Essentials of Cloud Computing - Winter 2024

DAT 304
Closed
McMaster University Continuing Education
Hamilton, Ontario, Canada
Instructor
(14)
6
Timeline
  • January 15, 2024
    Experience start
  • January 20, 2024
    Project Scope Meeting
  • March 12, 2024
    Midway Check-in
  • April 8, 2024
    Final Presentation
  • April 9, 2024
    Experience end
Experience
3 projects wanted
Dates set by experience
Preferred companies
Anywhere
Any company type
Any industries
Categories
Information technology Cloud technologies
Skills
cloud computing adult education encryption cloud technologies authentications information privacy data visualization computer science data analysis authorization (computing)
Student goals and capabilities

This course is part of the Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc.

Students will explore the principles and practices of cloud computing with this introductory course, and discover the importance of cloud computing for today’s business and IT sectors through an examination of the development of cloud technologies over time. 


Common practices for delivery, deployment, architecture and security will be presented.

Students will explore various cloud computing platforms to understand and assess 

current service options and to discuss future developments for cloud computing


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The project provides an opportunity for businesses and learners to collaborate to identify and translate a real business problem into an analytics problem. 

The projects, which can be short, will allow the student to apply the skills acquired on to address the business problem.  Some examples are:

  • Determine the characteristics of the collection system and select a collection system that handles the large data set
  • Identify the right storage solution for analytics
  • Design and implement a solution for transforming and preparing data for analysis
  • Select the right data analysis and data visualization solution for a given scenario
  • Apply the right authentication and authorization mechanisms
  • Apply data protection and encryption techniques
  • Manage and monitor data solutions

You should submit a high-level proposal/business problem statement including relevant data sets and definitions, a list of acceptable tools (if applicable), and expected deliverables. Business datasets could be provided based on a non-disclosure agreement or in an anonymized/synthetic data format that is relevant to your organization and business problem. The course instructors will review the documents to confirm the scope and timing of the proposed problem and its alignment with the course requirements.



Students
Certificate
Any level
20 students
Project
40 hours per student
Students self-assign
Teams of 4
Expected outcomes and deliverables
  • A report on students’ findings and details of the problem presented
  • Future collaboration ideas will be identified based on current project outcomes
Project timeline
  • January 15, 2024
    Experience start
  • January 20, 2024
    Project Scope Meeting
  • March 12, 2024
    Midway Check-in
  • April 8, 2024
    Final Presentation
  • April 9, 2024
    Experience end
Project Examples

Analytics solution may be applicable for (however they are not limited to) the following topics:

  1. Demand for social services (healthcare, emergency services, infrastructure, etc.)
  2. Customer acquisition and retention
  3. Merchandising for trade areas (categories)
  4. Quantifying Customer Lifetime Value
  5. Determining media consumption (mass vs digital)
  6. Cross-sell and upsell opportunities
  7. Develop high propensity target markets
  8. Customer segmentation (behavioral or transactional)
  9. New Product/Product line development
  10. Market Basket Analysis to understand which items are often purchased together
  11. Ranking markets by potential revenue
  12. Consumer personification

To ensure students’ learning objectives are achieved, we recommend that the datasets are at least 20,000+ rows in size. If more than one database is provided, which must be conjoined, students will be required to integrate them. This supports the learning experience and minimizes partner data preparation.