Data Science & Analytics including Operations / Decision Science are evolving fields which are in demand currently for various reasons. Most companies are experimenting and creating projects / products around analytics / data science. I am listing the subjects & courses that an MBA student should take to cover Data Science / Analytics:
- Mathematics — Intermediate level statistics, linear algebra, discreet mathematics & basic calculus
- Introduction to Business Analytics & Data Science — covering basics of the subjects like what is machine learning, artificial intelligence, major software / products, data science / analytics basics including various types of data, sentiment analysis, basics of algorithms and contemporary topics
- BigData ecosystem — Concepts of Hadoop, Spark, MapReduce, NoSQL and the ecosystem around it
- Business Intelligence — covering reporting, dash-boarding, visualization and contemporary topics around it
- Business Analysis — covering concepts of how to collect requirements, build a project plan / statement of work, proposals, proof of concepts, concepts of AGILE / DevOps, data analysis, business process re-engineering and similar
- Programming in R & Python for managers — Intermediate level topics including data manipulation / cleaning, charting / visualization, running major machine learning algorithms, mathematics functions and libraries
- Data warehousing — covering the introduction of it and multi-dimensional cubes, business dimensions, star / snowflake schema, process of ETL and similar
- Data mining — covering major algorithms in supervised / unsupervised / semi-supervised areas and their implementation
- Cloud computing — covering cloud architecture, offerings & major product companies
- Operations subjects — which should include Operations management, Operations research, Project Management, Logistics & Supply Chain management, Total Quality Management
- Case study, use case and industry driven internships and projects which give exposure to students using proprietary / open source tools & products mapped to domains like Digital marketing, Financial analytics, HR analytics, Web / Mobile analytics, Advertising, Operational Analytics, eCommerce, Manufacturing, Banking, etc. used in industry to join all of the above together into implementation
- Above goes with an assumption that students already have intermediate level skills in productivity tools like MS-Office / Google Docs/Sheets, Linux, Year 1 general management subjects like Finance, HR, Marketing, etc.
Reach out to me at neil@TechAndTrain.com if you want to discuss Data Science / R / Java / Python / etc. or want to conduct a training for MBA / BE / MCA / MSc students or are interested in having a workshop for on Data Science / R / Java / AWS / Excel / etc.
