This Spreadsheet Modelling for Business course provides a
comprehensive overview and hands-on experience in utilizing Microsoft
Excel for effective business decision-making. The course provides a
competitive edge by fostering practical application, making it an
invaluable resource for professional development in today's data-driven
business landscape.
This Spreadsheet Modelling for Business course provides a
comprehensive overview and hands-on experience in utilizing Microsoft
Excel for effective business decision-making. The course provides a
competitive edge by fostering practical application, making it an
invaluable resource for professional development in today's data-driven
business landscape.
ENTREPRENEURIAL ESSENTIALS Syllabus Introduction *Course Overview* This course introduces students to the fundamentals of entrepreneurship, focusing on the skills and knowledge required to start and grow a successful business. Students will learn about entrepreneurial mindset, opportunity identification, business planning, and entrepreneurial finance. *Course Objectives* - Understand the entrepreneurial mindset and its importance in business - Identify and evaluate business opportunities - Develop a comprehensive business plan - Understand entrepreneurial finance and funding options - Learn about entrepreneurial marketing and sales strategies *Course Outline* 1. *Introduction to Entrepreneurship* - Definition and types of entrepreneurship - Entrepreneurial mindset and characteristics - Importance of entrepreneurship in economic development 2. *Opportunity Identification* - Identifying business opportunities - Evaluating market potential - Conducting feasibility studies 3. *Business Planning* - Business plan components - Business model canvas - Lean startup methodology 4. *Entrepreneurial Finance* - Funding options for startups - Financial planning and management - Valuation and investment strategies 5. *Marketing and Sales* - Entrepreneurial marketing strategies - Sales and customer acquisition - Building a sales funnel 6. *Growth and Scaling* - Growth strategies for startups - Scaling a business - Managing growth and challenges *Recommended Textbooks* - Entrepreneurship: Successfully Launching New Ventures by Bruce R. Barringer and R. Duane Ireland - The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses by Eric Ries
Management Training and Development Syllabus Introduction *Course Overview* This course explores the principles and practices of management training and development, focusing on designing, delivering, and evaluating training programs to enhance managerial skills and organizational performance. *Course Objectives* - Understand the importance of management training and development - Learn about training needs analysis and program design - Develop skills in training delivery and facilitation - Understand evaluation and measurement of training effectiveness - Learn about leadership development and succession planning *Course Outline* 1. *Introduction to Management Training and Development* - Importance of management training and development - Adult learning principles - Learning styles and training methods 2. *Training Needs Analysis* - Identifying training needs - Conducting needs assessments - Setting training objectives 3. *Training Program Design* - Designing training programs - Developing training materials - Selecting training methods and media 4. *Training Delivery and Facilitation* - Training delivery skills - Facilitation techniques - Managing group dynamics 5. *Evaluation and Measurement* - Kirkpatrick's Four-Level Evaluation Model - ROI analysis - Continuous improvement 6. *Leadership Development* - Leadership competencies - Leadership development programs - Succession planning 7. *Emerging Trends in Management Training and Development* - Digital learning and e-learning - Gamification and simulation - Coaching and mentoring *Recommended Textbooks* - Training and Development by Raymond A. Noe - Management Training and Development by M.W. Clements
*Supply Chain and Logistics Management Syllabus Introduction* *Course Overview* This course introduces students to the principles and practices of supply chain and logistics management, focusing on the planning, coordination, and execution of activities involved in the flow of goods, services, and information from raw materials to end customers. *Course Objectives* - Understand the strategic importance of supply chain and logistics management - Learn about supply chain design, planning, and execution - Analyze logistics and transportation management - Understand inventory management and warehousing strategies - Learn about supply chain risk management and sustainability *Course Outline* 1. *Introduction to Supply Chain Management* - Definition, scope, and importance of supply chain management - Supply chain strategies and trends 2. *Supply Chain Design and Planning* - Supply chain network design - Capacity planning and management - Demand forecasting and planning 3. *Logistics Management* - Logistics and transportation modes - Transportation management systems - Warehousing and inventory management 4. *Inventory Management* - Inventory types and management techniques - Inventory optimization models - Just-in-time (JIT) and lean inventory management 5. *Supply Chain Execution* - Procurement and sourcing strategies - Supply chain visibility and event management - Performance measurement and metrics 6. *Supply Chain Risk Management* - Types of supply chain risks - Risk assessment and mitigation strategies - Supply chain resilience and sustainability 7. *Emerging Trends in Supply Chain Management* - Digital supply chain and Industry 4.0 - Sustainability and circular supply chains - Future of supply chain management *Recommended Textbooks* - Supply Chain Management: Strategy, Planning, and Operation by Sunil Chopra and Peter Meindl - Logistics Management by Donald J. Bowersox and David J. Closs
Objective: To provide a basic knowledge about operations research and to acquaint the students some common operations research tools for various business decision marketing situations. Learning Outcomes:On completion of the course the students will be able to learn different OR techniques. III : Network Analysis: Meaning and Objectives – Network Techniques – Managerial applications of Network Techniques – PERT & CPM – Network diagram – activity – Event –Dummy Activity – Construction of Network diagram – Numbering of events – Activity & Event times – Float & Slack – Steps in the application of CPM – Critical activity – Finding of critical path & Estimated Duration – Time estimates in PERT – Steps involved in PERT calculations – Difference between PERT & CPM (only simple problems are expected – Crashing of activity timing not expected) 25 hours Module IV : Decision Theory: Decision making situations – Decision making under certainty -Decision making under uncertainty : Payoff, Regret (Opportunity loss), Maximax criterion –Minimax criterion, Laplace criterion &Huurwics alpha criterion – Decision making under risk : Expected Monetary Value (EMV) , Expected Opportunity Loss (EOL) , Expected Value of perfect information (EVPI) – Decision making under competition – Game Theory (Theory only) – Decision
FOUNDATOINS OF BUSINESS ANALYTICS Module 1: Introduction to Business Analytics & Probability Business Analytics Why Analytics Types of Business Analytics Random Experiment Sample Space and Events Probability Estimation using Relative Frequency Algebra of Events Fundamental Concepts of Probability Axioms of Probability Joint Probability Marginal Probability Independent Events Conditional Probability Applications of Simple ProbabilityBaye's Theorem Module 2: Theoretical Distributions Random Variables Probability Density Function (PDF) Cumulative Distribution Function (CDF) of a Continuous Random Variable Binomial Distribution Poisson Distribution Normal Distribution Chi-Square Distribution Student’s t Distribution F Distribution
Programme: BBA Course Title: Decision Science Course Type: Core Course Semester: I Academic Level : 2020–20 Credits: 4 Lecture per Week: 4 Pre-requisites No pre-requisites required Course Summary Various concepts of Operations Research Identification and development of business solutions Use of quantitative techniques helps students understand tools required to solve optimal problems in management Course Outcomes (CO) CO1: Develop an understanding of basic management science techniques and their role in managerial decision-making CO2: Help students formulate business situations into quantitative models for optimal decision-making CO3: Build capabilities in students for analyzing different business problems using management science and finding optimal solutions within constraints CO4: Enable students to apply techniques such as linear programming in managerial decision-making CO5: Apply techniques to business decision-making situations CO6: Develop mathematical models for real-life business and management problems Decision Science syllabus Module I – Introduction to Operations Research Meaning of Operations Research (OR) Scope of Operations Research Limitations of Operations Research Methodology of Operations Research OR Models Applications of Operations Research Importance of Ethics in Operations Research Linear Programming: Basic concepts Applications in management decision-making Mathematical formulation of Linear Programming Problems Graphical solution of Linear Programming Models Module II – Transportation and Assignment Problems Transportation Problem: Initial Basic Feasible Solution North West Corner Rule Vogel’s Approximation Method (VAM) Test for Optimality: Modified Distribution (MODI) Method Assignment Problem: Introduction Solution methods Hungarian Method Maximization in Assignment Problems Unbalanced Assignment Problems Travelling Salesman Problem
FOUNDATOINS OF BUSINESS ANALYTICS Module 1: Introduction to Business Analytics & Probability Business Analytics Why Analytics Types of Business Analytics Random Experiment Sample Space and Events Probability Estimation using Relative Frequency Algebra of Events Fundamental Concepts of Probability Axioms of Probability Joint Probability Marginal Probability Independent Events Conditional Probability Applications of Simple ProbabilityBaye's Theorem Module 2: Theoretical Distributions Random Variables Probability Density Function (PDF) Cumulative Distribution Function (CDF) of a Continuous Random Variable Binomial Distribution Poisson Distribution Normal Distribution Chi-Square Distribution Student’s t Distribution F Distribution
FOUNDATOINS OF BUSINESS ANALYTICS Module 1: Introduction to Business Analytics & Probability Business Analytics Why Analytics Types of Business Analytics Random Experiment Sample Space and Events Probability Estimation using Relative Frequency Algebra of Events Fundamental Concepts of Probability Axioms of Probability Joint Probability Marginal Probability Independent Events Conditional Probability Applications of Simple ProbabilityBaye's Theorem Module 2: Theoretical Distributions Random Variables Probability Density Function (PDF) Cumulative Distribution Function (CDF) of a Continuous Random Variable Binomial Distribution Poisson Distribution Normal Distribution Chi-Square Distribution Student’s t Distribution F Distribution
SUBJECT DETAILS Programme: BCA Course Code: BCA2CJ103 / BCA2MN102 Course Title: Numerical Analysis and Operations Research Type of Course: Major / Minor (B2) Semester: II Academic Level: 100–199 Credits: 4 Lecture Hours: 4 per week PRE-REQUISITES Understanding of algebraic concepts, equations, and inequalities Basic knowledge of derivatives and integrals COURSE SUMMARY Covers numerical methods and operations research Focus on error analysis and solution techniques Includes algebraic and transcendental equations Topics include interpolation, numerical integration Introduces linear programming and OR principles COURSE OUTCOMES CO1: Solve algebraic and transcendental equations using numerical methods CO2: Apply interpolation and numerical integration techniques CO3: Understand fundamentals of Operations Research CO4: Solve Linear Programming Problems using optimization techniques CO5: Understand and solve transportation problems CO6: Solve assignment problems for optimal solutions MODULE I – NUMERICAL ANALYSIS I Errors in numerical calculations Sources of errors Solution of algebraic and transcendental equations Bisection method Method of false position Newton–Raphson method MODULE II – NUMERICAL ANALYSIS II Polynomial interpolationLagrange interpolation Newton’s forward difference interpolation Newton’s backward difference interpolation Numerical solution of definite integrals Simpson’s 1/3 rule Simpson’s 3/8 rule Trapezoidal method MODULE III – OPERATIONS RESEARCH I Introduction to Operations Research Definition, advantages, and limitations of OR Linear Programming Problem (LPP) Formulation of LPP Feasible solution and optimal Solution Dual of LPP Graphical solution of LPP Simplex method Big-M method MODULE IV – OPERATIONS RESEARCH II Transportation problem Balanced and unbalanced transportation problems Finding basic feasible solutions Northwest corner method Least cost method Vogel’s approximation method Optimized (MODI) method Assignment model Balanced and unbalanced assignment problems Hungarian method for optimal solution MODULE V – OPEN ENDED MODULE (OTHER NUMERICAL METHODS) Any two additional methods to solve algebraic and transcendental equations Any two additional methods for polynomial interpolation Any two additional methods to solve definite integrals Any one additional method to solve LPP
This course is designed to help commerce students enhance their English communication skills, particularly focusing on professional oral and written communication, critical reading, presentation skills, and discipline-specific communication strategies. earning Outcomes (COs) After completing the course, you should be able to: Interpret and critically evaluate complex texts (literary, technical, academic). Enhance practical English language skills in personal, social, and professional contexts. Formulate perspectives and articulate ideas clearly in speech and writing. Deliver effective presentations and participate confidently in discussions/debates using rhetorical and communication tools. Develop collaborative communication skills, including teamwork, active listening, and clear expression. Utilise digital tools for research, collaboration, and multimedia presentation
