Privacy, Security and Responsible AI Basics Roadmap

Every developer is now expected to handle user data safely. Learn the habits, the law in outline and the risks of AI features.

8 milestones · ~72 hours total

1. 1

   Security mindset

   ~6h

   Threat modelling in plain terms: what are we protecting, from whom, and what is the cheapest defence?

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2. 2

   Authentication and secrets

   ~10h

   Password hashing, sessions vs tokens, multi-factor auth and keeping keys out of code and logs.

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3. 3

   Common web vulnerabilities

   ~16h

   Injection, XSS, CSRF, broken access control and insecure dependencies, with how to prevent each.

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4. 4

   Data protection basics

   ~8h

   Collect only what you need, encrypt in transit and at rest, set retention limits and delete on request.

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5. 5

   India's data protection law

   ~8h

   Outline of the Digital Personal Data Protection Act and Rules: consent, notice, purpose limits, user rights and breach reporting. Confirm current deadlines with official sources.

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6. 6

   Secure development workflow

   ~10h

   Dependency scanning, code review for security, least-privilege access and incident response basics.

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7. 7

   Security of AI features

   ~8h

   Prompt injection, data leakage through prompts and logs, and keeping tools behind permissions.

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8. 8

   Responsible AI

   ~6h

   Bias, transparency, human oversight and telling users when they are talking to an AI or when content is generated.

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