Syllabus

• Week 1

  The business value of data science

  • Welcome to the course

    Before we dive into data science and its applications in business, let’s understand how this short course is designed. In this topic, we will cover the structure and learning outcomes of this short course.

  • Introduction to data science

    Data forms the crux of data science. It is essential for a data scientist to understand what data is, its sources, and its types. In this topic, you'll learn about the data science domain and the opportunities it presents.

  • Data science in business

    Data science is becoming ubiquitous in business. In this topic, you will learn the data science life cycle – a framework used to plan and execute successful data science business projects.

  • Data analytics

    Data analytics is a subset of data science that involves analysing and visualising data. In this topic, you will learn about the relationship between data science and analytics and dive deep into data analytics, and its process.

• Week 2

  Scientific approach to data science

  • Data science as a science

    In this topic, you will learn about the various structured thinking frameworks that you can use as a data scientist to solve complex business problems using data science in a structured and scientific manner.

  • Generating a hypothesis

    After you identify the structured-thinking approach to resolve your business problem, the next step is to start hypothesising the root cause(s) behind the business problem. In this topic, you will learn to formulate a hypothesis.

  • Hypothesis testing

    After forming the hypothesis, the next logical step is to check its validity. You will learn how to test a hypothesis and set it as null or alternative in this topic.

• Week 3

  Performing data analysis

  • Introduction to data analysis

    Data scientists leverage various statistical operations to describe and manipulate data sets. Within this topic, you will learn how to leverage descriptive statistics to describe a data set.

  • Fundamentals of spreadsheets

    In this topic, you will learn the basics of working with spreadsheets and the various functions and formulas it offers for data analysis.

  • Performing data analysis using Excel

    The process of data analytics involves importing, tidying, transforming, and communicating data insights. In this topic, we will be learning about the first three steps – importing, tidying, and transforming data.

• Week 4

  Data visualisation using spreadsheets

  • Introduction to data visualisation

    You’ve probably heard the expression, ‘A picture is worth a thousand words’. This holds true in data science! In this topic, you'll learn about the different types of data visualisations such as charts and dashboards.

  • Visualising data using Excel

    Excel offers a variety of tools to create effective and engaging data visualisations. In this topic, you will learn how to create charts in Excel to analyse, identify, and present your data insights through a practical activity.

  • Communicating insights

    In this topic, you will learn how to create data visualisations to appeal to and engage your audience. You’ll learn about one of the key communication frameworks used in data visualisation: Storytelling.

  • Ethics in data science

    Ethical consideration is a key area in data science. In this topic, you will learn about the role of ethics in data science and how to implement ethical data science practices in organisations.