IT AND ANALYTICS FOR BUSINESS LEADERS

Syllabus

IT and Analytics for Business Leaders

Course Code: MBA 2.1

Module 1: Introduction to Information Systems in Business (10 Hours)

Information Systems in Business - Definition and types of Information Systems (TPS, MIS, DSS, EIS), Enterprise Resource Planning (ERP), Customer Relationship Management (CRM)- Functions and benefits, Emerging Trends in Computing – Artificial Intelligence (AI), Internet of Things (IoT), Quantum Computing, Cybersecurity, Edge Computing, Augmented Reality (AR) and Virtual Reality (VR), Blockchain, Cloud Computing, Strategic IT Management, IT Governance.

Module 2: Data Analytics in Business (10 Hours)

Data Analytics in Business: Overview of data analytics and its value for strategic decision-making, Types of Data: Structured vs. Unstructured Data: Quantitative vs. Qualitative Data: Types of Data Analytics: Descriptive Analytics, Diagnostic Analytics Predictive Analytics. Prescriptive Analytics. Data Collection, Data Warehousing, Data Mining & Big Data Concepts, Cleansing, Transformation. Basic Data Modelling Concepts, Business Intelligence (BI) Tools and Data Visualization Techniques, Applications of Business Analytics.

Module 3: AI, ML & IoT In Business (12 Hours)

Artificial Intelligence (AI): Basics of Artificial Intelligence (AI)- Definition of AI, Types of AI, Narrow AI vs. General AI. Applications of AI in Business, Benefits of AI in Management, Ethical Implications and Regulatory Challenges in AI, Robotics and Process Automation in Business Operations,

Machine Learning: Basics of Machine Learning (ML)- Definition of Machine Learning, How ML differs from traditional programming. Key Concepts - Supervised, unsupervised, and reinforcement learning, Applications of ML in Business,

Internet of Things (IoT)- Definition and Concept of IoT, Components of an IoT System, Applications of IoT in Business, Impact on Business Operations.

Module 4: Digital Innovations in Finance, HR, Marketing, and Logistics (12 Hours)

Introduction to Digital Innovations, Definition and Overview: Understanding digital innovations and their impact on various sectors,

Fintech- Introduction, Definition and evolution of FinTech, Overview of the global Fin-Tech ecosystem, Impact on Traditional Financial Services, Key drivers of FinTech growth. Key Fintech Technologies: Blockchain, Cryptocurrency - Understanding Initial Coin Offerings (ICOs) and Central Bank Digital Currencies (CBDCs) and Smart Contracts, EFT - Mobile Payments, Digital Wallets, and Banking-as-a-Service (BaaS), Regulatory challenges and future trends in FinTech.

Human Resources (HR): AI in Recruitment, HR Platforms, Data-Driven Decisions in HR, Virtual Reality and Augmented Reality in Employee Experience.

Marketing: Digital Marketing, AI & Big Data, Mobile, Social Media Marketing tools, Future Digital Marketing Trends.

Logistics, IoT & AI in Logistics, Blockchain for Supply Chain, Smart Logistics, Future Logistics Trends.

Module 5: Introduction to Advanced Excel & MS Access (12 Hours)

Getting started with Excel, working with Formulas (SUM, SUMIF, IF, LOOKUP, etc) & Functions and creating Charts & Graphs. Statistical tools – use statistical functions such as average, Standard Deviation, ANOVA, IF function etc.Data analysis by using What IF, PIVOT table, Scenarios, Goal seek. Excel Tools for Data Cleaning- Remove Duplicates, Filters, and Text-to-Columns.

MS-ACCESS: Creating a database and tables by different methods- Entering and Editing data Sorting, Filtering and Displaying data, Creating & querying using forms. Creating & printing reports and labels.

Building a Simple Regression Model Using Python on Google Colab