Your roadmap · आपका रोडमैप
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Admission & first meetingप्रवेश और पहली मुलाकातEnquire at your nearest NDSS centre, meet the teacher, fix the batch time and get your study material.
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Part 1 of the syllabusपाठ्यक्रम भाग 1Unit-wise coaching with notes and doubt classes.
Unit 1: Introduction to Business AnalyticsUnit 2: Data Management & Descriptive AnalyticsUnit 3: Predictive Analytics
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Part 2 of the syllabusपाठ्यक्रम भाग 2Unit-wise coaching with notes and doubt classes.
Unit 4: Data Mining & Machine Learning BasicsUnit 5: Prescriptive Analytics
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Unit tests & assignmentsयूनिट टेस्टRegular tests in the university / board pattern.
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Semester 2 exam (university / board)विश्वविद्यालय / बोर्ड परीक्षाPrevious papers and full revision before the exam.
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Online tests & resultऑनलाइन टेस्ट और रिज़ल्टTake the tests online; your marks and result show in your student login and at the centre.
Syllabus · पाठ्यक्रम
1 subject · 5 chapters · 27 topics
01Unit 1: Introduction to Business Analytics
6 topics+
- Meaning, evolution and scope of business analytics
- Data, information and decision making
- Descriptive, predictive and prescriptive analytics
- Business intelligence vs business analytics
- Big data: volume, velocity, variety, veracity
- Applications in marketing, finance, HR and operations
02Unit 2: Data Management & Descriptive Analytics
5 topics+
- Types of data: structured and unstructured
- Data collection, cleaning and preparation
- Measures of central tendency and dispersion
- Data visualisation: charts, dashboards, pivot tables
- Introduction to Excel, Power BI / Tableau
03Unit 3: Predictive Analytics
5 topics+
- Correlation analysis
- Simple and multiple linear regression
- R-squared and interpretation of coefficients
- Time-series forecasting: moving average, exponential smoothing
- Logistic regression basics
04Unit 4: Data Mining & Machine Learning Basics
6 topics+
- Data mining process (CRISP-DM)
- Classification: decision tree, k-nearest neighbours
- Clustering: k-means
- Association rules: support, confidence, lift
- Model evaluation: confusion matrix, accuracy, precision, recall
- Overfitting and train-test split
05Unit 5: Prescriptive Analytics
5 topics+
- Optimisation and linear programming formulation
- Graphical solution and Excel Solver
- What-if analysis and scenario analysis
- Simulation basics (Monte Carlo)
- Ethics and privacy in analytics
About this course
You will be able to
- Explain descriptive, predictive and prescriptive analytics and their business uses
- Clean, summarise and visualise business data in Excel / a BI tool
- Build and interpret simple and multiple linear regression models
- Use basic classification and clustering ideas and read a confusion matrix
- Formulate and solve simple optimisation (linear programming) problems
- Present data-driven recommendations to managers
Who it is for
- MBA students of Semester 2 (AKTU) - Finance, Human Resource, Marketing specialisations
- Students who want analyst roles in marketing, finance or HR analytics
What you need
- Graduation in any discipline (MBA admission)
- Business statistics basics and working knowledge of MS Excel
Online tests & result
Practice and unit tests online; marks and result show in your student login and at the centre.
Student login →
Questions
Which syllabus is followed?
The AKTU (Dr. A.P.J. Abdul Kalam Technical University, Lucknow) MBA syllabus of Business Analytics (Semester 2). If your own university's syllabus differs, the centre follows your university syllabus and units.
Is coding compulsory?
No. The course is taught mainly in Excel with an introduction to Power BI; simple Python / R examples are shown where your university syllabus asks for them.
How will I be tested?
Unit-wise MCQ tests and a final paper at semester level, plus practice on short and long answer questions from previous university papers.
