project 
insideBIGDATA
APRIL 29, 2024
The article covers how to avoid 8 data-related mistakes on data projects This article is excerpted from the book, “Winning with Data Science: A Handbook for Business Leaders,” by Howard Friedman and Akshay Swaminathan with permission from the publisher, Columbia Business School Publishing.
Data Science Dojo
MAY 16, 2024
With a broad spectrum of applications, AI is fast becoming a staple in project workflows. Recent findings from a Capterra survey underscore this trend, revealing that 93% of project managers saw a positive return on investment from AI tools last year, with only a minimal 8% of companies not yet planning to adopt AI technologies.
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Analytics Vidhya
MARCH 21, 2024
In this python tutorial, we’ll cover everything from the basics to advanced topics, as well as important libraries and practical projects in Python. Before […] The post Python Tutorial | Concepts, Resources and Projects appeared first on Analytics Vidhya.
Analytics Vidhya
MAY 8, 2024
Per Statista, The Artificial Intelligence market in India is projected to grow by 28.63% (2024-2030), resulting in a market volume of US$28.36bn in 2030. It is visible that AI is booming, […] The post 10 Datasets by INDIAai for your Next Data Science Project appeared first on Analytics Vidhya. Quiet impressive, right?
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It can be confusing to determine which features are most important for your project. Get the Entity Resolution Evaluation Checklist to make sure you’ve thought of everything to make your project a success! Are you trying to decide which entity resolution capabilities you need? And sometimes key features are overlooked.
Analytics Vidhya
AUGUST 29, 2023
In a rapidly evolving technological panorama, the emergence of generative AI projects has redefined how we interact with, create, and experience content. These projects harness the power of artificial intelligence to replicate human creativity and productiveness, spanning from text chatbots to video generators.
Data Science Dojo
MAY 14, 2024
The field of project management has undergone a significant transformation over the years, particularly with the advent of AI. The integration of AI project management tools has reshaped the landscape, allowing for greater efficiency, predictive analytics, and automated task handling.
Speaker: David Bard, Principal at VP Product Coaching
In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development!
Speaker: Aindra Misra, Sr. Staff Product Manager of Data & AI at BILL (Previously PM Lead at Twitter/X)
Anticipated future use cases as we project into 2024 and beyond. Examine real world use cases, both internal and external, where data analytics is applied, and understand its evolution with the introduction of Gen AI.
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In this White Paper, Logi Analytics has identified 5 tell-tale signs your project is moving from “nice to have” to “needed yesterday.". Many application teams leave embedded analytics to languish until something—an unhappy customer, plummeting revenue, a spike in customer churn—demands change. But by then, it may be too late.
Speaker: Ryan MacCarrigan, Founding Principal, LeanStudio
Watch this webinar with Ryan MacCarrigan, Founding Principal of LeanStudio, to learn about key considerations for launching your next analytics project. But what happens when you have a growing user base and additional feature requests?
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Every time an application team gets caught up in the “build vs buy” debate, it stalls projects and delays time to revenue. There is a third option. Partnering with an analytics development platform gives you the freedom to customize a solution without the risks and long-term costs of building your own.
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You'll learn: Why every product leader goes into a new project with untested, hidden assumptions. Watch this webinar with Laura Klein, product manager and author of Build Better Products, to learn how to spot the unconscious assumptions which you’re basing decisions on and guidelines for validating (or invalidating) your ideas.
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What should product managers keep in mind when adding an analytics project to their roadmap? What are best practices when designing the UI and UX of embedded dashboards, reports, and analytics? What should software teams know about implementing security that works with the rest of their products?
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Every data-driven project calls for a review of your data architecture—and that includes embedded analytics. Before you add new dashboards and reports to your application, you need to evaluate your data architecture with analytics in mind.
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