Artificial Intelligence in Business
Senior Professional Track. Celltron Artificial Intelligence Lab – Empowering Minds, Building Nations
Dealine: 2025-11-28
Course Description
Key
Program Information
|
Category |
Details |
|
Eligibility |
Students in Grades 9–12, HSC, A-Level, or Adults |
|
Prerequisites |
No prior coding or AI experience required |
|
Course Duration |
3 Months (12 Weeks, 24 Classes, 2 Classes per Week) |
|
Class Duration |
90 minutes per class |
|
Delivery Mode |
Online / Offline (depending on availability) |
|
Tools & Software |
Python, Power BI, Tableau, Google Teachable Machine,
Excel / Google Sheets |
|
Learning Outcomes |
1. Understand AI concepts, machine learning, and
business intelligence 2. Develop Python programming skills for predictive
analytics 3. Create interactive dashboards and visualizations 4. Apply AI and
BI for problem-solving in real-world scenarios 5. Build a portfolio of 6
professional projects |
|
Project Highlights |
Chatbot Project, Dashboard Project, ML Prediction
Model, BI Analysis Project, AI Problem-Solving Case, Capstone AI Project |
|
Support |
Mentorship and step-by-step guidance for all
projects |
|
Certification |
Certificate of Completion + Capstone Showcase
Recognition |
Module 1: Introduction to Artificial Intelligence
|
Week |
Class |
Topic /
Activity |
Learning
Objective |
Outcome /
Project Milestone |
|
Week 1 |
Class 1 |
What is AI? Principles & Applications |
Understand AI concepts, history, and global
applications |
Group discussion: “AI in Our Daily Lives” |
|
Class 2 |
AI in Business and Society |
Learn real-world AI use cases |
Case study review of AI in finance, healthcare, and
retail |
|
|
Week 2 |
Class 3 |
AI Tools Overview (No-Code / Low-Code) |
Introduction to AI platforms for professionals |
Explore no-code AI platforms like ChatGPT, Lobe, or
Teachable Machine |
|
Class 4 |
Build Your First AI Chatbot |
Hands-on: chatbot using no-code tool |
Create a simple Q&A chatbot for customer support
or FAQ |
|
|
Mini-Project |
— |
Simple Chatbot |
Apply AI basics to practical solution |
Project 1: “Customer FAQ Chatbot” |
Module 2: Data Analytics & Visualization
|
Week |
Class |
Topic /
Activity |
Learning
Objective |
Outcome /
Project Milestone |
|
Week 3 |
Class 5 |
Introduction to Data Analytics |
Learn the analytics workflow: collect, clean,
analyze |
Understand data types and cleaning techniques |
|
Class 6 |
Data Cleaning & Transformation |
Hands-on cleaning datasets using Excel / Python |
Prepare dataset for visualization |
|
|
Week 4 |
Class 7 |
Data Visualization Principles |
Understand charts, dashboards, and storytelling with
data |
Explore visualization options: bar, line, scatter
plots |
|
Class 8 |
Building Dashboards (Power BI / Tableau) |
Hands-on: create interactive dashboards |
Project dashboard with real dataset |
|
|
Mini-Project |
— |
Dashboard Project |
Apply analytics and visualization |
Project 2: “Sales/Marketing Dashboard” |
Module 3: Machine Learning Fundamentals
|
Week |
Class |
Topic /
Activity |
Learning
Objective |
Outcome /
Project Milestone |
|
Week 5 |
Class 9 |
Introduction to Machine Learning |
Understand supervised vs unsupervised learning |
Explore ML algorithms overview |
|
Class 10 |
Data Preprocessing for ML |
Learn feature selection, normalization, and
splitting datasets |
Prepare dataset for ML model |
|
|
Week 6 |
Class 11 |
Supervised Learning (Regression &
Classification) |
Build predictive models |
Implement regression/classification in Python |
|
Class 12 |
Unsupervised Learning (Clustering) |
Explore clustering algorithms |
Group similar data points using Python |
|
|
Mini-Project |
— |
ML Prediction Model |
Apply ML concepts |
Project 3: “Predict Customer Churn / Sales Forecast” |
Module 4: Business Intelligence Tools
|
` |
Class |
Topic /
Activity |
Learning
Objective |
Outcome /
Project Milestone |
|
Week 7 |
Class 13 |
Introduction to BI Tools |
Learn the purpose of BI for decision-making |
Overview of Power BI, Tableau, and Looker |
|
Class 14 |
Data Integration & Automation |
Understand ETL (Extract, Transform, Load) and data
pipelines |
Hands-on connecting multiple datasets |
|
|
Week 8 |
Class 15 |
Analytics & KPI Monitoring |
Learn to track KPIs and metrics |
Build automated dashboards for performance tracking |
|
Class 16 |
BI Case Study |
Apply BI to real-world business data |
Analyze retail or banking dataset |
|
|
Mini-Project |
— |
Business Analytics Project |
Apply BI tools |
Project 4: “Retail Sales Analysis Dashboard” |
Module 5: AI for Problem Solving
|
Week |
Class |
Topic /
Activity |
Learning
Objective |
Outcome /
Project Milestone |
|
Week 9 |
Class 17 |
Identifying Business Challenges |
Learn how to frame problems for AI solutions |
Brainstorm potential AI applications in industry |
|
Class 18 |
AI Solution Design |
Explore methods to solve problems using AI |
Create solution design templates |
|
|
Week 10 |
Class 19 |
AI Implementation Strategies |
Learn best practices for AI adoption |
Evaluate tools, data, and ethical concerns |
|
Class 20 |
Group Case Study |
Apply AI knowledge to national productivity scenario |
Present AI solution plan for a case study |
|
|
Mini-Project |
— |
AI Problem-Solving Case |
Combine analytical & AI skills |
Project 5: “AI Solution Proposal” |
Module 6: Capstone Project
|
Week |
Class |
Topic /
Activity |
Learning
Objective |
Outcome /
Project Milestone |
|
Week 11 |
Class 21 |
Capstone Brainstorming |
Identify business or societal problem to solve |
Ideate project solutions integrating AI, ML, and BI |
|
Class 22 |
Project Prototype Development |
Combine learning from all modules |
Build working prototype or dashboard |
|
|
Week 12 |
Class 23 |
Testing & Refinement |
Improve solution based on feedback |
Prepare for final presentation |
|
Class 24 |
Final Capstone Showcase |
Present integrated solution |
Project 6: “AI for Sustainable Business”
presentation |
