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Level 6 Diploma in Information Technology

Applied Descriptive Analytics

IT602 · Advanced Data Analytics — Week 5 of 16

CourseIT602
Week5 of 16
SemesterI
TutorOnline in the course chat

This week’s topics

Applied Descriptive Analytics

  1. Exploratory data analysis using Python or R
  2. Central tendency and dispersion metrics
  3. Customer segmentation profiles for operational decisions
  4. Quantitative Data Analysis 101 Tutorial: Descriptive vs Inferential Statistics (With Examples)
  5. 8 Market Segmentation: How to Define Optimal Customer Segments
  6. Descriptive statistics and data visualisation. An introduction to statistics and working with data
  7. Data Visualization in Python - Seaborn

What you will be able to do

  • 3.2 Apply an appropriate programming language or tool to demonstrate how descriptive analytic techniques contribute to decision-making.

Activity

Start with this week’s 4 videos, then: Seminar, guided reading and a short written task: apply an appropriate programming language or tool to demonstrate how descriptive analytic techniques contribute to decision-making.

Study materials

Videos

  • Quantitative Data Analysis 101 Tutorial: Descriptive vs Inferential Statistics (With Examples) · YouTube · Grad Coach · 28 min · for registered students
  • 8 Market Segmentation: How to Define Optimal Customer Segments · YouTube · Marketing Insights · 7 min · for registered students
  • Descriptive statistics and data visualisation. An introduction to statistics and working with data · YouTube · Global Health with Greg Martin · 14 min · for registered students
  • Data Visualization in Python - Seaborn · YouTube · TU Delft · 11 min · for registered students
  • Session 3: Descriptive Statistics · YouTube · Aswath Damodaran · 19 min · for registered students

Further resources

  • Introduction to Python Programming, ch. 15: Data Science · PDF · OpenStax, textbook chapter; pp. 341–397 · for registered students
  • Learning Statistics with R (Navarro, v0.7.1), ch. 5: Descriptive statistics · PDF · Other, textbook chapter; pp. 158–213 · for registered students
  • Introductory Business Statistics 2e, ch. 2: Descriptive Statistics · PDF · OpenStax, textbook chapter; pp. 57–148 · 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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Admitted students ask questions on this week’s page in the student portal: an AI assistant trained on the course answers first, and during the course’s timetabled classes Connect to your tutor brings your tutor into the chat, who may start a call if needed.

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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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