Business Analyst
Overview
The Business Analytics specialization aims to empower students with the analytical expertise and data-driven decision-making skills required to solve complex business challenges. This program provides a strong foundation in statistical analysis, predictive modelling. Artificial Intelligence and machine learning, and the use of advanced analytical tools and technologies. This student can extract actionable insights from data, optimize business processes, and support strategic initiatives across various functional areas.
Program Outcomes
- Build predictive models and AI-powered decision systems.
- Extract actionable insights from structured and unstructured data.
- Use analytics to improve marketing, HR, finance, and operations.
- Work with tools like Python, R, Power BI, and Tableau.
- Solve complex business problems with data science methods.
Program Objectives
- Introduce core concepts of statistics, AI, and machine learning.
- Train students in tools for data visualization and storytelling.
- Teach ethical and legal aspects of data use.
- Develop cross-functional analytical skills.
- Prepare students for data-driven leadership roles.
Business Analyst
Data Science
Quantitative Analyst
Predictive Modeller
Data Visualization
BA Consultant
Admission Process
Step - 01
Application
Apply online by visiting www.iiamvizag.com or Application for Admission can be obtained from the office of lIAM.
Step - 02
Registration
Registration of Application enclosing qualifying examination certificates and scorecard
Step - 03
Evaluation
Apply online by visiting www.iiamvizag.com or Application for Admission can be obtained from the office of lIAM.
Step - 04
Short Listing
Qualified candidates will be shortlisted for Admission
Step - 05
Admission Confirmation
Candidates who are offered admission will have to pay the processing fee as stipulated
with in 7 days from the date of offer
Basic coding in Python/R is taught from scratch, no prior experience needed.
Tech, healthcare, finance, e-commerce, logistics, and more.
Excel, SQL, Python, R, Tableau, Power BI, and machine learning libraries.
Yes, with capstone projects and case studies aligned to industry needs.
Absolutely—this course is designed for both technical and non-technical students.