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Short Course
on
Distributed Computing for Data Scientists
The financial and other industries currently have a shortage of people with the necessary data science skills to address problems relating to large and/or complex data sets. Nowadays financial institutions are confronted with an abundance of data, and so in order to maintain a competitive advantage it is imperative to have analysts with these necessary data science skills. This short course will address one of the topics needed to become a skilful data scientist.

Purpose of the course:

This short course aims to equip participants with the skills necessary to understand the fundamentals of distributed computing including security risk management in order to be able to analyse different commercial products and access data stored in commercial distributed databases.

Admission requirements:

Admission requirements: 
NQF level 7 majoring in either Mathematics/Statistics/Engineering/Computer Science
Learning assumed to be in place: 
NQF level 7

Course outcomes and assessment criteria :

Course outcomes and the associated assessment criteria: 

Study Unit

Outcomes

Assessment Criteria

  After completion of this course, participants will: Participant will be assessed on the following criteria:
 
  1. Demonstrate applied knowledge and understanding of the nature and architecture of distributed computing and understand how it is applied in practice.
  2. Demonstrate an ability to identify real-world practical problems that can be solved using analysis of data stored in distributed databases and then apply data query methods to solve these problems.
  3. Demonstrate an ability to use a range of data base analysis skills to identify, analyse and address complex problems
  1. Critically discuss the characteristics of distributed computing
  2. Explain the characteristics of commercial products implementing distributed computing
  3. Use tools to query and report on data stored in a distributed database
  4. Implement a solution to a business problem using data stored in a distributed database

 

Assessment: 
Assignments and participation
Method of assessment: 
Learning objectives will be accomplished through the successful completion of assignments and participation in short course activities, proving insight into the topics at hand.

Additional information

Mode of delivery: 
Mixed
Target group: 
Graduates and/or industry professionals working in fields that require data science and analytical skills.
Contact us
Name: 
Prof Roelien Goede
Telephone number: 
018 285 2670