Is your product or service worth the price? Even if you think so, an army of competitors is deluging your loyal customers with messages to the contrary. Customer loyalty expert Jill Griffin explains how customers form perceptions of your brand, why they switch brands, and how you can manage the relationship between your brand, your product/service, and your price—so they see why your offering is valuable and remain loyal. She offers seven proven methods to maximize value and differentiate your product/service, drawing on real-world examples from companies such as Zappos, 3M, and Amazon. Plus, get a 10-day action plan that will help your company or team find fresh ways to bring value to customers.

Social engineering is one of the most dangerous forms of hacking because it preys on human nature. Learn how to defend your organization from social engineering by recognizing and thwarting the most common types of attacks. This course provides security teams and professionals with information on common social engineering techniques and safeguards. Instructor Stephanie Ihezukwu—a security analyst and engineer—describes how phishing, vishing, baiting, and physical activities like tailgating all provide entry to bad actors, and explains how training can be the most effective tool to combat these attacks. She also explains how to create policies and procedures; set up controls around passwords, email, and software updates; and conduct tests to see how effective your defenses truly are.

The central task of leaders and managers is to help their people perform at their best and contribute the most. In this course, join #1 New York Times best-selling author Daniel Pink as he shares science-backed methods for effectively motivating others. With his trademark clarity, Pink distills the crucial research on human motivation. And he shares practical takeaways in the three key areas lead to enduring high performance: autonomy, mastery, and purpose. Pink teaches a group exercise to help surface your team’s purpose, then shows you how to create a sense of connection. He explains the secrets of effective feedback and how to promote progress using simple 90-second practices. And since offering employees space to make small changes in their jobs can dramatically boost engagement, Pink walks you through how to carve out small islands of autonomy to spark your team’s innovation and deepen their commitment.

In the world of data analytics, you're consistently presented with the same decision when it comes to how you'll communicate your data and insights. For each project, you need to decide whether to use a dashboard or tell a data story. In this course, business intelligence architect Sara Anstey provides you with the necessary information you need to make this decision with confidence. First, Sara covers the fundamentals of making decisions with data and shares how the role of a data analyst makes this possible for organizations. She then dives into the topics of data science dashboards and data storytelling, highlighting the pros and cons of each and providing the details you need to determine which approach is right for you. Sara closes by recapping key concepts, leaving you prepared to pick between each of these options with ease and intentionality.

This course was created by Madecraft. We are pleased to host this training in our library.

Since the inception of data analytics, the way in which analysts view and interpret data has evolved tremendously. New technologies, tools, and approaches have advanced what's possible with data analytics, and network analysis is no exception. In this course, longtime data analyst and data visualization expert Heather Johnson shares the fundamentals of using graph analytics, or network analysis, when analyzing data. Heather begins by reviewing the components of a network analysis and detailing the advantages of using a graph analytics approach. She then walks through key applications of using graph analytics when reviewing data. To wrap up the course, Heather discusses career opportunities within the realm of graph analytics. Upon completion, you’ll be equipped with the knowledge of what graph analytics is and how it can be leveraged within your analytics career.

This course was created by Madecraft. We are pleased to host this training in our library.

Technology has given organizations an opportunity to work with data in interesting new ways, but now governments, citizens, and customers are taking a close look at how companies use or misuse data. If one of your customers posts harmful information, should you take it down? Can you use data to manipulate your customer’s behavior? The answers to these questions have an enormous impact on how your customer views your organization. Yet, these decisions aren’t happening in the boardroom. Instead, they’re made in much smaller meetings by people just like you. Instructor Doug Rose gives you the understanding and skills you need to discuss these issues in a way that's both meaningful and productive. Doug begins with ethical views that you need to consider. He goes over ways data can be misused, by a company and by a customer. Then Doug goes over the responsibility to be accurate and what you can do when inaccurate materials are propagated. He concludes with an overview of data challenges. This course was created for LinkedIn Learning by Doug Rose. We are pleased to offer this training in our library.

The revolution in data science has transformed, for better or worse, the way companies do business in the last few decades. But data science isn't just for capitalists. AI is one of the most important forces for change developed in the last century, and we've only begun to recognize its true power and potential. In Data for Good: Using Data Science in Nonprofits and NGOs, Martin Kemka examines how data science and machine learning can be used outside of the for-profit sector. He covers parameters for how data works to influence our world, how the data-for-good concept can be applied, how to determine the best problems to solve with data, and what tools are needed. Martin also provides real-world case studies and challenges to further illustrate the lessons.

Learning the basics of data science and how to apply them in Java opens up a world of possibilities for you, in terms of building software and job opportunities. In this course, instructor Shaun Wassell takes you through the skill sets required for data science, shows you how to visualize data in Java, and explores different methods of turning data into information. Shaun introduces some basic concepts and examples of data science, then walks you through the process of representing data in Java and some difficulties you may encounter. He discusses data manipulation techniques like mapping, filtering, collecting, and sorting. Shaun describes how to find, gather, clean, manipulate, and store data, so that you can start doing useful things with it. Next, he shows you the fun part: different methods you can use to turn data into information. Shaun covers Nearest-Neighbor, Bayes, linear regression, decision trees, clustering, and more.

Data mining is the area of data science that focuses on finding actionable patterns in large and diverse datasets: clusters of similar customers, trends over time that can only be spotted after disentangling seasonal and random effects, and new methods for predicting important outcomes. In this course, instructor Barton Poulson introduces you to data mining that uses the programming language Python. Barton goes over some preliminaries, such as the tools you may use for data mining. He discusses aspects of dimensionality reduction, then explains clustering, including hierarchical clustering, k-Means, DBSCAN, and more. Barton covers classification, including kNN and decision trees. He goes into association analysis and introduces you to Apriori, Eclat, and FP-Growth. Barton steps you through a time-series decomposition, then concludes with sentiment scoring and other text mining tools.

Data science continues to grow in sophistication and demand at an exponential rate. Data mining is the area of data science that focuses on finding actionable patterns in large and diverse datasets: clusters of similar customers, trends over time that can only be spotted after disentangling seasonal and random effects, and new methods for predicting important outcomes. Instructor Barton Poulson focuses on data mining in R, presents a broad range of algorithms including machine learning methods, and offers important information on laws and policies that affect data mining. Barton gives an overview of dimensionality reduction. He introduces clustering, including hierarchical clustering, then goes into association analysis. He explains time-series mining and decomposition, then concludes with text mining, sentiment analysis, and sentiment scoring.

The term “knowledge graph” describes a semantic search based on the systematic compilation and processing of data and was first coined by Google. Leading internet companies have been using knowledge graphs for several years to present information that is tailored to customers’ needs. You can also use knowledge graphs to map your company’s internal knowledge and improve search results. Knowledge graphs can also improve the results of AI or machine learning systems. In this course, blockchain technology leader Daniel Burgwinkel explains what knowledge graphs are, offers examples and use cases, gives you practical recommendations on how to implement knowledge graphs, and shows you how to build a knowledge base. This course is aimed at data stewards, digital transformation managers, and data scientists who are responsible for data stocks and knowledge management.

There is an increasing recognition that data science needs to go beyond small-scale experimentation to a large-scale implementation. In this course, Neelam Dwivedi brings software engineering and data mining methodologies to data scientists, then applies these ideas by taking a simple business need through an entire life cycle—hosting a model, consuming it in a web application, and setting up its CI/CD pipeline. Neelam begins by explaining the methodologies used in the course and how they are combined. She shows you where to begin in developing architecture and deploying a model, then explains how larger web applications may consume the model as a service. Neelam covers how to stage your model and the app, as well as how to plan ahead with an overall roadmap. She concludes with thoughts on how to further applications of data science methodologies.

Data stewardship programs help organizations achieve the maximum value from their information assets. In this course, instructor Mike Chapple shows you the basic foundations of data stewardship and best practices for getting your own data stewardship program off the ground. Mike explores the roles, qualities, and responsibilities of a data steward. He goes over best practices for maintaining data quality, then explains the many protections that go into maintaining data security. Mike discusses privacy controls and the patchwork of international, national, and local laws that govern data security and privacy. He concludes with useful steps you can take in building a data stewardship program.

Tidy data is a data format that provides a standardized way of organizing data values within a dataset. By leveraging tidy data principles, statisticians, analysts, and data scientists can spend less time cleaning data and more time tackling the more compelling aspects of data analysis. In this course, learn about the principles of tidy data, and discover how to create and manipulate data tibbles—transforming them from source data into tidy formats. Instructor Mike Chapple uses the R programming language and the tidyverse packages to teach the concept of data wrangling—the data cleaning and data transformation tasks that consume a substantial portion of analysts' time. He wraps up with three hands-on case studies that help to reinforce the data wrangling principles and tactics covered in this course.

Ongoing, regular administration is critical to the security and performance of databases such as SQL Server. In this course—the fourth installment in the Database Foundations series—explore vital techniques and best practices for administering a database. Instructor Adam Wilbert covers a variety of core concepts, including how to secure a server with user authentication and roles, protect your database by setting up permissions for authorized user accounts, and perform a backup and restore. Adam also offers expert tips for ensuring that a database remains available, even through hardware maintenance, upgrades, and failures. Along the way, he provides tips for working effectively with both SQL Server and PostgreSQL.

While learning about the individual components of a software development stack like databases, programming languages, and interfaces is important, combining multiple technologies that each contribute a piece to the whole is where all the knowledge really comes together. In this fifth and final course of his Database Foundations series, database expert Adam Wilbert explores the role of relational databases in the larger landscape of application development. He examines the architecture of modern apps and how databases integrate with presentation and logic, and how all these building blocks of software development fit together. To do so, Adam shows two different approaches of how to integrate a database with a web server and details the components that allow you to build custom interfaces for your data, in order to provide end users access to your databases from any web browser.

Node.js developers often consider MongoDB to be their main choice when building a data-driven application—but many alternatives may provide better solutions. In this course, learn about the various database options available for Node.js applications, so that you can select the right database for your app. Daniel Khan reviews the basics of relational and nonrelational databases, and explains how—and when—to use document databases with Node.js. He also covers using key-value stores and relational databases with Node.js, demonstrating how to work with MySQL and Sequelize.

Are you new to DaVinci Resolve? Are you intrigued by the power of this digital video media creation tool? Do you find the power of this tool intimidating or confusing? Then this title is for you. Join instructor and professional colorist Patrick Inhofer in this course designed to get you up to speed in as little time as possible. This course includes a 60-second commercial for you to work with so you can get comfortable with the layout and workflow as you follow along. Patrick starts with the process of importing your media, using both manual and automated tools, before showing how to start building a rough cut in Resolve. He then explains how to refine your rough cut using trim tools and adding titles and transitions, details the important aspects of color correction, and shows how to organize and mix sound clips. Patrick finishes the course covering the export process, showing how to use preset templates as well as how to create your own reusable custom templates.

DaVinci Resolve is a leading professional color grading solution used for digital intermediates (the digital color grading of film-acquired sources, to be printed back out to film for theatrical exhibition). It’s not surprising that its color management tools are used every day in major film productions all over the world. In this course, professional colorist Patrick Inhofer takes an extensive look at the color page in DaVinci Resolve, starting with the settings and preferences that have a significant impact on color manipulations. He then covers the concept of primary corrections and the tools used for establishing a base color correction, as well as secondary corrections and how to isolate and minimize problematic areas of the image. Patrick also shows how to combine primary and secondary color operations to enhance viewer engagement, and shares tips for improving your shot-matching skills to help your story have a better visual flow.

This course was created by Patrick Inhofer. We are pleased to host this training in our library

DaVinci Resolve is constantly being updated and refined. In this course, instructor Patrick Inhofer shows you how to work smarter with this feature-rich platform, sharing important workflows and options that every Resolve editor, colorist, VFX artist, or audio mixer should understand. Learn how to efficiently manage databases and project files, customize the user interface to suit your personal preferences, and optimize playback performance—including how to leverage Render Cache and proxy options. Plus, discover how to move a project between Premiere Pro or Final Cut Pro and DaVinci Resolve, as well as add additional hardware to speed up your editing, color grading, or mixing workflows.