Speaker

Sweta Sinha

Sweta Sinha

Director of Data Science at Ascend Learning

Kansas City, Missouri, United States

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Sweta Sinha, Director of Data Science at Ascend Learning, is at the forefront of transforming healthcare education through cutting-edge AI technologies. Her expertise in strategically deploying AI and ML solutions drives groundbreaking initiatives, significantly enhancing learning outcomes and experiences for healthcare professionals.

She leads the AI Center of Excellence and is instrumental in launching enterprise-grade Machine Learning and generative AI products, Her huge commitment to building AI systems responsibly is demonstrated through her leadership roles on the AI Governance body. Her dedication is not only shaping the future of education technology but also setting the standard for ethical AI development.

Area of Expertise

  • Information & Communications Technology
  • Government, Social Sector & Education
  • Finance & Banking
  • Health & Medical

Topics

  • Azure machine learning service
  • Data Science & AI
  • natural language processing
  • Conversational AI
  • Model Deployment
  • Responsible AI
  • Deep Neural Networks
  • Azure Data Factory
  • Azure Data & AI
  • Snowflake
  • EdTech
  • HealthTech
  • Analytics and Big Data
  • Common Data Service
  • generative ai
  • Artificial Intelligence (AI) and Machine Learning

Operationalizing AI models with ModelOps - Delivering value at scale

Description: Organizations are realizing the revolutionary potential of Artificial Intelligence In gaining competitive advantage. Though AI is in mainstream, many organizations are still struggling to move beyond proof of concept to operationalizing the models and optimize the ROI on AI investments. ModelOps takes principled approach to operationalizing AI models into production, thereby accelerating AI initiatives to deliver continuous business value. A well strategized ModelOps practices will automate and augment model life cycle management and make AI ready for DevOps. In this session you will learn about steps to take to operationalize AI/ML model with enterprise level ModelOps platform.

Role of Data Governance in building Responsible AI system

In today's digital age, organizations are amassing huge amounts of data from various sources. However, managing and utilizing this data effectively is becoming increasingly complex and challenging. The use of AI, particularly in regulated industries such as healthcare, finance, and law enforcement, has brought new ethical and legal considerations, raising concerns about data privacy, security, and potential biases in AI systems. Therefore, it is crucial for organizations to have clear policies and procedures in place to govern the collection, storage, and use of data being used by AI systems, and ensure that these systems are developed and used responsibly. In this session, you will learn about how organizations can implement proper governance and oversight of data used in AI systems, including issues of accuracy, bias, privacy, and security. Additionally, we will also explore the challenges and best practices for implementing data governance in organizations developing AI systems and the role of stakeholders in ensuring responsible AI development and use.

Generative AI: Why businesses should care?

Recent advancements in Generative AI have led to the development of powerful models such as GPT-3 and recently ChatGPT, which have proven to be capable of generating high-quality, human-like text, images, and audio. These developments have opened up a range of opportunities in industries such as content creation, natural language processing, and computer-aided design. In this session, we will delve into the benefits of implementing generative AI models in automating processes, uncovering insights, and driving innovation in businesses. Furthermore, we will examine practical ways in which businesses can harness the power of Generative AI to enhance efficiency, automate repetitive tasks and make data-driven decisions.

AI DevWorld 2021 Sessionize Event

October 2021

KCDC 2021 Sessionize Event

September 2021 Kansas City, Missouri, United States

Kansas City Women in Tech

Tech Talk: What Do Data Scientists Actually Do?

Data Science is one of the fastest growing career fields in the 21st century, but what do data scientists actually do? Learn all about the career at our October TechTalk on October 17 from 6pm to 8pm with a Q&A with data scientists who work in the field. Our panelists will share what it’s like to work in the field and how organizations use data to inform their processes.

October 2018 Kansas City, Missouri, United States

Techweek Kansas City 2018

Topic: Data Science in ELearning

Abstract: E-Learning analytics makes use of huge wealth of data gathered from online learner digital footprint by employing various data science techniques and machine learning. This data can be used to improve the learner’s experience, knowledge acquired and skill gained and increase the effectiveness of learning resources.

October 2018 Kansas City, Missouri, United States

Kansas City R Users Group

Talk Topic: Uses of Data Science at Ascend Learning

May 2018 Overland Park, Kansas, United States

IIBA Kansas CIty

Presentation Description: Data Analytics? Business Intelligence? Data Science? Machine Learning? If you are confused about the world of data, please join the Kansas City Chapter of the IIBA to for an overview of the world of Data Analytics and Data Science, presented by Diana Alt and Sweta Sinha. Our presenters will give you a peek into the world of analytics - from descriptive to prescriptive analytics and share how product management and data science teams work together to create valuable analytics products.

February 2018 Leawood, Kansas, United States

Sweta Sinha

Director of Data Science at Ascend Learning

Kansas City, Missouri, United States

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