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Explore cloud computing fundamentals and Microsoft Azure's ecosystem. Learn core concepts, services, and practical applications to kickstart your journey in cloud technology.
Learn ethical data monetization strategies to unlock value, maximize revenue, and ensure customer satisfaction while navigating legal considerations and leveraging appropriate technologies.
Learn fraud detection techniques using KNIME, including random forest, autoencoder, and isolation forest. Explore methods for both labeled and unlabeled data, with practical demonstrations and insights on implementation.
Explore Master Data Management's role in data science, its implementation styles, unique features, and future trends. Learn how MDM enhances data accuracy and drives improved business outcomes.
Learn to create and deploy custom VM offers on Azure Marketplace using Azure CLI and Packer. Gain hands-on experience with essential tools and best practices for publishing Azure offers.
Learn to use Azure virtual machines, explore the Marketplace, deploy applications, and discover useful tools in this hands-on webinar on working with VMs and Marketplace offers.
Explore graph analytics fundamentals, use cases, and applications in fraud detection. Learn how graph technology enhances ML approaches and its growing importance in complex data analysis.
Learn to streamline machine learning model development with Azure AutoML. Explore algorithm selection, hyperparameter tuning, and evaluation metrics for efficient model creation and deployment.
Learn to set up and use MySQL for data science, covering RDBMS basics, deployment, interfacing, and practical dataset examples. Gain essential SQL skills for working with structured data in real-world scenarios.
Explore the revolutionary ResNet architecture, its impact on deep learning, and hands-on image classification. Learn about CNN limitations and how ResNet's skip connections transformed the field.
Learn effective data storytelling techniques using the 3Vs: Vocabulary, Voice, and Vision. Improve your ability to create compelling narratives for data management programs and gain support from stakeholders.
Learn essential SQL data wrangling techniques for querying, joining, appending, filtering, and creating new fields in datasets. Gain practical skills to efficiently prepare and transform data for analysis.
Learn effective data storytelling techniques to enhance data analysis impact. Discover how to use visualizations, narratives, and creative approaches to make insights more relatable and actionable for businesses.
Learn effective data storytelling techniques to transform raw information into compelling narratives. Discover how to analyze, visualize, and communicate insights for evidence-informed decision-making in organizations.
Explore methods for interpreting machine learning models, including feature importance and local explanations, to increase trust in AI products and bridge gaps in problem understanding.
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