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Data Science and Generative AI: Leveraging Best Practices and Avoiding Pitfalls
Data science is the key to business success in the information economy. This course will teach you about best practices in deploying a data science capability for your organization.
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Modern Data Warehouse Platforms and Architectures for the Cloud
This course will give you the technical reasons why scaling up is sometimes easy and sometimes very hard—at a level that architects, strategists, and decision makers can understand. You need this understanding to choose the best platform for your cloud data warehouse or workload—and to avoid platform mistakes that can be catastrophic.
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Modern Data Platforms and Architectures for Advanced Analytics, AI, and Machine Learning at Scale
In this course, you will learn how to select a data platform that meets the unique requirements of your organization for artificial intelligence (AI), machine learning (ML) and advanced analytics.
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Data Science Bootcamp // Modeling Your Data: Building and Assessing Models
Students will receive an overview of common statistical techniques and algorithms that are used in analytic models, how they are matched to business objectives and available data, and how the models are tuned and validated. The course will also cover key technologies that enable model development and management, and examples will reinforce key concepts.
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Machine Learning Bootcamp // Hands-On: Machine Learning with Python Made Easy - No, Really!
In this hands-on course, you will be provided with all the fundamentals for understanding and effectively training predictive models using the mighty random forest algorithm. Focusing on core concepts and intuitions means that no complicated math is required.
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MLOps: Best Practices for Delivering and Managing Machine Learning
Machine learning operations (MLOps) is a process-focused and automated methodology for delivering advanced analytics. Building on the data management foundations of DataOps, MLOps provides end-to-end processes to develop, build, test, and automate machine learning and AI models.
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Machine Learning Bootcamp // Hands-On: Data Wrangling for Machine Learning with Python
This course aims for you to return to work and immediately employ these techniques to wrangle data, enhance data analyses, and craft the most valuable machine learning models. You will get hands-on experience wrangling data using the Python pandas library via a series of labs.
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Decision Trees in Machine Learning: Building Explainable Models
This half-day session will dedicate half of its time to translating the business problem into a form that the algorithms can support and preparing data for optimal performance during modeling. The second half of the course focuses on different decision tree algorithms for classification and regression. Participants may consider “Predictive Modeling with Ensembles” as a natural follow-on to this course.
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TDWI Data Warehouse Automation: Better, Faster, Cheaper … You Can Have It All
Data warehouse automation (DWA) is a relatively new class of technology that accelerates warehouse development and change cycles while simultaneously assuring quality and consistency. More than simply generating ETL scripts, DWA automates the entire life cycle from source system analysis to testing and documentation. Productivity gains, cost savings, and quality improvement are all possible with DWA.
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Building Your LLM Roadmap: Delivering Advanced AI and Deep Learning
In this course, you will learn to chart your organization’s path in the world of advanced AI and DL—and build a roadmap to deliver tangible business outcomes!
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