NMIMS MBA X – Business Analytics – For Executives

– Identify and demonstrate best practices of verbal, non-verbal and written communication in the professional environment

– Formulate, implement and assess a personal brand strategy

-Understand the key concepts of micro and macroeconomics

– Analyze the impact of various economic factors on elements of the business strategy

– Understand the game theory and identify optimum strategies in various business situations.

– Develop a marketing strategy for a product/service

– Identify the most appropriate channel mix for a marketing plan

– Evaluate a marketing campaign on summary metrics

– Get an overview of the key IT tools (traditional and emerging)

– Get an overview of the key tools in MS Excel

– Perform basic pivoting and formatting to represent data in MS Excel

– Use basic data visualization techniques to derive better insights from a dataset

– Use hypothesis testing to add statistical rigor to your business decisions

– Study associations between business variables to determine their relationship

– Apply basic syntax and operations in Python

– Clean and manipulate the data using Python’s powerful data analysis libraries

– NumPy and Pandas – Create basic visualizations using Python

– Create visualizations using Tableau and utilize storytelling principles for presenting insights in impactful ways

Apply frameworks to understand business problems and formulate a hypothesis

– Identify the different steps of a Data Science project utilizing the Crisp DM framework

– Understand individual behavior in the context of teams, groups, and organizations

– Understand key HR strategies for the 3 phases of an employee – recruitment, development, and assessment

– Formulate an effective resource management strategy to create a high-performance team

– Understand the basics of accounting and financial ratios

– Analyze accounting statements and financial ratios to identify the key action areas for a business

– Understand the key operations and SCM strategies available to a business

– Optimise decisions w.r.t plant planning, layout, production and operations management

– Formulate an optimum operations, procurement, inventory, and logistics strategy

– Understand project financing, project risk, and risk management strategies

– Evaluate a project on its financial viability

– Effectively manage working capital to ensure the financial health of project

– Understand the key frameworks for business, competition and industry analysis

– Apply the strategy models to varying business situations

– Formulate a plan for business growth, expansion (market entry/acquisition)

– Acquire data, identify different features, clean it and perform Exploratory Data Analytics on Python/ Excel –

– At the end of this course, students will be able to apply a set of techniques to display data in such a way that interesting features will become apparent, helping solve business problems

– Perform basic and intermediate operations in SQL to query and manipulate data

– Identify the important components of the Big Data ecosystem so that students can understand its capabilities and collaborate with big data engineers

– Identify the strategic advantage of deploying big data systems, identify the roadmap for setting up Big Data Systems for the same

– Identify the different problems where linear and logistic regression can be applied

– Write Python code for the algorithms to apply these and create models

– Evaluate the model

– Apply basic model selection principles

– Understand the basics of decision trees

– Identify the different problems where decision trees, other advanced ensembles, and supervised learning models can be applied

– Identify the different problems where time series forecasting, clustering, PCA, NLP, and deep learning can be applied

– Understand the concept of time series – Create time series models on excel

– Apply K-Means clustering on excel – Introduction to PCA

– Identify the different applications of data science in marketing

– Identify the different applications of data science in finance

– Identify the different applications of data science in operations and supply chain

– Identify the different applications of data science in human resource management

– Showcase the skills learned in the program through a 3-month long industry project. Get guidance and feedback on your project from a seasoned industry expert.