National Energy Board of Canada

Data Science with Open Data

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  • Course Number
    DS0110EN
  • Classes Start
    Any time, Self-paced
  • Estimated Effort
    3 hours
  • Audience
  • Course Level
  • Language
  • Learning Path
  • Badge Earned
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About This Course

The National Energy Board of Canada has established Data and Information Management as a focus area for the future. The objectives are to increase capacity in data analytics, experimentation culture and evidence-based decision making withing their organization but more broadly in the communities they serve.

One pillar of this strategy is to develop open data science training content, developed using open data. Success is predicated on all of us having a common understanding of data terminology, tools and techniques, so nothing is “lost in translation.” This course is open to public servants in Canada and to the general public.

Data experts are encouraged to participate, no programming or IT experience are required and, participants from non-technical backgrounds are encouraged to take this short course. Happy learning!


What will I get after passing this course?

  • You will receive a completion certificate.
  • You will receive the IBM Explorer - Big Data Foundations badge.

Course Syllabus

  • Lesson 1 - What is Data Science
    • Buzzwords and Definitions
    • What is Open Data?
  • Lesson 2 - Intro to R?
    • RStudio Cloud
    • Create an R Cloud Account
    • RScript Instructions
    • Lab - Create an RStudio Cloud Account
  • Lesson 3 - The National Energy Board of Canada (NEB)
    • What is the National Energy Board of Canada?
    • Case Study 1: Basic Charts with NEB Open Data
  • Lesson 4 - Intro to Data Analysis
    • The Funnel Approach
    • Measures of Central Tendency
    • Descriptive Statistics
    • Anomaly Detection
    • Lab Case Study 2
  • Lesson 5 - Data Visualization with Open Data
    • Data Visualization Theory
    • Case Study 2: Data Analysis with NEB Open Data

General Information

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

Recommended skills prior to taking this course

  • None

Grading scheme

  • The minimum passing mark for the course is 70%, where the review questions are worth 50% and the final exam is worth 50% of the course mark.
  • You have 1 attempt to take the exam with multiple attempts per question.

Requirements

  • None.

Course Staff

Shingai Manjengwa

Shingai Manjengwa

Shingai Manjengwa is the Chief Executive Officer of Fireside Analytics Inc., an ed-tech start-up that develops customized online educational 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 CognitiveClass.ai and Coursera. An IBM Influencer, author and NYU Stern alumni, 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. The ‘IDC4U – High School Data Science’ course is available directly to local and international students online.