Practical Time Series Analysis and Forecasting for Business
The financial industry currently has 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 skillful data scientist.
This short course aims to equip participants with the skills necessary to comprehend time series forecasting principles applicable to business problems where time series data is prevalent.
NQF level 7 majoring in either Mathematics/Statistics/Engineering/Computer Science.
Learning assumed to be in place:
NQF level 7.
Course outcomes and the associated assessment criteria:
|After completion of this course, participants will:||Participant will be assessed on the following criteria:|
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.
Mode of delivery:
Graduates and/or industry professionals working in fields that require data science and analytical skills.