Course 2



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Course 2 Overview

This online course consists of 3 modules as described and illustrated below.

400: Data Acquisition (1.5 hours)

Module 400

This module aims to introduce you to:

  • The main goals and benefits of digital biomanufacturing
  • What data can and should be captured for biomanufacturing purposes
  • How data acquisition is foundational for both data analytics and data visualization

The learning objectives of this module are that you will be able to:

  • Identify key goals of digital biomanufacturing
  • List the characteristics of big data
    (the 3 V’s plus 2)
  • Define structured data, unstructured data,
    and metadata
  • List the four main steps of digitizing data
  • Define what main types of data can and should
    be acquired for biomanufacturing
  • List key activities of data governance
  • Explain the meaning of the Industrial Internet
    of Things (IIoT)

510: Computer system validation (1 hour)

Module: 410

This module aims to introduce you to data visualization by helping you:

  1. Introduce you to system validation and its importance
  2. Give you an introduction into Data Governance
  3. Introduce you to IT systems and the risks and control measures associated with such systems

The learning objectives of this module are that you will be able to:

  • Explain why understanding business objectives, your audience, and insight needs all help you to better communicate data visually
  • Apply a set of design steps to create a new graph
  • Critically evaluate any visualization in terms of how informative and emotive it is using a set of criteria

520: Equipment considerations for data integrity (1 hour)

Module: 420

This module aims to give you an introduction to data analytics and how to DISCOVER, PREDICT, and PRESENT insights using data analytics tool. Some of the questions that will be asked during this module include:

  • What are the main types of analytics used to get insights from data?
  • What is exploratory data analysis?
  • How is data science different to business intelligence?
  • What team members will I likely need to work with?
  • What is the #1 challenge that organizations face regarding analytics?
  • What are some of the common analytics tools used in biomanufacturing?

The learning objectives for this module will allow you to:

  • Define the three main types of analytics on the analytics spectrum
  • Explain the purpose of exploratory data analysis
  • List some analytics platforms/tools and their suitability to discover, predict or report


“Collaboration between academics and industry subject matter experts in the Life Sciences led to the design of this course, which introduces students to digital technology concepts in a biomanufacturing setting. In this course, we cover topics including the initial collection and storage of biomanufacturing process data and its subsequent analysis and transformation into valuable information that is actionable and used to make process and business decisions. The purpose of this course is to provide students with knowledge and experience, so that they are familiar with the various functions and tools related to data collection and data utilization, which they will encounter in a modern biomanufacturing facility.”

- Ryan Barton, Automation/Data Scientist at NCSU BTEC