Data Programming I

DAT 302
Closed
McMaster University Continuing Education
Hamilton, Ontario, Canada
Instructor
(13)
6
Timeline
  • September 17, 2024
    Experience start
  • September 20, 2024
    Project Scope Meeting (TBD)
  • October 26, 2024
    Midway Check-in (TBD)
  • December 10, 2024
    Final Presentation (TBD)
  • December 14, 2024
    Experience end
Experience
3 projects wanted
Dates set by experience
Preferred companies
Anywhere
Any company type
Any industries
Categories
Data visualization Data analysis Data modelling Data science
Skills
nosql apache hbase presentations adult education apache kafka apache spark java (programming language) scala (programming language) application programming interface (api) computer science
Learner goals and capabilities

This course is part of the Big Data Programming and Analytics certificate program.

Students in the program are adult learners with a post-secondary degree/diploma in

computer science, engineering, business, etc.


This course examines developing solutions for extracting and analyzing big data sets

using various technologies. Students will learn Scala and Java, which are the

fundamental part of Spark, Kafka, and HBase. The focus will be on Apache Spark and

its different aspects. Students will explore real-time analytics tools such as Kafka and

HBase. NoSQL will be covered in this course.


Course activities will include instructor presentations, required readings and experiential

learning activities (i.e. case studies, group discussions, projects, etc.).

Learners
Continuing Education
Beginner, Intermediate, Advanced levels
20 learners
Project
40 hours per learner
Learners self-assign
Teams of 2
Expected outcomes and deliverables

The final project deliverables will include:

 A report on students’ findings and details of the problem presented

 Future collaboration ideas will be identified based on current project outcomes

Project timeline
  • September 17, 2024
    Experience start
  • September 20, 2024
    Project Scope Meeting (TBD)
  • October 26, 2024
    Midway Check-in (TBD)
  • December 10, 2024
    Final Presentation (TBD)
  • December 14, 2024
    Experience end
Project Examples

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

the various tools to address the business problem. Students also learn how to

implement real-time scenarios.

Some examples of potential projects:

 Development of search and analytics solutions

 Development of highly scalable and cost-efficient applications with MongoDB

 Building MongoDB data models for enterprise applications

 Deploy and management of Elasticsearch clusters

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

capstone course requirements.

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.)


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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. Data need to be ‘clean’. 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.

Companies must answer the following questions to submit a match request to this experience:

Be available for a quick phone call with the organizer to initiate your relationship and confirm your scope is an appropriate fit for the experience. Advise the instructor if students will be required to sign an NDA prior to beginning the project.

What's your dataset size? Please note that ideally the datasets should be at least 20,000+ rows in size.

Share feedback and recommendations about the project deliverables with the students and instructor.

Provide a dedicated contact who will be available to answer periodic emails or phone calls over the duration of the project to address student’s questions or provide additional information. Minimum of 2-4 interactions with each student group leader (approximately 4-6 hours over the duration of the project). Let the students/instructor know if you will be away for an extended time (e.g., vacation).