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Level 6 Diploma in Information Technology

Applied Model Synthesis, Governance, and Visual Interpretation

IT602 · Advanced Data Analytics — Week 11 of 16

CourseIT602
Week11 of 16
SemesterI
TutorOnline in the course chat

This week’s topics

Applied Model Synthesis, Governance, and Visual Interpretation

  1. Assessing ethical implications and algorithmic bias
  2. Model drift and monitoring
  3. Communicating strategic findings through interactive visualisations
  4. MIT 6.S191: AI Bias and Fairness
  5. Data Governance vs. Model Governance: Building a Strong Foundation for AI
  6. Dr. Olya Kadina on the ethical implications of AI during OAY

What you will be able to do

  • 2.2 Critically evaluate potential issues in the preparation of data for use in an applied analytical model.
  • 3.1 Critically evaluate methods to visualise the output from an applied analytical model.

Activity

Start with this week’s 3 videos, then: Seminar, guided reading and a short written task: critically evaluate potential issues in the preparation of data for use in an applied analytical model.

Study materials

Videos

  • MIT 6.S191: AI Bias and Fairness · YouTube · Alexander Amini · 43 min · for registered students
  • Data Governance vs. Model Governance: Building a Strong Foundation for AI · YouTube · IBM Technology · 6 min · for registered students
  • Dr. Olya Kadina on the ethical implications of AI during OAY · YouTube · TU Delft · 10 min · for registered students
  • Anna Martirosyan: Ethical AI, Model Governance, and the Future of Responsible Finance · YouTube · CFA Institute · 26 min · for registered students
  • Addressing Algorithmic Bias • Muniba Talha • GOTO 2022 · YouTube · GOTO Conferences · 43 min · for registered students

Further resources

  • Foundations of Information Systems, ch. 8: Data Analytics and Modeling · PDF · OpenStax, textbook chapter; pp. 297–338 · for registered students
  • Information Systems for Business and Beyond (2019), ch. 12: The Ethical and Legal Implications of Information Systems · PDF · Other, textbook chapter · for registered students
Materials marked “for registered students” open in the student portal, which is set up as soon as you receive final acceptance.
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Course plan
  • Week 1: Foundations of Data Analytics
  • Week 2: Evaluation of Analytical Frameworks
  • Week 3: Data Ingestion and Pipeline Architecture
  • Week 4: Data Preprocessing Pitfalls and Data Quality
  • Week 5: Applied Descriptive Analytics
  • Week 6: Predictive Analytics for Trend and Demand Forecasting
  • Week 7: Advanced Predictive Classification Models
  • Midterm: Midterm evaluation
  • Week 9: Prescriptive Analytics and Optimisation Modelling
  • Week 10: Model Output Visualisation and Visual Analytics
  • Week 11: Applied Model Synthesis, Governance, and Visual Interpretat…
  • Week 12: Applying Advanced Data Analytics in practice: case studies
  • Week 13: Assignment workshop: research, planning and referencing
  • Week 14: Assignment workshop: drafting, feedback and improvement
  • Week 15: Review and coursework completion
  • Final: Final assessment and submission
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