{"id": "urn:uuid:2297c5f3-38c5-4ece-9045-e2650bc95e63", "type": ["VerifiableCredential", "OpenBadgeCredential"], "proof": {"type": "Ed25519Signature2020", "created": "2026-07-04T14:56:55Z", "proofValue": "z3yiJkMGguCzRbM2DDY8P6XYtJWkLnZvpX4j1oBu4SDH4n9Hp96XWhEiuu37CrgKSv7Sa2ppcNJYuXfyP68bJ9cQW", "proofPurpose": "assertionMethod", "verificationMethod": "did:key:z6MkfwJEckNVbaLwbCETHMYkpfb7g2Nnvqn78ASyrYJfqvow#z6MkfwJEckNVbaLwbCETHMYkpfb7g2Nnvqn78ASyrYJfqvow"}, "issuer": {"id": "did:key:z6MkfwJEckNVbaLwbCETHMYkpfb7g2Nnvqn78ASyrYJfqvow", "name": "MIT Learn", "type": ["Profile"], "image": {"id": "https://learn.mit.edu/images/mit-red.png", "type": "Image", "caption": "MIT Learn logo"}}, "@context": ["https://www.w3.org/ns/credentials/v2", "https://purl.imsglobal.org/spec/ob/v3p0/context-3.0.3.json", "https://w3id.org/security/suites/ed25519-2020/v1"], "validFrom": "2026-07-04T14:56:55Z", "credentialSubject": {"type": ["AchievementSubject"], "identifier": [{"salt": "not-used", "type": "IdentityObject", "hashed": false, "identityHash": "Nikolaos Papakonstantinou", "identityType": "name"}], "achievement": {"id": "https://learn.mit.edu/courses/course-v1:UAI_SOURCE+UAI.5", "name": "Foundations of Neural Networks", "type": ["Achievement"], "criteria": {"narrative": "- Describe how perceptrons and multilayer networks form the basis of neural network predictors.\r\n- Distinguish between structured data (e.g., tables) and unstructured data (e.g., images, text).\r\n- Explain how neural networks handle underfitting, overfitting and generalization.\r\n- Understand the role of embeddings in representing unstructured data.\r\n- Summarize the key building blocks that make neural networks flexible models for different data types."}, "description": "Nikolaos Papakonstantinou has successfully completed all modules and earned a Course Certificate in Foundations of Neural Networks.", "achievementType": "Course"}, "activityEndDate": "2026-07-04T14:56:55Z", "activityStartDate": "2026-06-15T18:51:03Z"}}