UNIQUE SERIES AKTU Syllabus
BMBA106

Introduction to Business Analytics & Data Science

L-T-P4-0-0 Credits3 Session2024-25 TypeTheory
Appears in 1 semester

MBA Business Analytics · Sem 1 (Core)

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Syllabus

5 units · 40 lecture hours
Unit1

Unit 1

8 hrs

Introduction: What is business analytics? Historical Overview of data analysis, Data Scientist vs. Data Engineer vs. Business Analyst, Career in Business Analytics, what is data science, Why Data Science, Applications for data science, Data Scientists Roles and Responsibility

Unit2

Unit 2

8 hrs

Data: Data Collection, Data Management, Big Data Management, Organization/sources of data, Types of Data, Importance of data quality, Dealing with missing or incomplete data, Data Visualization, Data Classification Data Science Project Life Cycle: Business Requirement, Data Acquisition, Data Preparation, Hypothesis and Modeling, Evaluation and Interpretation, Deployment, Operations, Optimization.

Unit3

Unit 3

8 hrs

Introduction to Data Mining, The origins of Data Mining, Data Mining Tasks, OLAP and Multidimensional data analysis, Basic concept of Association Analysis and Cluster Analysis.

Unit4

Unit 4

8 hrs

Introduction to Machine Learning: History and Evolution, AI Evolution, Statistics V/S Data Mining V/S Data Analytics V/S, Data Science, Supervised Learning, Unsupervised Learning, Reinforcement Learning, Frameworks for building Machine Learning Systems.

Unit5

Unit 5

8 hrs

Application of Business Analysis: Retail Analytics, Marketing Analytics, Financial Analytics, Healthcare Analytics, Supply Chain Analytics.

Course Objectives5 points
  • Understanding the Role of Business Analyst and Data Science in business.
  • Understanding the basic concept of data management and data mining techniques
  • To understand the basic concept of machine learning
  • To understand the application of business analysis.
  • Understanding the basic concept of Data Science Project Life Cycle.
Course Outcomes (COs)5 outcomes

After completion of the course student will be able to:

  1. CO1Understand the basics of business analysis and Data ScienceK2 (Knowledge)
  2. CO2Understand data management and handling and Data Science Project Life CycleK3 (Comprehending)
  3. CO3Understand the data mining concept and its TechniquesK4 (Applying)
  4. CO4Understand and Analyzing machine learning conceptK5 (Analyzing)
  5. CO5Understand the application of business analysis in different domainK4 (Applying)

Suggested Readings

  1. Essentials of Business Analytics: An Introduction to the methodology and its application, Bhimasankaram Pochiraju, Sridhar Seshadri, Springer
  2. Introduction to Machine Learning with Python: A Guide for Data Scientists 1st Edition, by Andreas C. Müller, Sarah Guido, O’Reilly
  3. Introduction to Data Science, Laura Igual Santi Seguí, Springer
  4. Introduction to Data Mining, Pang-Ning Tan, Michael Steinbach, Vipin Kumar, Pearson Education India
  5. An Introduction to Business Analytics, Ger Koole, Lulu.com, 2019

Official AKTU syllabus

This subject is on page 14, 15 of the original AKTU PDF.

Official AKTU syllabus PDF ↗