{"id": "urn:uuid:e0fa15bb-a2de-440f-96a6-bc3487376fba", "type": ["VerifiableCredential", "OpenBadgeCredential"], "proof": {"type": "Ed25519Signature2020", "created": "2026-07-31T23:37:34Z", "proofValue": "z2YjDrLFuts58K52FUbWDv6nUEvf44hFFNsHX1PqCemLWBiykgjHMSYDGzmnuEBdUKAVmhF1z3JVtdgFYFTEH9XzA", "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": "2026-07-31T23:37:34Z", "credentialSubject": {"type": ["AchievementSubject"], "identifier": [{"salt": "not-used", "type": "IdentityObject", "hashed": false, "identityHash": "ADRIANE PAULIELI COLOSSETTI", "identityType": "name"}], "achievement": {"id": "https://learn.mit.edu/courses/course-v1:UAI_SOURCE+UAI.2", "name": "Python Coding, Part 2", "type": ["Achievement"], "criteria": {"narrative": "- Understand and use Python dictionaries\r\n- Use dictionaries to store appropriate data\r\n- Understand the CSV format and how it represents structured data.\r\n- Read and parse CSV files.\r\n- Convert CSV data into NumPy arrays and Pandas DataFrames\r\n- Create and manipulate NumPy arrays for 1D and 2D datasets.\r\n- Create various plot types using matplotlib.pyplot\r\n- Learn how visualization complements statistical analysis to reveal trends in data\r\n- Understand type abstraction and why it matters in Python programming.\r\n- Create user-defined types with classes, attributes, and methods.\r\n- Build modular code using classes to simulate real-world systems.\r\n- Design simulations of real-life situations using data abstraction and object-oriented design.\r\n- Learn different types of ML problems: classification, regression, and clustering.\r\n- Study how decision trees and random forests work\r\n- Understand overfitting and randomness in ensemble methods\r\n- Apply learned Python skills to explore machine learning examples"}, "description": "ADRIANE PAULIELI COLOSSETTI has successfully completed all modules and earned a Course Certificate in Python Coding, Part 2.", "achievementType": "Course"}, "activityEndDate": "2026-07-31T23:37:34Z", "activityStartDate": "2026-07-31T18:05:46Z"}}