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Last date of admission: 24th Sep
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Data Analysis 
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Semester 1
Financial Reporting & Statement Analysis
This subject provides a strong foundation in financial reporting and statement analysis, covering regulatory frameworks, the accounting cycle, accrual adjustments, cash flow preparation, asset and liability reporting, and key techniques for evaluating profitability, risk, and accounting quality.
Business Statistics
This subject introduces core business statistics concepts, including descriptive analysis, probability and uncertainty, key probability distributions, sampling methods, confidence intervals, hypothesis testing, and regression techniques for data-driven decision-making.
Managerial Economics
This subject covers demand analysis and forecasting, supply and cost concepts, pricing decisions in competitive and imperfect markets, and core macroeconomic topics such as consumption, investment, business cycles, and inflation.
Programming with R & Python
This subject helps to build foundational skills in R and Python for data analysis, visualization, and data manipulation using libraries like tidyverse, NumPy, and Pandas.
Database Management
This subject introduces core concepts of databases, covering data models, ER design, SQL querying, normalization, transaction processing, concurrency control, query optimization, and modern topics like data warehousing and big data systems.
Semester 2
Machine Learning Methods
This course introduces key machine learning concepts and techniques used in business analytics. Learners explore supervised and unsupervised learning, model evaluation, and practical applications for analysing data, identifying patterns, and supporting business decisions.
Data Visualization using Tableau and Power BI Management
This course introduces data visualization using Tableau and Power BI. Learners explore techniques to transform data into interactive dashboards and visual reports, enabling clear insights and informed business decisions.
Big Data Analytics
This course introduces the concepts and techniques used to manage and analyse large and complex datasets. Learners explore big data tools and methods to identify patterns, generate insights, and support data-driven business decisions.
Applied Multivariate Data Analysis
This course introduces techniques for analysing multiple variables simultaneously. Learners explore multivariate methods to identify relationships, patterns, and trends in complex datasets and apply these techniques to support data-driven business decisions.
Business Econometrics
This course introduces econometric methods for analysing business and economic data. Learners explore statistical techniques to understand relationships between variables, interpret trends, and use data-driven insights to support business and economic decisions.
Financial Management
This course covers the principles of financial management and their application in business decision-making. Learners explore financial planning, investment decisions, risk, and financial analysis to support effective management of business resources.
Skill Lab-I
This course provides hands-on exposure to essential skills used in business analytics. Learners apply analytical tools and techniques to practical tasks, helping them develop problem-solving and data-driven decision-making skills.
Semester 3
Time Series Analysis
This subject defines fundamental time series components, trend-fitting, smoothing algorithms in R, seasonal variations, rigorous statistical testing, correlograms, and essential forecasting models.
Deep Learning Principles and Applications
This subject offers deep learning in tensor algebra, performance via gradient descent, multi-layered networks, regularization, and convolutional models for image classification.
Project Management
This subject provides an end-to-end framework for managing projects, covering life cycle phases and feasibility, Work Breakdown Structures (WBS), network scheduling via PERT/CPM, risk and cost management, procurement, quality control, and formal project termination using PMIS tools.
Research Methodology
This subject offers a complete research framework covering hypothesis formulation, experimental design, sampling techniques, statistical analysis through univariate and bivariate methods, and the ethical standards of professional report writing and intellectual property.
Design and Analysis of Experiments
This course introduces the principles of planning, designing, and analysing experiments. Learners explore experimental methods to test relationships, evaluate outcomes, and draw reliable conclusions from data.
Skill Lab-II
This course provides practical experience in applying business analytics concepts and tools. Learners work on real-world analytical tasks to strengthen their technical, problem-solving, and data-driven decision-making skills.
Semester 4
Generative AI
This course introduces the concepts and applications of generative artificial intelligence. Learners explore how generative AI can create and analyse content, automate tasks, and support data-driven business processes and decision-making.
Choose any one elective group
Elective (Marketing): Marketing Analytics, Digital and Web Analytics
Elective (Finance): Financial Assets Valuation, Financial Analytics
Capstone Project
Capstone projects encourages learners to apply interdisciplinary knowledge, use relevant tools and frameworks, and build a portfolio-worthy project aligned with their career goals.
27+ years of experience
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