Privacy engineering skills make you invaluable to fast-growing companies. Get the resources and support you need to become a privacy engineer. Reduce risk for your company. Fast-track your career.
Data Protocol’s Privacy Engineering Certification is your opportunity to learn from trailblazer and industry leader Nishant Bhajaria. Now’s the time to skill up – quickly, and in a platform designed for you.
Data Protocol trains and certifies software builders in responsible data management. The time to apply privacy training and data best practices is before there is a problem, not after.
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This certification consists of three modules: Governance, Systems, and Execution. After successfully completing each module, you will receive a shareable badge. Once all three modules are complete, you will be eligible to purchase the comprehensive final assessment to earn your Privacy Engineering certification. The fee for the final assessment is $495.
Data classification is the foundation of privacy engineering. If you can’t identify and measure the risk profile of your data, you can’t manage its value, its flow, or its security. This course will teach you how to classify and map data throughout your systems according to its risk level, retention requirements, and access policies.
With a strong foundation of data categorization in place, this course will teach you the techniques to optimize data flow in support of privacy and business operations. Specifically, you will learn about tagging data, building a system architecture to discover data, and measuring the success of your categorization program. These techniques will enable you to identify all of your data and automate privacy.
The importance of data privacy and the rise of privacy engineering has driven innovation and availability of privacy technologies. As a privacy engineer, you have options. Determining what tools to use for your specific needs is an important part of the job. In this course, you will begin to consider what tools you will need to execute your plan, and why. Specifically, you will learn some of the key players in the privacy tooling space, the criteria you should use when shopping for solutions, and the pros and cons of building versus buying.
You have learned how - and why - privacy should be designed into your systems, your processes, and your products. As a privacy engineer, you work to limit risk as early as possible with both a strategic plan and the right tools. It is also your job to maintain the program you’ve designed and built by continually assessing risks and protections. In this course, you will learn a new approach to the traditional privacy review, a process that often occurs too late. Implementing ongoing technical privacy consulting throughout your existing program will reduce risks and avoid costly mitigations.
Data management should start at the source. Implementing an effective consent management system is critical to protecting and operationalizing data. You will learn how to secure and maintain informed, granular consent to comply with data regulations and promote user trust. You will also learn how to implement a flexible Consent Management Platform and manage the common complexities created by multiple variables, such as features, locations, and version control.
A privacy engineer does not need to be a security expert, but you do need to understand how to manage and use data securely. In this course, you will learn how to build a framework that reduces the attack surface for sensitive data and how to implement tools for the management of access control and monitoring, such as Access Control Lists (ACLs) and encryption keys.
Data deletion is critical to regulatory compliance and overall privacy protection. Effective data classification and categorization enable data deletion upon request or once it is no longer required. In this course, you will learn about implementing, automating, and scaling deletion in a distributed environment. This includes the basics of deletion, how designing a process for deletion relies on understanding the data collection architecture, and the tools and processes you will use from implementation to scaling.
Data is most at risk when it’s in motion, but data sharing is a necessity to support customer engagement, business continuity, and product innovation. Effective privacy engineering eliminates the need to choose between the two. In this course, you will learn to prioritize data minimization, anonymization, and channel segmentation to protect data in motion while maintaining its availability. Finally, you will learn how to quantify the impact of your efforts to manage privacy risk.
Once all three modules are complete, you will be eligible to purchase the final assessment and earn your Privacy Engineering certification and badge. The fee for the final assessment is $495.
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