Data Science · Beginner level

Beginner level · Module 1 of 5 · 10 guided hours

The Data Science Process

See how data science turns questions into evidence for decisions, where data comes from and the tools used in this program.

Learning objectives

  • Describe the stages of the data science life cycle
  • Turn a vague question into a specific, answerable data question
  • Set up Python, Jupyter or Colab and pandas

Topics

  • question to insight
  • the data science life cycle
  • types of data
  • data sources: surveys, administrative records, mobile data collection
  • notebooks
  • pandas basics

Lessons

  1. Lesson 1 From Question to Insight

    Understand the data science life cycle and why every analysis must start with a clear question tied to a decision.

    data questiondecisionlife cycle stagesinsight

  2. Lesson 2 Data Types and Sources

    Recognise different kinds of data and where organisations get it, with the strengths and weaknesses of each source.

    numeric and categoricalordinalsurveys and administrative datamobile data collection

  3. Lesson 3 Tools: Notebooks and pandas

    Set up a notebook environment and use pandas to load, inspect and select data.

    DataFrameread_csvhead, info, describefiltering rows

Practical activity

Rewrite five vague requests from a manager ("tell us about our students") as specific data questions, each with the data needed and the decision it supports.

Expected outcomes

  • Clear, answerable data questions
  • A working analysis environment

Assessment

Question-framing exercise and an environment check that loads and summarises a CSV file.

Free taster lesson The Data Science Lifecycle Read a free self-study lesson on this topic in the Free Course Library.

Taught live by an instructor — online or in person. Free course lessons are for self-study and do not lead to a certificate — see registration options.