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Introduction to Data Science for Business

Build a solid foundation in data science and learn how to analyse data and communicate insights in a business environment.

750 enrolled on this course

Woman looking at information and data on a clear screen in front of her.

Launch a career as a data scientist

Traditionally data was mainly collected from single or very few sources, classed as ‘structured’ and simple to analyse. Enter the era of ‘big data’. Data is now being generated from a plethora of sources at unprecedented volumes and this significant rise in unstructured data has created challenges that are driving the demand for data science skills worldwide.

On this four-week course, you’ll gain a foundational knowledge of data science for business applications, which can act as a launchpad to set you on an exciting career path to becoming a successful data scientist.

Discover the business value of data science

This course will show you the business value of data science, from data security to predicting market trends. You’ll also delve into the data science life cycle and how to identify and frame business needs to solve problems.

Explore the scientific approach to data science

Data science is a multidisciplinary domain that uses scientific methods, processes, algorithms, and systems to draw knowledge and insights from unstructured data.

During the second week, you’ll dive deeper into solving business problems with data. You’ll learn how to design a structured thinking problem, build a hypothesis, and then test it to discover a solution to a business need.

Learn to use spreadsheets for data analysis and visualisation

The second half of this course will introduce you to data analysis, data visualisation and using Excel to perform and display your analysis.

You’ll explore the different functions of Excel and how to create formulas and build charts. You’ll then learn the communication frameworks to help you communicate your insights to stakeholders in a concise and engaging way.

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.

When would you like to start?

Start straight away and join a global classroom of learners. If the course hasn’t started yet you’ll see the future date listed below.

  • Available now

Learning on this course

On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.

What will you achieve?

By the end of the course, you‘ll be able to...

  • Explain the business value of data science
  • Apply the scientific method to business problems to take an analytical approach to define and test hypotheses
  • Perform basic data analysis using spreadsheets
  • Create data visualisations to support data analysis and communicate insights with diverse stakeholders.

Who is the course for?

This course is designed for anyone interested in a career in data science. It will also be useful to anyone looking to understand how data science teams can play a role in enhancing business performance.

Who developed the course?

FutureLearn

FutureLearn is jointly owned by The Open University and The SEEK Group and has been providing online courses for learners around the world over the last eight years.

In collaboration with

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