while Data Stack Academy is the most comprehensive Data Engineering bootcamp; training the future of Cloud Data Engineers. In his 20 years as Data Engineer and Cloud/Big Data Solution Architect, he has been an Apache Software Foundation contributor and an early adopter and contributor to open source Big Data projects as Map Reduce and Hive. Prior to Tura Labs, he was a product manager at Pivotal and one of the initial members of Talend. Prior to Tura Labs, he was a product manager at Pivotal and one of the initial members of Talend. As a Data Advisor and consultant, Parham’s has had the opportunity and pleasure to work with nearly every fortune 100 company over the years. From managing thousands node clusters to optimizing data task that you are familiar with behind the scenes.

Speaker#3: Cal Al-Dhubaib, Founder & AI Strategist at Pandata

Cal is a globally recognized data scientist, entrepreneur, and innovator in responsible artificial intelligence, specializing in high-risk sectors such as healthcare, energy, and defense. He is the founder and CEO of Pandata, a consulting company that helps organizations to design and develop AI-driven solutions for complex business challenges, with an emphasis on responsible AI. Their clients include globally recognized organizations like the Cleveland Clinic, Progressive Insurance, University Hospitals, and Parker Hannifin. Cal frequently speaks on topics including AI ethics, change management, data literacy, and the unique challenges of implementing AI solutions in high-risk industries. His insights have been featured in noteworthy publications such as Forbes, Ohiox, the Marketing AI Institute, Open Data Science, and AI Business News. Cal has also received recognition among Crain’s Cleveland Notable Immigrant Leaders, Notable Entrepreneurs, and most recently, Notable Technology Executives.

Abstract:

Amid the growing accessibility of performant Large Language Models (LLMs) like GPT-4 and Llama-2, and a burgeoning range of commercial licenses, enterprises are now forging the first wave of LLM-driven applications. This session will begin by addressing the challenges with LLMs such as defining clear success criteria for an LLM project and understanding different approaches to LLM work.

We’ll further address technical challenges such as memory handling, input quality control ("garbage in, garbage out"), and the complexities of embeddings. A comparison of different approaches from using Retrieval-Augmented Generation (RAG) to training or fine-tuning on top of a variety of different LLMs.

Through real-world examples we will discuss practical approaches to risk management, ethical considerations, and the ideal team composition for an LLM project. In addition, we’ll discuss a variety of tools that form the modern LLM application development stack. Join us to demystify LLM applications and equip your organization with the knowledge to succeed.

ODSC Links:

• Get free access to more talks/trainings like this at Ai+ Training platform:

https://hubs.li/H0Zycsf0

• ODSC blog: https://opendatascience.com/

• Facebook: https://www.facebook.com/OPENDATASCI

• Twitter: https://twitter.com/_ODSC & @odsc

• LinkedIn: https://www.linkedin.com/company/open-data-science

• Slack Channel: https://hubs.li/Q01YzHZw0

• Code of conduct: https://odsc.com/code-of-conduct/

To access this webinar, please register here: https://hubs.li/Q01_8X6V0

Topic: “Preparing for your First Enterprise Large Language Model (LLM) Application”

Speaker#1: Nicolas Decavel-Bueff, Data Science Consultant at Pandata

He is an SF-based Data Scientist who has delivered valuable solutions across a broad spectrum of industries. His accomplishments range from employing natural language processing models in logistics to leading teams in the development of vital models in the utility sector. His work with diverse tools has consistently created quantifiable business impact. Equipped with a Master's in Data Science from the University of San Francisco, Nicolas blends academic rigor and practical experience to address complex business challenges.

Speaker#2: Parham Parvizi, Founder of Data Stack Academy and Tura.io

Parham is a founding member of Tura.io and DataStack.Academy. Tura is a group of professional Cloud Data Engineers and Architects while Data Stack Academy is the most comprehensive Data Engineering bootcamp; training the future of Cloud Data Engineers. In his 20 years as Data Engineer and Cloud/Big Data Solution Architect, he has been an Apache Software Foundation contributor and an early adopter and contributor to open source Big Data projects as Map Reduce and Hive. Prior to Tura Labs, he was a product manager at Pivotal and one of the initial members of Talend. Prior to Tura Labs, he was a product manager at Pivotal and one of the initial members of Talend. As a Data Advisor and consultant, Parham’s has had the opportunity and pleasure to work with nearly every fortune 100 company over the years. From managing thousands node clusters to optimizing data task that you are familiar with behind the scenes.

Speaker#3: Cal Al-Dhubaib, Founder & AI Strategist at Pandata

Cal is a globally recognized data scientist, entrepreneur, and innovator in responsible artificial intelligence, specializing in high-risk sectors such as healthcare, energy, and defense. He is the founder and CEO of Pandata, a consulting company that helps organizations to design and develop AI-driven solutions for complex business challenges, with an emphasis on responsible AI. Their clients include globally recognized organizations like the Cleveland Clinic, Progressive Insurance, University Hospitals, and Parker Hannifin. Cal frequently speaks on topics including AI ethics, change management, data literacy, and the unique challenges of implementing AI solutions in high-risk industries. His insights have been featured in noteworthy publications such as Forbes, Ohiox, the Marketing AI Institute, Open Data Science, and AI Business News. Cal has also received recognition among Crain’s Cleveland Notable Immigrant Leaders, Notable Entrepreneurs, and most recently, Notable Technology Executives.

Abstract:

Amid the growing accessibility of performant Large Language Models (LLMs) like GPT-4 and Llama-2, and a burgeoning range of commercial licenses, enterprises are now forging the first wave of LLM-driven applications. This session will begin by addressing the challenges with LLMs such as defining clear success criteria for an LLM project and understanding different approaches to LLM work.

We’ll further address technical challenges such as memory handling, input quality control ("garbage in, garbage out"), and the complexities of embeddings. A comparison of different approaches from using Retrieval-Augmented Generation (RAG) to training or fine-tuning on top of a variety of different LLMs.

Through real-world examples we will discuss practical approaches to risk management, ethical considerations, and the ideal team composition for an LLM project. In addition, we’ll discuss a variety of tools that form the modern LLM application development stack. Join us to demystify LLM applications and equip your organization with the knowledge to succeed.

ODSC Links:

• Get free access to more talks/trainings like this at Ai+ Training platform:

https://hubs.li/H0Zycsf0

• ODSC blog: https://opendatascience.com/

• Facebook: https://www.facebook.com/OPENDATASCI

• Twitter: https://twitter.com/_ODSC & @odsc

• LinkedIn: https://www.linkedin.com/company/open-data-science

• Slack Channel: https://hubs.li/Q01_Yrgb0

• Code of conduct: https://odsc.com/code-of-conduct/

To access this webinar, please register here: https://hubs.li/Q01_8X6V0

Topic: “Preparing for your First Enterprise Large Language Model (LLM) Application”

Speaker#1: Nicolas Decavel-Bueff, Data Science Consultant at Pandata

He is an SF-based Data Scientist who has delivered valuable solutions across a broad spectrum of industries. His accomplishments range from employing natural language processing models in logistics to leading teams in the development of vital models in the utility sector. His work with diverse tools has consistently created quantifiable business impact. Equipped with a Master's in Data Science from the University of San Francisco, Nicolas blends academic rigor and practical experience to address complex business challenges.

Speaker#2: Parham Parvizi, Founder of Data Stack Academy and Tura.io

Parham is a founding member of Tura.io and DataStack.Academy. Tura is a group of professional Cloud Data Engineers and Architects while Data Stack Academy is the most comprehensive Data Engineering bootcamp; training the future of Cloud Data Engineers. In his 20 years as Data Engineer and Cloud/Big Data Solution Architect, he has been an Apache Software Foundation contributor and an early adopter and contributor to open source Big Data projects as Map Reduce and Hive. Prior to Tura Labs, he was a product manager at Pivotal and one of the initial members of Talend. Prior to Tura Labs, he was a product manager at Pivotal and one of the initial members of Talend. As a Data Advisor and consultant, Parham’s has had the opportunity and pleasure to work with nearly every fortune 100 company over the years. From managing thousands node clusters to optimizing data task that you are familiar with behind the scenes.

Speaker#3: Cal Al-Dhubaib, Founder & AI Strategist at Pandata

Cal is a globally recognized data scientist, entrepreneur, and innovator in responsible artificial intelligence, specializing in high-risk sectors such as healthcare, energy, and defense. He is the founder and CEO of Pandata, a consulting company that helps organizations to design and develop AI-driven solutions for complex business challenges, with an emphasis on responsible AI. Their clients include globally recognized organizations like the Cleveland Clinic, Progressive Insurance, University Hospitals, and Parker Hannifin. Cal frequently speaks on topics including AI ethics, change management, data literacy, and the unique challenges of implementing AI solutions in high-risk industries. His insights have been featured in noteworthy publications such as Forbes, Ohiox, the Marketing AI Institute, Open Data Science, and AI Business News. Cal has also received recognition among Crain’s Cleveland Notable Immigrant Leaders, Notable Entrepreneurs, and most recently, Notable Technology Executives.

Abstract:

Amid the growing accessibility of performant Large Language Models (LLMs) like GPT-4 and Llama-2, and a burgeoning range of commercial licenses, enterprises are now forging the first wave of LLM-driven applications. This session will begin by addressing the challenges with LLMs such as defining clear success criteria for an LLM project and understanding different approaches to LLM work.

We’ll further address technical challenges such as memory handling, input quality control ("garbage in, garbage out"), and the complexities of embeddings. A comparison of different approaches from using Retrieval-Augmented Generation (RAG) to training or fine-tuning on top of a variety of different LLMs.

Through real-world examples we will discuss practical approaches to risk management, ethical considerations, and the ideal team composition for an LLM project. In addition, we’ll discuss a variety of tools that form the modern LLM application development stack. Join us to demystify LLM applications and equip your organization with the knowledge to succeed.

ODSC Links:

• Get free access to more talks/trainings like this at Ai+ Training platform:

https://hubs.li/H0Zycsf0

• ODSC blog: https://opendatascience.com/

• Facebook: https://www.facebook.com/OPENDATASCI

• Twitter: https://twitter.com/_ODSC & @odsc

• LinkedIn: https://www.linkedin.com/company/open-data-science

• Slack Channel: https://hubs.li/Q01YzHZw0

• Code of conduct: https://odsc.com/code-of-conduct/

To access this webinar, please register here: https://hubs.li/Q01_8X6V0

Topic: “Preparing for your First Enterprise Large Language Model (LLM) Application”

Speaker#1: Nicolas Decavel-Bueff, Data Science Consultant at Pandata

He is an SF-based Data Scientist who has delivered valuable solutions across a broad spectrum of industries. His accomplishments range from employing natural language processing models in logistics to leading teams in the development of vital models in the utility sector. His work with diverse tools has consistently created quantifiable business impact. Equipped with a Master's in Data Science from the University of San Francisco, Nicolas blends academic rigor and practical experience to address complex business challenges.

Speaker#2: Parham Parvizi, Founder of Data Stack Academy and Tura.io

Parham is a founding member of Tura.io and DataStack.Academy. Tura is a group of professional Cloud Data Engineers and Architects while Data Stack Academy is the most comprehensive Data Engineering bootcamp; training the future of Cloud Data Engineers. In his 20 years as Data Engineer and Cloud/Big Data Solution Architect, he has been an Apache Software Foundation contributor and an early adopter and contributor to open source Big Data projects as Map Reduce and Hive. Prior to Tura Labs, he was a product manager at Pivotal and one of the initial members of Talend. Prior to Tura Labs, he was a product manager at Pivotal and one of the initial members of Talend. As a Data Advisor and consultant, Parham’s has had the opportunity and pleasure to work with nearly every fortune 100 company over the years. From managing thousands node clusters to optimizing data task that you are familiar with behind the scenes.

Speaker#3: Cal Al-Dhubaib, Founder & AI Strategist at Pandata

Cal is a globally recognized data scientist, entrepreneur, and innovator in responsible artificial intelligence, specializing in high-risk sectors such as healthcare, energy, and defense. He is the founder and CEO of Pandata, a consulting company that helps organizations to design and develop AI-driven solutions for complex business challenges, with an emphasis on responsible AI. Their clients include globally recognized organizations like the Cleveland Clinic, Progressive Insurance, University Hospitals, and Parker Hannifin. Cal frequently speaks on topics including AI ethics, change management, data literacy, and the unique challenges of implementing AI solutions in high-risk industries. His insights have been featured in noteworthy publications such as Forbes, Ohiox, the Marketing AI Institute, Open Data Science, and AI Business News. Cal has also received recognition among Crain’s Cleveland Notable Immigrant Leaders, Notable Entrepreneurs, and most recently, Notable Technology Executives.

Abstract:

Amid the growing accessibility of performant Large Language Models (LLMs) like GPT-4 and Llama-2, and a burgeoning range of commercial licenses, enterprises are now forging the first wave of LLM-driven applications. This session will begin by addressing the challenges with LLMs such as defining clear success criteria for an LLM project and understanding different approaches to LLM work.

We’ll further address technical challenges such as memory handling, input quality control ("garbage in, garbage out"), and the complexities of embeddings. A comparison of different approaches from using Retrieval-Augmented Generation (RAG) to training or fine-tuning on top of a variety of different LLMs.

Through real-world examples we will discuss practical approaches to risk management, ethical considerations, and the ideal team composition for an LLM project. In addition, we’ll discuss a variety of tools that form the modern LLM application development stack. Join us to demystify LLM applications and equip your organization with the knowledge to succeed.

ODSC Links:

• Get free access to more talks/trainings like this at Ai+ Training platform:

https://hubs.li/H0Zycsf0

• ODSC blog: https://opendatascience.com/

• Facebook: https://www.facebook.com/OPENDATASCI

• Twitter: https://twitter.com/_ODSC & @odsc

• LinkedIn: https://www.linkedin.com/company/open-data-science

• Slack Channel: https://hubs.li/Q01YzHZw0

• Code of conduct: https://odsc.com/code-of-conduct/