NICF – Business Analytics with Machine Learning
Course Objectives
Machine Learning (ML) refers to the usage and development of computer systems that can adapt without any explicit instructions. This is achieved with algorithms and statistical models to analyse and draw inferences from patterns in business data. In Business Analytics, ML serves as a keydriving force for revenue enhancement. It uses data to identify patterns and trends in market and customer behaviour and enables businesses to understand the market better and create better products and services. This course is designed to transfer the knowledge and skillsets of business analytics and machine learning to learners.
Course Outcomes
- Learners will be able to extract and interpret data patterns to acquire business insights.
- Learners will be able to manage data science projects with CRISP-DM Framework.
- Learners will be able to perform supervised machine learning models to gain business insights.
- Learners will be able to perform unsupervised machine learning models to evaluate hypothesis.
- Learners will be able to communicate the findings and make recommendation to guide organizational decision.
Target Audience
- Fintech Industry & Banking Professionals
- ICT Professionals
- Database Administrators, Entrepreneurs
- IHL Students
Program Structure
Component 1:
Written Examination (MCQ)
40 Questions
1 Hour duration
Closed Book
Score 70% to pass
Component 2:
Project Work Component (PWC)
Individual work
2 weeks to complete from the last day of course
Score 70% to pass
These components are individual based. Participants will need to obtain 70% in both the components in order to qualify for this certification. If the participant fails in one of the components, they will not pass the course and have to re-take that particular failed component. If they fail both components, they will have to re-take the assessment.