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Predictive Analytics Executive Programme

Overview

The SBS Predictive Analytics Executive Programme is designed to equip participants with practical tools and skills to apply in data analysis in order to derive logical conclusions about current and future business trends to support informed decision-making by business leaders.

The programme will provide insights and tools to the participants to enable them to continuously and consistently leverage their data (financial, customer demand, credit scoring, sales, HR, web interactions) to better understand their customers and the business environment to remain and operate with a competitive edge.

Programme Objectives

Specifically, the programme will enable the participants:

  • Critically evaluate time series data and information, and apply the knowledge in building simple and robust models and conduct simulations in order to generate sensible forecasts about future trends and developments
  • Understand the art and science of predictive analytics to define clear actions that result in improved decisions and business results
  • Develop actionable plans from existing institutional data and initiatives to increase sales, reduce marketing costs, and improve customer retention
  • Define appropriate business goals for a predictive analytics implementation
  • Optimize product development, testing, and maintenance.
  • Understand the use and assist in the selection of industry standard analytics tools
  • Integrate powerful and traditionally untapped sources of information including social data, unstructured text and Big Data sets
  • Understand how to use predictive analytics tools to analyze real-life business problems

Target Audience

The programme targets middle-level to senior analysts from key financial sector and regulatory institutions.

Programme Benefits/ROI

The curriculum for the Predictive Analytics Programme will combine business and data science, offering new opportunities for competitive advantage that unlocks the predictive potential of data analysis to improve financial performance, strategic management and operational effciency.

Programme Faculty

The programme faculty will comprise of course leaders who will be responsible for the design and delivery of the respective module; an associate course leader to bring specific industry or international perspectives; topic specialist as facilitators; and guest speakers drawn from industry. All these will complement each other to ensure that the learning outcomes are realized.

Programme Content

Module 1: Strategic and Macroeconomic Overview


  • This module seeks to enhance the participant’s understanding of strategy and macroeconomic scenarios both local and global and the its influence on decision making.

Module 2: Data analysis and Econometric Modelling


  • This module will empower participants to utilize statistical and econometric methods to conduct research, analyse data and present it with a view to informing evidence-base policy decisions in areas relevant to their departmental or organizational mandates.

Module 3: Time Series Analysis


  • This module will enable participants to utilize statistical and econometric methods to conduct research, analyse data and present it with a view to informing evidence-base decisions in areas relevant to their departmental or organizational mandates.

Leadership, coaching and mentoring


  • This course is designed to equip participants with leadership competencies that will enable them to better manage themselves, others and teams, and lead to measurable improvements performance and effectiveness in their workplace.
  • Participants will be expected to carry out a personal leadership challenges to support them in this process they will be assigned coaches who will coach them as they implement the projects they choose.

Contacts

For more information on the programme, contact Daniel Ochieng on eeopenprograms@strathmore.edu or dochieng@strathmore.edu or call +254 703 034 414/6/7.



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Key Details

Module I: 3rd – 7th September 2018

Module II: 15th – 19th October 2018

Module III: 26th – 30th November 2018

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