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What is DataRobot University

Traditional data science education can be overwhelming. Mathematics, statistics, programming, algorithms — each of these subjects takes years to actually master. What’s worse is that even after learning them you still don’t have the practical skills and experience needed to solve real world business problems.

DataRobot University starts with the practical, teaching you what you need to know to start solving real world problems immediately. Because most of the technical work can now be automated, training can focus on everything else you need to ensure success. These include topics like scoping and framing data science projects, avoiding common mistakes, and communicating solutions to others in your organization.
Recorded May 5 2016 2 mins
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  • Pontos chave para o sucesso do Machine Learning na sua organização Recorded: Feb 22 2018 58 mins
    Tom de Godoy
    O machine learning está mudando a forma como organizações de todos os setores lidam com análises preditivas. Mesmo com toda a movimentação e jargões de mercado — machine learning, inteligência artificial, deep learning e modelagem estatística — é cada vez mais difícil separar o fato da ficção à medida que você avalia soluções de machine learning.

    Em meio ao desafio de contratar e reter de talentos — cientistas de dados, engenheiros, analistas, profissionais de TI — torna-se um pesadelo decidir quem pode alavancar e implementar tecnologias de análises preditivas e adotar com sucesso o machine learning.
  • Multichannel Marketing Attribution with Automated Machine Learning Recorded: Feb 22 2018 47 mins
    Colin Priest
    Companies are spending more than ever on marketing. According to the Harvard Business Review, it is estimated that global spending on media is expected to reach $2.1 trillion by 2019. But is all that money effective in producing improved ROI? Without knowing which channels are driving sales, or more specifically, which individual marketing activities are working, marketing spending is a black box.

    On this webinar, Data Scientist Colin Priest of DataRobot explains the importance of multichannel, multi-touch attribution to accurately measure the success of your marketing efforts – and how automated machine learning offers the shortest path to success.
  • Machine Learning for Mission Success: Data Science for the Federal Executive Recorded: Feb 22 2018 60 mins
    Erin Hawley
    Within the federal sector, machine learning and artificial intelligence are treated like a distant possibility rather than an immediate reality. Considerable confusion exists about how the government can implement technology to automate predictive analytics and free data scientists to make educated decisions in real time, rather than crunch algorithms.



    The objective of this webinar is to help educate the federal community about the realities, and real possibilities, data science can provide. See how agencies can start implementing machine learning for mission success.
  • Analytics Strategy of a 21st Century Insurance Company Recorded: Feb 21 2018 56 mins
    Satadru Sengupta
    There is no doubt about the impact of predictive analytics in any insurance company – large, medium, or small. The question that everyone is asking: how can we bring a sustainable, cost-effective, and consumer centric predictive analytics strategy within the organization? Machine Learning Automation is the answer to that question.

    This 60 minute on-demand webinar provides an overview of predictive modeling, machine learning, and Artificial Intelligence (AI) in the insurance industry, offering insights into how these technologies will impact growth and profitability. You’ll also learn the three main aspects of a sustainable and cost-effective predictive analytics strategy in an insurance company:
  • How to Avoid Building Bad Models Recorded: Feb 21 2018 59 mins
    Jen Underwood
    Don’t be naive when it comes to automated machine learning. Despite the unprecedented speed and ease of creating automated predictive models today, the human mind is still essential for generating good models.



    From selecting the right problem to solve to preventing algorithm bias, machine learning is still an art and a science. To reap the benefits of automated machine learning, Jen Underwood, Founder of Impact Analytix, will share the most common mistakes – and battle-proven practices – to help you build better models.
  • Moving from BI to Automated Machine Learning Recorded: Feb 21 2018 56 mins
    Jen Underwood
    Machine Learning has become a competitive differentiator in a big data world. Vast amounts of data are already overwhelming existing BI tools and analytics processes. When faced with hundreds of variables, a human’s ability to efficiently identify new insights or detect changing patterns manually has also been exceeded. To address these challenges, BI and analytics professionals are adopting user-friendly, automated machine learning solutions.



    In this on-demand webinar, recognized analytics industry expert Jen Underwood discusses how BI and analytics professionals can get started with automated machine learning.
  • The Fast Path to Success with AI Recorded: Feb 21 2018 54 mins
    Greg Michaelson
    In this webinar, Greg Michaelson, PhD, and Head of DataRobot Labs, reviews the practical first steps an organization takes towards becoming an AI-driven enterprise and remaining competitive in the coming years.
  • Enhancing Customer 360 Models with Automated Machine Learning Recorded: Feb 21 2018 58 mins
    Raju Penmatcha and Justin Dickersson
    Predicting customer behavior is quite challenging. However, knowledge of a customer at an individual level offers enormous benefits. A company with such knowledge can provide better customer experience and retention, targeted marketing, increase sales, and proactive care. But many existing customer models are very macro in nature and fail to deliver at an individual level.

    Machine Learning allows us to build such micro level models by taking into account all digital touch points of a customer with the company. These models will help predict what a customer is going to do next, what their near-future behavior will be and what response to anticipate from an action.

    On this webinar, you’ll hear the current state of machine learning in Customer 360 – and then learn how you can stay one step ahead in building highly customer-centric models for your business.
  • Data Preparation Essentials for Automated Machine Learning Recorded: Feb 21 2018 55 mins
    Jen Underwood
    In order to run successful machine learning projects, and create highly-accurate predictive models for your business, you need effective data preparation. Although machine learning automation provides safeguards to prevent common mistakes, you’ll still want to correctly prepare, shape and format your data to generate optimal models.



    In this on-demand webinar, Jen Underwood, Founder of Impact Analytix reviews how to organize data in a machine learning-friendly format that accurately reflects the business process and outcomes. She shares basic guidelines, practical tips, and additional resources to help get you started mastering the essence of predictive model data preparation.
  • Enhancing Anti-Money Laundering (AML) Programs with Automated Machine Learning Recorded: Feb 21 2018 47 mins
    Dan Yelle
    Compliance organizations within banks and other financial institutions are turning to machine learning for improving their AML compliance programs. Today, the systems that aim to detect potentially suspicious activity are commonly rule-based, and suffer from ultra-high false positive rates. Automated machine learning provides a solution to address this challenge.



    In this webinar, Dan Yelle, a Customer-Facing Data Scientist for DataRobot will show how automated machine learning can be used to reduce false positive rates, thereby improving the efficiency of AML transaction monitoring and reducing costs.
  • Advances in Fraud Detection with Automated Machine Learning Recorded: Feb 21 2018 61 mins
    Justin Dickerson and Igor Veskler
    Preventing fraud is a mission-critical objective of every financial institution, including fintechs. But those committing fraud continue to evolve their tactics to evade detection by even the best prepared organizations.



    On this on-demand webinar, you’ll get an overview of the current state of machine learning in fraud detection – and learn how you can stay one step ahead of those looking to harm your business.
  • Dynamic Risk-Based Pricing in Fintech Recorded: Feb 21 2018 46 mins
    Justin Dickerson and Igor Veskler
    Machine learning has quickly become the tool of choice for pricing a variety of financial products. Instead of utilizing legacy rules-based matrices for pricing, companies have turned to predictive modeling to understand the likelihood of default and overall borrower repayment performance. This has enabled companies to move from older pricing schemes to dynamic risk-based pricing.

    Justin Dickerson, General Manager of Global Fintech for DataRobot and Igor Veksler, a leading Customer-Facing Data Scientist for DataRobot have both worked in the alternative finance industry as data scientists and led this transition to risk-based pricing for their respective organizations. As leaders at DataRobot, they currently share their expertise with clients and potential customers looking to leverage machine learning to make the transition to dynamic risk-based pricing.

    In this on-demand webinar, Justin and Igor describe how DataRobot can help enable your enterprise to leverage automated machine learning to become a leader in risk-based pricing.
  • Is Artificial Intelligence Worth It for Me? Recorded: Feb 20 2018 60 mins
    Greg Michaelson
    Understanding buzzwords, avoiding the hype, and capitalizing on AI.
  • The Making of Data Science Superheroes - with Crest Financial Recorded: Oct 10 2017 53 mins
    Daniel Hinkson, Crest Financial; Ryan Thorpe, Crest Financial; Yong Kim, DataRobot
    Data scientists Daniel and Ryan were the only resources on-hand for Crest Financial's increasing predictive analytics workload, making them feel like mere mortals as they faced the ever-increasing challenge of developing and deploying predictive models to boost their business.

    Enter the DataRobot machine learning automation platform. With DataRobot's help, Daniel and Ryan are quickly transforming into data science superheroes, now able to tackle more projects with better results -- faster than a speeding bullet! In this on-demand webinar, you'll learn how they are helping Crest Financial make better lending decisions while:

    * Completing tasks that once took months -- almost immediately
    * Rolling out models through an easy-to-use and robust enterprise-ready framework
    * Delivering more accurate results to their colleagues and educating management on results
  • A Fireside Chat with Scot Barton of Farmers Insurance Recorded: Sep 19 2017 57 mins
    Scot Barton, Farmers Insurance ; Satadru Sengupta, DataRobot
    In this on-demand webinar, Scot Barton, Head of Business Insurance R&D, provides an overview of how Farmers Insurance created a sustainable, cost-effective, and customer-centric predictive analytics strategy through machine learning automation. 

    Satadru Sengupta, General Manager of Insurance at DataRobot, then reviews the full spectrum of use cases that DataRobot clients are currently solving with machine learning automation - and deliver a demo.

    You'll discover:
    • The critical aspects of predictive analytics
    • The predictive analytics challenges that drove Farmers to consider machine learning
    • How machine learning automation helped Farmers to overcome these challenges
  • Executives: The New Drivers of Data Science Recorded: Sep 14 2016 29 mins
    Tom de Godoy, CTO and Co-Founder at DataRobot
    Sponsored by DataRobot, the leading automated machine learning platform, Executives: The New Drivers of Data Science offers a unique perspective on the executive’s place in the new world of transformative data.
  • What is DataRobot University Recorded: May 5 2016 2 mins
    DataRobot University
    Traditional data science education can be overwhelming. Mathematics, statistics, programming, algorithms — each of these subjects takes years to actually master. What’s worse is that even after learning them you still don’t have the practical skills and experience needed to solve real world business problems.

    DataRobot University starts with the practical, teaching you what you need to know to start solving real world problems immediately. Because most of the technical work can now be automated, training can focus on everything else you need to ensure success. These include topics like scoping and framing data science projects, avoiding common mistakes, and communicating solutions to others in your organization.
  • What is DataRobot Recorded: May 5 2016 2 mins
    DataRobot & Clark
    Meet Clark and find out how he leverages DataRobot to be more efficient and effective in identifying the right data model for his data modeling needs.
Enabling the AI-Driven Enterprise with Automated Machine Learning
DataRobot powers the AI-driven enterprise, enabling users throughout the organization to make business decisions unmatched in simplicity, speed, and accuracy. Its revolutionary approach to automated machine learning harnesses hundreds of cutting-edge algorithms to discover and deploy the best predictive models for every situation and delivers accurate business predictions at scale.

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