Course Overview:
- Immerse yourself in the world of predictive analytics with this comprehensive course on Business Analytics. Gain valuable insights into leveraging historical data to forecast future demand and identify key drivers for improved outcomes.
- Drawing from foundational principles in Statistics and Business Intelligence, this course equips you with the essential skills for effective decision-making using predictive analytics. Explore the two prominent paths of Supervised learning and Unsupervised learning, enabling you to master the art of problem-solving and hypothesis testing.
- Discover the wide-ranging impact of predictive analytics across various domains. Witness its influence on marketing, where it empowers businesses to create customer engagement platforms that drive customer retention. Learn how predictive client models and understanding customer behaviour have propelled industry leaders to new heights. In the realm of Human Resources, uncover how predictive analytics can forecast the effects of people policies on employee well-being, happiness, and overall performance, leading to enhanced organizational stability. Additionally, explore how predictive analytics can optimize productivity and profitability across different departments, ultimately boosting the bottom line of organizations.
- Embark on this transformative course to develop a solid foundation in predictive analytics. Gain a comprehensive understanding of its key components and the tools used through the lens of statistical modeling. Equip yourself with the skills necessary to harness the power of predictive analytics and drive success in the dynamic business world.
Learning Outcomes:
- Understand the scope and limitations of multivariate predictive models in business context.
- Create predictive models using multivariate statistical techniques
- Use clustering methods in business context.
- Clearly communicate and present predictive analytics results in common business lingua that can be understood by a general non-technical audience.
Course Evaluations:
- Full Attendance: Attending all course sessions without any absences, regardless of the reason, constitutes full attendance. It reflects your commitment and dedication to actively participate in all aspects of the course. Full attendance is a valuable aspect of the learning experience as it allows you to grasp the course content comprehensively and engage in meaningful discussions with fellow students and instructors. In recognition of your commitment, 10% of the total course marks will be allocated to full attendance. Please note that any partial attendance or missed sessions, regardless of the reason, will not be eligible for the full attendance marks.
- Class-Assignments: This assignment will require you to work in supervised manner on a business problem which demands actionable insights using predictive analytics tools. The datasets will be supplied, or you will be guided to obtain a data set for these assignments. You shall analyse/synthesise data using appropriate modelling method. The completed analysis (outputs along with interpretation) shall be uploaded in Google drive for assessment within 24 hours of the session. The evaluation will be out of 100 marks divided in Problem Identification & Solutioning (30 marks), Completeness (40 Marks) and Quality (30 Marks).
Course Faculty :- Saurabh Agarwal
Course Duration : – 32 Hours
