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Important projects to have in your portfolio as a Data Analyst.

17,820 просмотров • 1 месяц назад •via X (Twitter)

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The private markets didn’t have a purpose-built AI agent for portfolio analysis, so we decided to build one. Today, I’m excited to announce the launch of Standard Metrics’ AI Analyst. When we first launched a portfolio-company-specific agent last year, it was an experiment: would investors trust AI to answer questions and provide reporting and analytics for an individual portfolio company? The answer turned out to be a resounding yes. The missing piece was portfolio-wide analysis to answer broader queries like “which of my companies have accelerating revenue growth?” or “create a report of our companies in Europe that are getting low on runway.” These types of analyses are now possible in seconds with our new AI Analyst, which allows for multi-company, portfolio-wide questions across quantitative and qualitative data on Standard Metrics. It’s been incredibly rewarding working with a small set of Beta customers to hone the analyst before today’s release. Many use cases have already emerged, including monitoring risks, creating materials for follow-on investment decisions, and summarizing portfolio performance for LPs. The AI Analyst was a labor of love across every department at Standard Metrics. We’re just getting started and continuing to invest aggressively in new capabilities. Check it out in action at the video below. More on the launch can be found at our blog in comments. 👇

John Melas-Kyriazi

66,105 просмотров • 4 месяцев назад

Major program launch: Data Analytics Professional Certificate! This large, five-course sequence takes you all the way to being job-ready as a data analyst, and shows how to use Generative AI as a thought partner to enhance your work in this role. Offered by on Coursera, this is taught by Sean Barnes, Ph.D., a Data Science & Engineering Leader at Netflix. Analyzing data remains one of the most important skills in where the world is going with AI. This comprehensive certificate takes you all the way to being job-ready. Each course comes with practical projects demonstrated in real-world contexts, such as analyzing sales data for a Korean bakery, video game sales trends across different regions, or identifying factors impacting customer retention for a communications company. You'll also work on estimating fire distribution for forest fire prevention, analyzing how a diamond's properties affect its market value, and developing predictive models for retail sales analysis, carbon emissions, and coral reef conservation. Here's some of what you'll learn: - How to define data and categorize it into its many types such as discrete & continuous numerical, structured & unstructured, time series, categorical, and know what insights can be derived from the different types of data categories. - How to differentiate between data-related job roles and their responsibilities, and how data flows through an organization from the moment of capture to decision-making. - How to perform data processing functions and apply conditional formatting in spreadsheets to extract business value from your data using statistical calculations and best practices for visualizing and interpreting data. - How to use LLMs for stakeholder analysis, data exploration, and data visualization. - Best practices for using LLMs for as a thought partner to data analysis work By the end of this professional certificate program, you will have learned core statistical concepts, analysis techniques, and visualization methodologies that will serve as the foundation for working as a data analyst. The world needs more data analysts, especially ones who know how to use modern generative AI. With data science roles projected to grow 36% by 2033, the skills taught in this program create new professional opportunities in data. Sign up here!

Andrew Ng

84,686 просмотров • 1 год назад