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Data Privacy
Privacy engineering : why it's needed, how to scale it -- Understanding data and privacy -- Data classification -- Data inventory -- Data sharing -- The technical privacy review -- Data deletion -- Exporting user data : data subject access requests -- Building a consent management platform -- Closing security vulnerabilities -- Scaling, hiring, and considering regulations.
Top Privacy Concerns for Small Businesses
Unlike large companies, small companies cannot always hire privacy specialists or buy pricey third-party tools. In this course, instructor Nishant Bhajaria provides an easy-to-understand, practical primer on privacy, security, and compliance. He shows hands-on leaders what obligations are created by laws like GDPR and CCPA, identifies techniques to detect privacy risk in data handling and product development, demonstrates how to implement tools and processes to manage access to sensitive data, and much more. This course can help you build tooling for critical functions like data inventory; data sharing and export; data subject access requests; deleting account and event streaming data; capturing; storing and updating user consent; and addressing security vulnerabilities that could cause privacy harm. After taking this course, companies will be able to prioritize and execute on their privacy priorities intelligently, reduce risk, manage compliance, and build user trust.
Privacy for Executives and Aspiring Executives
Privacy is top of mind for all of today's business leaders, because it is getting attention from regulators, media, privacy activists, and customers. However, amid a profusion of laws, product offerings by vendors, and media coverage, executives often struggle to get clear guidance and options on how to execute a privacy program. This course helps C-level leaders, their deputies, and other aspiring executives develop an understanding of the privacy landscape and capabilities and build a program to stay ahead of the curve-while continuing to grow their business. Instructor Nishant Bhajaria provides strategies to build a program that will be flexible and measurable. Such a program will involve a team that can manage risks in partnership with the rest of the business, provide solutions, measure progress, and inform decision-making. After taking this course, executives will have a template to not just start their teams, but also embed them into the business.
Implementing a Privacy, Risk, and Assurance Program
In today's highly regulated and privacy-aware market, a single misstep could cost you both your customers and your credibility. To keep your users safe, it's important to know how privacy has changed both the economy and the overall business landscape, as well as which steps you must take to keep your information secure. In this course, join Nishant Bhajaria as he steps through how to design a cross-functional privacy program. Nishant details the challenges in data privacy and expectations on the part of regulators, industry stakeholders, and your consumers. He also delves into foundational privacy concepts, how they relate to the business landscape, and how you can create, measure, and scale a privacy culture and program in your company.
Inclusive Tech: Building Your Team
Given the tech industry's role in everyday life-from products and services to employment-there's almost no one untouched by tech companies. For this reason, bias and inclusivity in tech are so important. While companies are focused on new technology to shape a better world, inclusivity often gets overlooked. Many managers have a moment when they feel lost on how to handle inclusivity, and other moments when they feel like they are making progress. While there are many skills taught in engineering school, we learn inclusivity on the job and often outside of it. In this course, Nishant Bhajaria shows managers and leaders how to bridge that gap. He looks at the dimensions of diversity a leader can use to foster inclusion-from introversion vs. extroversion, to education and demographics-and provides strategies for developing an inclusive environment.
Privacy by Design: Data Classification
Companies often collect customer data with third parties to enable better products and growing engagement, as well as for safety reasons. But users expect-and deserve-that their information is handled with great care. In this course, instructor Nishant Bhajaria steps through how to create an architecture to manage data collection and measure risk, as well as afford privacy protections relative to that risk. This architecture-which is a combination of technology, techniques, and processes-can enable companies to be more disciplined with data while collecting and processing it. Nishant goes over the current privacy landscape, explains how classifying data can save you money in the long run, and shares what the data classification process should look like. He also takes a deep dive into the data inventory process, explaining how to best approach it and discern whether it is succeeding. Finally, Nishant provides context on executive communication on privacy governance. Note: Want to continue learning how to strengthen your organization's privacy infrastructure? After wrapping up this course, check out the final installment in this series, Privacy by Design: Data Sharing.
Tech Soft Skills: Searching, Interviewing, and Landing a Job
Too many engineers focus on building hard technical skills, but do not receive the guidance or coaching necessary to make a strong case for their candidacy during the recruitment process. By focusing on the "what"-programming languages and infrastructure stacks-and the "how"-engineering and troubleshooting-they lose sight of the strategic "why." This context gap routinely hurts engineers when they apply for roles and when they try to present their point of view on the job. In this course, tech leader Nishant Bhajaria describes the tech recruitment process and explains how to present yourself on your resume, ask the right questions, and make your case in the interview. These soft skills are indispensable-giving you a better chance at landing the right role and succeeding in the actual job.
Privacy-Preserving Machine Learning
Keep sensitive user data safe and secure without sacrificing the performance and accuracy of your machine learning models. In Privacy Preserving Machine Learning, you will learn: Privacy considerations in machine learning Differential privacy techniques for machine learning Privacy-preserving synthetic data generation Privacy-enhancing technologies for data mining and database applications Compressive privacy for machine learning Privacy-Preserving Machine Learning is a comprehensive guide to avoiding data breaches in your machine learning projects. You’ll get to grips with modern privacy-enhancing techniques such as differential privacy, compressive privacy, and synthetic data generation....
Data for All
Take control of your personal data. Learn how companies manipulate and exploit your data and what you can do to access, delete, and monetize it yourself. Both a handbook and a manifesto, Data for All is a must-read for anyone who wants to take control of their personal data. It lays out how businesses collect, use, and exploit your data, and clearly explains the legislation that will overturn the existing system. Follow John Thompson’s direct and accessible guidance and you’ll completely change your relationship with your data. In this fascinating book, you will learn how to oversee who accesses your data, how much different types of data are worth, and how to keep private details private. You’ll soon stop being a passive source of free data, and start earning a “data dividend”—hundreds or thousands of dollars paid out simply for your daily online activities. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
Practical Data Privacy
Between major privacy regulations like the GDPR and CCPA and expensive and notorious data breaches, there has never been so much pressure to ensure data privacy. Unfortunately, integrating privacy into data systems is still complicated. This essential guide will give you a fundamental understanding of modern privacy building blocks, like differential privacy, federated learning, and encrypted computation. Based on hard-won lessons, this book provides solid advice and best practices for integrating breakthrough privacy-enhancing technologies into production systems. Practical Data Privacy answers important questions such as: What do privacy regulations like GDPR and CCPA mean for my data work...
