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Data Science for Business Analytics: Introduction to Computing

Enter the world of data science with ease as you gain the skills to use computational statistics for business analytics.

Classroom of students learning about computer studies and data science

Data Science for Business Analytics: Introduction to Computing

  • 3 weeks

  • 5 hours per week

  • Accreditation available

  • Digital certificate when eligible

  • Introductory level

Find out more about how to join this course

  • Duration

    3 weeks
  • Weekly study

    5 hours
  • Languages

    English, Español, Italiano, Français, PortuguêsEnglish, Español
  • 100% online

    How it works
  • Unlimited subscription

    $349.99 for one yearLearn more
  • Accreditation

    AvailableMore info
The CPD Certification Service

This course has been certified by the CPD Certification Service as conforming to continuing professional development principles. Find out more.

Learn the basics of programming with National Tsing Hua University

Programming can provide insights into data beyond what simple statistics can offer. This three-week course will help you use the power of programming to unlock useful concepts in statistics and analytics.

Through interactive materials, you’ll dive into computational statistics for business analytics and learn the basics of programming.

By the end of the course, you’ll possess a new set of coding tools and skills, and understand how this links to your career goals.

Explore computational statistics and data science in practice

You’ll start by delving into computational statistics to see data science in practice. This will help you unpack programming and the different tools you can use for basic statistics.

With this knowledge, you’ll be able to see both the limitations and value of computational statistics for data science.

Produce data visualisations to boost your data analysis

Next, you’ll develop key skills to help you produce data visualisations that will support and boost your data analysis and reporting processes.

You’ll also run simulations to help you gain practical skills and make your inference more robust.

Learn how to perform functions in r and bootstrapping

Finally, you’ll learn how to develop your own functions to personalise and ease up your coding, making it more efficient and clean.

Within this, you’ll discover resampling and bootstrapping as you learn how to explain their outcomes and understand their applications.

Throughout the course, you’ll develop practical skills with hands-on, weekly assignments. You’ll hone your ability by using a tangible real-world dataset to ensure you finish the course with the knowledge to confidently enter the world of statistics and data science.

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Skip to 0 minutes and 9 seconds Statistics and programming are the two skills you need to master data science and business analytics. Maybe you are curious about these skills, or maybe you have taken some courses already. But did you find yourself still wondering about the intuition behind statistics and coding? What do these formulas mean? What is their purpose? And how do they help us face real business challenges? And why do we have to write code to achieve this? In this course, we will see how programming can give you a fresh insight into data analytics. Learn to unpack the true power of a computer. It can help you conduct simulations, run algorithms, and visualize data.

Skip to 0 minutes and 53 seconds I’m Professor Soumya Ray, and I will be your guide through this introduction to computational statistics for analytics. Join us and discover the vivid world of computational statistics, where data analysis comes alive in your computer. This course will take the fear factor out of programming and statistics. You will learn important concepts through visualization and simulation. During the course, you will regularly practice your new skills on real data sets. We will learn all this in a social way. You will review and discuss other learner solutions to see how they approach the same problems. You will read blogs and forums where experts share their real world experience.

Skip to 1 minute and 37 seconds These lifelong habits of reading and sharing are how data scientists keep themselves at the cutting edge at all times. We welcome beginners and experienced learners alike. If you have already studied some basic statistics or programming, this course will give you key insights you may have missed and give you a friendly look at techniques that beginners don’t usually get a chance to see. If you are new to statistics or programming, this can be a fun challenge to teach yourself these techniques for the first time. You’ve got nothing to lose. Give it a shot. Let this course be your foundation to a future in data science and business analytics. Welcome to our class, and see you soon.

Syllabus

  • Week 1

    Computation and Statistics

    • Getting Started

      Welcome to Data Science for Business Analytics: Introduction to Computing. Get to know what you will be learning in this course.

    • Computational Statistics

      In this activity, you will learn what computational statistics is, what are its strong points, and how it serves the society.

    • Programming Tools

      In this activity, you will become familiar with R and RStudio, the tools that we will be using along the course.

    • Basic Statistics

      In this activity, you will become able to to use and interpret basic statistics such as mean, median and standard deviation.

  • Week 2

    Describing and Visualizing

    • Variables and Values

      In this activity, you will learn what is the relationship between variables and values.

    • Data Distributions

      In this activity, you will learn about data distributions and understand what they represent and how to read them.

    • Descriptive Statistics

      In this activity, you will learn how to produce efficient, clean and informative visualizations in R.

    • Simulation and Statistical Inference

      In this activity, you will learn how to simulate data, why is it useful, and get to know more about data distributions.

  • Week 3

    Resampling

    • Functions in R

      In this segment, we will learn how to create functions in R and use them to organize repeated steps in our analysis.

    • Functional Iteration

      In this segment, we will learn how functional iteration, loops, and vectorized iteration help us repeat operations efficiently in R.

    • Resampling Foundations

      In this segment, we will connect central tendency and repeated sampling to the logic of resampling and statistical inference.

    • Standardization

      In this segment, we will learn how standardization, z-scores, the normal distribution, and the Empirical Rule help us interpret data values.

    • Confidence Intervals

      In this segment, we will learn how confidence intervals use sample data to express uncertainty around statistical estimates.

    • Bootstrapping

      In this segment, we will learn how bootstrapping uses resampling with replacement to estimate uncertainty and create confidence intervals.

Who is this accredited by?

The CPD Certification Service
The CPD Certification Service:

The CPD Certification Service was established in 1996 and is the leading independent CPD accreditation institution operating across industry sectors to complement the CPD policies of professional and academic bodies.

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...

  • Produce data visualisations to support and boost your data analysis and reporting processes.
  • Compute and interpret basic statistics.
  • Develop your own functions to personalise and ease up your coding, making it more efficient and clean.
  • Perform resampling and bootstrapping, explain their outcomes, understand their applications.

Who is the course for?

This course is designed for anyone interested in the world of computation for business analytics.

It is ideal for anyone who is approaching the fields of business analytics or data science, such as students, those starting out in these industries, and for aspiring data analysts and data scientists in any industry.

Prior programming knowledge is welcome and will be helpful but not strictly required.

Who will you learn with?

Distinguished Professor of the Institute of Service Science at National Tsing Hua University. Soumya teaches about computational statistics and agentic software engineering.

Who developed the course?

National Tsing Hua University (NTHU)

National Tsing Hua University in Taiwan consistently ranks as one of the premier universities in East Asia.

  • Established

    1956
  • Location

    Taiwan
  • World ranking

    Top 170Source: QS World University Rankings 2021
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  • Learn at your own pace
  • Discuss your learning in comments
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$349.99 for one year

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Develop skills to further your career

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  • Learn at your own pace
  • Discuss your learning in comments
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