Advanced Certificate Programme In Business and Data Analytics (Batch 02)

Programme Objectives:

Upon completing the IIM Indore Advanced Certificate Programme in Business and Data Analytics, participants will achieve the following program objectives:

1. Master Analytical Tools: Acquire proficiency in utilizing advanced mathematical and statistical techniques, programming languages like Python, R and Tableau, and optimization methods to extract insights from complex data sets.
2. Informed Decision-Making: Develop the ability to make informed business decisions by interpreting and analyzing data through regression analysis, time series decomposition, outlier detection, and hypothesis testing.
3. Effective Data Visualization: Learn to create impactful data visualizations using tools like Power BI and Tableau, enabling effective communication of complex information to both technical and non-technical stakeholders.
4. Strategic Business Insight: Cultivate a deep understanding of business analytics’ life cycle, honing the skills needed to handle real-world business challenges in areas such as finance, HR, sales, and operations.
5. Data Management Expertise: Gain proficiency in designing and managing relational databases, applying normalization techniques, and utilizing SQL for data manipulation and querying.
6. Holistic Problem-Solving: Develop a holistic perspective on operations management, applying decision science principles to optimize processes, manage inventory, and enhance supply chain strategies.

Programme USP:

• Global industry aligned curriculum mapped with Business Analytics programmes from across the world
• Practical application oriented, integrates multiple business use cases, case studies and projects,

Programme Contents:

Participant will choose a few of the following contents.

Core

• Applied Mathematics and Statistics: Vector and matrix algebra, decomposition, linear algebra, gradient descent and optimization techniques, computations and vector spaces, probability theory and descriptive statistics, probability models and sampling techniques, estimations, testing of hypothesis, regression analysis, percentiles, box plots, and outlier analysis, time series decomposition
• Programming for Business Analytics: Recap of Language Fundamentals, Algorithmic Thinking, Variables and Operators in Python/ R, Data Visualization, Getting Data: APIs, Web scraping, File Handling Operations in Python/ R, Data Analysis, Python/ R Toolbox, Applications of Python/ R, Python and R Advanced Techniques, Python and R Libraries for Data Visualization, Optimization Techniques in Python/ R

• Global industry aligned curriculum mapped with Business Analytics programmes from across the world
• Practical application oriented, integrates multiple business use cases, case studies and projects,

Electives (Any 2)

• Fundamentals of Business and Data Analytics: Introduction to Business Analytics, Practical Techniques in Business Analytics, Life cycle of Business Analytics, Data Management, Case Study – Financial Analytics, Case Study – HR Analytics, Case Study – Sales Analytics, Agile for Business Analytics, Task Planning and Coordination, Requirement Basics, Requirement Elicitation, Analysis, Project Review, Game Theory for Business Analytics
• Business Data Management: Database Concepts and Architecture, Normalization Techniques in Database, Data Modelling, Introduction to Relational Databases, Structured Query Language, Structured Query language (part II), Structured Query Language (advanced), Business Intelligence Systems, Data Models, Database Design Considerations, Data Pipeline: Stages
• Data Visualization And Business Intelligence: Visualization – Methodology and Experience, Data Storytelling and Visualization, Introduction to Power BI, Working with Charts in Power BI, DAX calculations in Power BI, Building Dashboard with Power BI, Introduction to Tableau, Charts, Time Series and Aggregation, Building Dashboard with Tableau
• Decision Science for Operations Management: Introduction to Operations Management: Stockout, service levels management, Process Analysis: Flow rate/ throughput, Flow time, inventory, Little’s Law, Multiple types of flows, Queuing Theory: Introduction, single-server queues, multi-server queues, case study, Inventory Management I: Introduction, EOQ Model, EOQ Model with random demand, Inventory Management II: Newsvendor model, base stock policy, inventory pooling, case studies, Risk-based Production Strategy in supply chain: framework, use cases, case studies, Supply chain management: Strategies and incentive alignment
• Data Mining and Warehousing: Data Warehousing and Online Analytical Processing, Data Mining Concept, Data Mining Techniques, Data Mining Classification, Data Warehouse Research, Source Integration, Data Warehouse Refreshment, Multi-Dimensional Data Models and Aggregation, Query Processing and Optimization, Metadata and Data Warehouse Quality, Metadata and Data Warehouse Quality (Part II), Quality Driven Data Warehouse Design
• Capstone Project
  

  Duration & Number of Session Hours:

  This 12 Credit Programme Comprises:

  Duration: 3 Months, 180 Hours of Live Interaction.

  Number of Sessions (75 – 120 Minutes each): 108 sessions across 3 months

  Frequency: 9 sessions (i.e., 15 hours) a week

  *Students are expected to do self-study, research, work on labs, projects, assignments, assessment and other activities as per the requirements of each individual courses.

  **The programme duration may be slightly extended due to unavoidable situations.

How the Courses will be Delivered

Courses will be delivered through on-line mode using an appropriate technology Synchronized platform.  Lectures will be delivered through broadband based technology involving two-way audio and video communication. Sessions will be held once a week, generally on weekends. Participants can attend sessions directly from their desktop/laptop (Direct-2-device). Participants will be provided reading materials etc. for each course.  They may also interact with the concerned faculty through e-mails/ chat mode.

The academic sessions will start on -: May 01, 2024

The time gap between two consecutive sessions is to give the participants a break. On some days, the classes may extend beyond the mentioned time. In addition to attending interactive sessions, participants have to undertake online quizzes, assignments, and examinations.

Programme Activity Timelines

Total Fees and Payment Schedule

Learn More – https://uni.futurense.com/us-pathway

Credit Transfer of Admission to US University: The programme may allow certain participants (enrolled for the Futurense US Pathway programme) to get admission in the US university courses after completion. The Credit transfer, admission process, selection criteria, and final selection to the US universities are not under the control/discretion of IIM Indore. IIM Indore does not promise/guarantee any credit transfer to any US-based university or admission to any of its programmes.

The participants have to independently ensure such modalities with Futurense Technologies Pvt Ltd  or other third parties. IIM Indore will only deliver the course agreed and the certificate will be awarded after completion of the norms mentioned above for the “Advanced Certificate Programme in Business and Data Analytics”.

Please note that IIM Indore reserves the right to change the programme design, format, number of sessions, certificate format, and terms in the programme or can incorporate any such change deemed necessary by the institute without prior intimation.