Training Methodology
Expert-led, interactive sessions
Business case studies and group exercises
Tool-based learning (no coding)
Simulation and capstone for real-world application
Key Benefits:
Demystify machine learning and predictive analytics
Understand the business applications of supervised and unsupervised learning
Learn to identify high-value use cases across industries
Analyze and interpret machine-generated insights
Build confidence to lead data-driven innovation
Delivery Format:
This course is available in both in-person and online formats, offering flexibility without compromising on quality.
Duration: 6 Days (Full-Day Sessions)
Format: In-Person or Live Virtual Classroom
Venue: Premium 4–5 star hotels (for in-person); online via live sessions
Group Size: 1–5 participants (in-person and online)
Approach:
Expert-led sessions with real-world applications
Group exercises, industry case studies, and hands-on tools practice
Capstone simulation on Day 6
Interactive online discussions and collaborative workspaces
Course Features
- Lectures 24
- Quiz 0
- Duration 6 days
- Skill level Expert
- Language English
- Students 0
- Certificate Yes
- Assessments Yes
- 6 Sections
- 24 Lessons
- 6 Days
- Day 1: Foundations of Data Science & Business Intelligence4
- Day 2: Machine Learning Demystified4
- Day 3: Predictive Modeling in Practice4
- Day 4: Tools, Platforms & Automation4
- Day 5: ML Use Cases Across Industries4
- Day 6: Capstone & Executive Simulation4
Requirements
- No programming knowledge required
- Familiarity with spreadsheets or basic data interpretation helpful
- Open mindset and readiness to explore technical concepts applied in a business context
Features
- Six-day intensive in-person delivery in luxury hotel venues
- Applied exercises using Power BI, Excel, and visual ML tools
- Real-world case studies from finance, supply chain, and marketing
- Guided capstone project on business-focused ML deployment
- Certificate of Professional Achievement from Alverton Global
Target audiences
- Mid-to-senior professionals responsible for strategy, innovation, or operations
- Business analysts, consultants, or product managers
- Executives overseeing digital transformation
- Professionals aiming to work effectively with data science teams