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Program Goals
- Demystify AI & Data Build foundational understanding of how AI and data analytics intersect and deliver business value for MSMEs.
- Hands-On Competence Equip participants with practical ability to analyse, visualise, and interpret data using free AI-powered tools.
- Decision Intelligence Enable data-driven decision-making by connecting analytics outcomes to real MSME business scenarios.
- AI Readiness Prepare participants to identify AI analytics opportunities within their own organisations and initiate pilot projects.
Program Outcomes — Participants will be able to
- Explain key AI and data analytics concepts confidently
- Clean, analyse, and visualise datasets using free tools
- Build basic predictive models using no-code/low-code AI platforms
- Interpret dashboards and derive actionable business insights
- Identify analytics use cases relevant to their MSME sector
- Present a simple data story to business stakeholders
- Evaluate AI analytics tools for their specific business needs
- Earn a certificate of completion from Bombay Chamber
Contents:
Day 1-
Module 1: AI & Analytics Fundamentals
- What is AI?
- What is Data Analytics?
- Types of analytics (Descriptive, Diagnostic, Predictive, Prescriptive)
- AI vs traditional analytics.
- Real MSME use cases.
Tools
Google Slides, ChatGPT Free, Microsoft Copilot Free, Gemini Free
Hands on Lab activity
Group mapping exercise: identify one analytics challenge in their own business using a structured template.
Module 2: Data Literacy & Preparation
- Data types and sources.
- Data quality, cleaning, and structuring.
- Understanding structured vs unstructured data. Introduction to datasets.
- Ethics and data privacy basics.
Tools
Google Sheets, OpenRefine, ChatGPT Free, Microsoft Copilot Free
Hands on Lab activity
Clean a provided messy sales dataset — remove duplicates, fill gaps, standardise formats using Google Sheets + AI suggestions.
Module 3: AI-Powered Data Analysis
- Descriptive analytics using AI.
- Summary statistics and pattern discovery.
- Using AI prompts to query and interpret data.
- Pivot tables and trend analysis.
Tools
Google Sheets, Julius AI Free, Google Colab, ChatGPT Free
Hands on Lab activity
Use ChatGPT and Julius AI to query and summarise the cleaned dataset — identify top products, peak seasons, and revenue trends.
Module 4: Data Visualisation
- Principles of effective data visualisation.
- Chart types and when to use them.
- Building dashboards.
- Storytelling with data.
Tools
Google Colab, Google Sheets Charts, Canva Free
Hands on Lab activity
Build a simple 3-chart business dashboard in Looker Studio using the cleaned dataset.
Day 2-
Module 5: Predictive Analytics & ML Basics
- What is Machine Learning?
- Supervised vs unsupervised learning.
- Regression, classification basics.
- How AI makes predictions forecasting examples.
Tools
Google Teachable Machine, Orange Data Mining, ChatGPT Free
Hands on Lab activity
- Classification model relevant to a retail or manufacturing context.
Module 6: AI Analytics Platforms
- Overview of no-code AI analytics platforms.
- Using AI to generate forecasts and reports.
- Automating insights with AI.
- Comparing free tools for MSMEs.
Tools
Julius AI Free, KNIME Analytics Platform, Orange Data Mining, Google Colab, ChatGPT Free
Hands on Lab activity
Upload MSME sales data to Julius AI
generate a 3-month forecast and automated insight report using natural language prompts.
Module 7: Data Storytelling & Presentation
- The data storytelling framework.
- Building a narrative from analytics.
- Visualising for executive audiences.
- Common mistakes in presenting data.
Tools
Canva Free, Google Slides, ChatGPT Free, Microsoft Copilot Free, Gemini Free
Hands on Lab activity
forecast — structured as Problem → Data → Insight → Recommendation → Action.
Module 8: Capstone & Certification
- AI analytics roadmap for MSMEs.
- Next steps and tool recommendations.
- Q&A and peer showcase.
- Assessment and certificate briefing.
Tools
All revised free tools used across the program
Hands on Lab activity
Each participant presents their data story (2 min each) to the group. Peer feedback using a structured review card.
Trainer Profile: Meenakshi Sundaram is a Senior AI Consultant, Corporate Trainer, and Developer Enablement Specialist with 24+ years spanning enterprise IT, AI Engineering, Academic Leadership, and Global training delivery.
Expert in bridging AI theory with enterprise implementation, designing and delivering hands-on programs for developers, architects, and leadership teams across 4 continents.
Deep technical foundation in LLM architectures, Agentic AI, RAG pipelines, GitHub Copilot, and ISO AIMS governance. Trusted advisor on responsible AI adoption and digital transformation at scale.
