Cognitive Class / Fireside Analytics Inc.

Digital Analytics & Regression

Running a 100 meter sprint in rain boots is like asking your competition to win on your behalf. Know the tools you need to have the competitive edge. Use this course as a case study to move you from problem to solution using the best suited tool set.

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About This Course

Follow a case study where you define the business objective, establish the data required to address that objective, and use R, the programming language, to derive insights from the data. As with any business challenge, you will be required to articulate your findings to a business audience.

  • Learn basic concepts in statistics with step-by-step guidance on how to conduct an analysis to solve the business problem.
  • Data Science is like triathlon. Programming is cycling, by far the biggest investment is required in hardware and software. Running is domain expertise and communication skills and, swimming is mathematics, statistics and modelling. There are competitions in each of these disciplines, cycling, running and swimming (and there always will be), but the need for super athletes who can do all 3 is growing. An athlete who is brilliant at one discipline can learn the other two and succeed in the triathlon.

Course Syllabus

  • Module 1 - A Case Study Approach to Analytics
    1. Understand the business context
    2. Formulate the business objective
    3. State the hypothesis
    4. Assess available data
    5. Assign data for use
  • Module 2 - RStudio IDE on CC Labs (formerly known as Data Scientist Workbench)
    1. Using CC Labs (Data Scientist Workbench)
    2. What is R?
    3. Loading data into R with Data Scientist Workbench
    4. Upload a CSV data file into Data Scientist Workbench and RStudio
  • Module 3 - Google Trends Data in R
    1. Access Google Trends data in R
  • Module 4 - Simple Linear Regression in R
    1. Regression and Google Trends Data in R
    2. Box Plots and Histograms in R
    3. Scatter Plots & Lines of best fit in R
    4. Simple Linear Regression in R
  • Module 5 - Presenting Data Analytics in Business
    1. Using data to answer a business question
    2. Summarizing the data analytics process
    3. Presenting data insights

General Information

  • This course is free.
  • It is self-paced.
  • It can be taken at any time.
  • It can be audited as many times as you wish.

Recommended skills prior to taking this course

  • Knowledge of basic statistics is an asset
  • Knowledge of basic R is an asset


  • None

Course Staff

Fireside Analytics Inc.

Shingai Manjengwa (@Tjido) is the CEO of  Fireside Analytics Inc., an ed-tech start-up that develops customized online and in-person courses to teach digital literacy, data science, data visualization, and coding to high school students, policymakers, senior executives, small business owners, and working professionals. Data Science courses by Fireside Analytics have over 300,000 registered learners on platforms like IBMs and Coursera.

An IBM Influencer and Author, Shingai has a Masters in Business Analytics from NYU Stern. Shingai is also the founder of Fireside Analytics Academy, a registered private high school (BSID: 886528) that teaches high school students to solve problems with data.

What is Data Science? Data Science is the process of ethically acquiring, engineering, analyzing, visualizing and ultimately monetizing data.

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