Overview

This is not just an AI course.

It is not just a data analytics course.

And it is not simply a course about automation.

The Zabrol AI & Data Transformation Programme is an advanced programme designed for professionals who want to understand how AI, data, automation and intelligent systems can be used to solve business problems and transform organisations.

You’ll move beyond using AI as a productivity tool and begin learning how to design, build and implement AI-powered solutions.

What You’ll Get

✔ 12 weeks of advanced learning
✔ Weekly instructor-led expert sessions
✔ Advanced AI and data concepts
✔ Advanced prompt engineering
✔ AI-powered analytics
✔ Advanced Python
✔ Data automation
✔ AI workflow design
✔ AI agents
✔ Data engineering foundations
✔ Machine learning fundamentals
✔ Generative AI applications
✔ RAG and knowledge assistants
✔ AI strategy and transformation
✔ AI engineering foundations
✔ Business process transformation
✔ AI transformation capstone project
✔ Career and consulting guidance

What Makes This Different?

Many professionals use AI to:

• Write emails
• Summarise documents
• Generate content
• Ask questions

That’s useful.

But organisations need people who can ask a bigger question:

“Where can AI and data create real business value?”

This programme teaches you to look at an organisation, identify opportunities, design solutions and understand how those solutions can be implemented.

You’ll progress from:

Using AI → Building with AI → Automating with AI → Transforming with AI

What You’ll Learn

AI & Data Transformation

• AI and the changing workplace
• Data as a strategic asset
• Digital transformation
• AI transformation
• AI maturity
• AI use cases
• AI adoption
• AI strategy
• Human + AI collaboration
• Future of work

Advanced Prompt Engineering

• Advanced prompting
• Context and instructions
• Constraints
• Examples
• Structured outputs
• Prompt templates
• Prompt testing
• Prompt evaluation
• Advanced AI workflows

AI-Powered Analytics

• AI-assisted data exploration
• AI-assisted cleaning
• Statistical analysis
• Pattern detection
• Anomaly detection
• Predictive analytics
• Prescriptive analytics
• Forecasting
• Scenario analysis
• Decision modelling

Advanced Python

• Advanced Pandas
• NumPy
• Data transformation
• APIs
• Data pipelines
• Automation
• Advanced visualisation
• Statistical analysis
• AI-assisted coding
• Debugging and testing

AI Automation

• Identifying repetitive processes
• Workflow mapping
• Automated data collection
• Automated cleaning
• Automated reporting
• APIs
• Connecting systems
• No-code/low-code automation
• AI-powered workflows
• Human approval workflows

AI Agents

• What AI agents are
• Assistants vs agents
• Agent workflows
• Tools
• Memory
• Planning
• Actions
• Multi-step workflows
• Tool calling
• Agent testing
• Guardrails
• Monitoring and evaluation

Data Engineering for AI

• Data pipelines
• ETL/ELT
• Data warehouses
• Data lakes
• Data integration
• APIs
• Data quality
• Data governance
• Preparing data for AI

Machine Learning

• Machine learning fundamentals
• Supervised learning
• Unsupervised learning
• Regression
• Classification
• Clustering
• Training and testing
• Features and targets
• Model evaluation
• Overfitting
• Model interpretation

Generative AI & RAG

• Generative AI applications
• Document analysis
• Information extraction
• Question answering
• Multimodal AI
• Knowledge bases
• Embeddings
• Vector search
• Retrieval
• RAG
• AI knowledge assistants

AI & Business Transformation

• Business process mapping
• Identifying inefficiencies
• AI opportunity assessment
• Process redesign
• Automation opportunities
• Productivity
• Customer experience
• Employee experience
• AI strategy
• AI roadmaps
• Business cases
• ROI
• AI risk
• Governance
• Change management

AI Engineering Foundations

• AI application architecture
• APIs
• LLM APIs
• Model selection
• Prompt pipelines
• Tool calling
• Function calling
• Structured outputs
• Connecting AI to data
• Connecting AI to APIs
• AI application development
• Testing and deployment concepts

Transformation Capstone

You will identify a real business problem and develop an AI and data transformation solution.

Your project will follow:

Problem → Process → Data → AI Opportunity → Solution → Prototype → Automation → Business Value

Depending on the problem, your project could include:

• AI automation
• AI agent
• Power BI dashboard
• Python application
• Machine-learning model
• RAG knowledge assistant
• AI-powered reporting
• AI business workflow
• AI application

Who This Course Is For

✔ Experienced Data Analysts
✔ BI professionals
✔ Data Scientists
✔ Technology professionals
✔ Business analysts
✔ Managers and decision-makers
✔ AI enthusiasts with technical foundations
✔ Professionals moving into AI
✔ Aspiring AI Engineers
✔ Aspiring AI Consultants
✔ Professionals interested in AI automation
✔ Entrepreneurs building AI-powered businesses

Real Impact

✔ Advanced and practical
✔ Business-focused
✔ Project-driven
✔ AI + data + automation combined
✔ Focused on solving real problems
✔ Develops technical and strategic thinking
✔ Builds advanced portfolio projects
✔ Opens pathways towards AI, analytics and transformation careers

What You’ll Achieve

By the end of this programme, you will:

✔ Understand AI and data transformation
✔ Design advanced AI workflows
✔ Build AI-powered analytical solutions
✔ Automate repetitive business processes
✔ Understand and prototype AI agents
✔ Work with Python for advanced analytics and automation
✔ Understand data engineering for AI
✔ Build basic machine-learning solutions
✔ Understand Generative AI and RAG
✔ Design AI transformation strategies
✔ Understand the foundations of AI engineering
✔ Complete an AI/data transformation capstone project
✔ Build an advanced AI and data portfolio
✔ Identify opportunities to use these skills professionally or commercially

Your Transformation Journey

Analyse → Automate → Build → Integrate → Transform