Every AI model carries ethical risk, every blockchain carries an attack surface, and every customer record carries a privacy obligation. This Specialization builds AI ethics, blockchain security, and data privacy skills together: apply machine learning algorithms like XGBoost and CNNs alongside causal models and transformer-based NLP, run STRIDE threat modeling to harden smart contracts and wallets against real-world crypto attacks, and build a privacy program spanning data inventories, consent, and secure destruction. You'll leave equipped to design AI systems, blockchain architectures, and data programs that are technically sound, secure, and genuinely trustworthy.
Courses in this learning path or series 3
Practical Privacy for Products and Services
Protect Your Data: An Introduction to Blockchain Security
Advanced AI: Techniques, Applications, and Ethics
Advantages and disadvantages
Advantages
Structured courses with graded quizzes, assignments and deadlines you can reset.
A shareable certificate from the university or company when you pay.
Financial aid is often approved for students in India (apply 15 days before you need it).
Self-paced: start any time.
A clear syllabus (3 parts) you can see before you start.
Disadvantages
Paid after a 7-day free trial (Coursera Plus or per course).
Some courses can be audited for free, but graded work and certificates need payment.
Some points apply to every course of this kind; see how we rank.
This course is paid. Here is how to take it for free
Free trials: You can start a 7-day free trial for many individual courses, Specializations, or a Coursera Plus subscription to test full course features. Cancel before the seventh day if you do not want to be charged.
Financial aid: If you cannot afford the fee for a certificate, you can apply for financial aid through the link on the course home page by filling out an application about your background and goals.
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