Programme Overview

The Data Analytics for Engineers Programme is designed to equip engineers, technicians, engineering students, and professionals with practical data analysis skills that are increasingly required in modern engineering environments.

Participants will learn how to use industry-standard tools such as Microsoft Excel, Power BI, SQL, Python, and engineering dashboards to transform raw engineering data into actionable insights.

The programme bridges the gap between engineering and data science, enabling professionals to make data-driven decisions that improve productivity, reliability, safety, and operational efficiency.

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Duration

8 Weeks (2 Months)

Study Commitment

• 2 Live Sessions per Week
• Practical Workshops
• Real Engineering Data Projects
• Self-Paced Exercises

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Delivery Mode

✅ Live Online Classes

✅ Practical Labs

✅ Industry Projects

✅ Career Coaching

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Programme Fee

Standard Tuition Fee

£1,250

Early Bird Fee

£1,050

Registration Fee

£50

Flexible Payment Plan

• £350 Deposit
• Remaining Balance in 2 Installments

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Course Structure

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Module 1: Introduction to Engineering Data Analytics

Week 1

Topics Covered

• What is Data Analytics?
• Role of Data in Engineering
• Engineering Data Sources
• Data Types & Measurements
• Data-Driven Decision Making
• Engineering KPIs

Practical Exercise

Analyze engineering performance reports.

Learning Outcome

Understand how data supports engineering operations and business decisions.

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Module 2: Excel for Engineering Analytics

Week 2

Topics Covered

• Advanced Excel Functions
• Data Cleaning
• Pivot Tables
• Engineering Calculations
• Data Validation
• Dashboard Creation

Practical Project

Create an Engineering Performance Dashboard.

Learning Outcome

Use Excel to organize, analyze, and visualize engineering data.

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Module 3: Statistics for Engineers

Week 3

Topics Covered

• Descriptive Statistics
• Mean, Median & Standard Deviation
• Process Variability
• Trend Analysis
• Quality Metrics
• Engineering Performance Indicators

Practical Exercise

Analyze equipment performance trends.

Learning Outcome

Apply statistical techniques to engineering problems.

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Module 4: SQL for Engineering Data Management

Week 4

Topics Covered

• Database Fundamentals
• SQL Queries
• Data Extraction
• Data Filtering
• Reporting & Analysis
• Database Management Concepts

Practical Project

Build engineering reports using SQL queries.

Learning Outcome

Retrieve and manage engineering data from databases.

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Module 5: Power BI & Data Visualization

Week 5

Topics Covered

• Power BI Fundamentals
• Data Modeling
• Interactive Dashboards
• Engineering KPIs
• Report Automation
• Visual Storytelling

Practical Project

Develop a Plant Operations Dashboard.

Learning Outcome

Create professional dashboards that communicate engineering insights.

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Module 6: Python for Engineering Analytics

Week 6

Topics Covered

• Python Fundamentals
• Data Analysis Libraries
• Pandas
• NumPy
• Engineering Data Processing
• Automation Scripts

Practical Project

Analyze engineering datasets using Python.

Learning Outcome

Use Python to automate and enhance engineering analysis.

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Module 7: Predictive Maintenance & Industrial Analytics

Week 7

Topics Covered

• Maintenance Analytics
• Equipment Reliability
• Failure Analysis
• Asset Performance Monitoring
• Predictive Maintenance Concepts
• Industrial IoT Data

Practical Project

Predict equipment maintenance requirements using historical data.

Learning Outcome

Apply analytics to improve equipment reliability and reduce downtime.

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Module 8: Engineering Analytics Capstone Project

Week 8

Topics Covered

• Data Presentation Techniques
• Business Reporting
• Engineering Decision-Making
• Project Documentation
• Stakeholder Communication

Capstone Project

Students will analyze a real-world engineering dataset and develop a complete analytics solution, including:

• Data Cleaning
• Statistical Analysis
• Dashboard Development
• Recommendations Report
• Executive Presentation

Final Assessment

• Practical Analytics Project
• Dashboard Presentation
• Technical Knowledge Assessment

Learning Outcome

Demonstrate the ability to solve engineering problems using data analytics.

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Software & Tools Covered

Analytics Tools

• Microsoft Excel (Advanced)
• Microsoft Power BI
• SQL
• Python
• Google Sheets

Engineering Analytics Applications

• Maintenance Data Analysis
• Production Analytics
• Energy Consumption Analysis
• Quality Control Reporting
• Reliability Analytics

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Professional Certifications Awarded

Upon successful completion:

GDSL Professional Certificate in

Data Analytics for Engineers

Additional Certificates

• Advanced Excel for Engineering
• Power BI Data Visualization
• SQL for Data Analysis
• Python Fundamentals for Engineers
• Engineering Performance Analytics

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Engineering Sectors Covered

Manufacturing

• Production Monitoring
• Process Optimization

Energy & Utilities

• Energy Performance Analytics
• Asset Monitoring

Construction & Infrastructure

• Project Performance Reporting
• Cost Analysis

Maintenance & Operations

• Equipment Reliability
• Maintenance Planning

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Career Opportunities

Graduates can pursue roles such as:

Engineering Roles

• Engineering Data Analyst
• Maintenance Analyst
• Operations Analyst
• Reliability Analyst

Data Roles

• Junior Data Analyst
• Business Intelligence Analyst
• Reporting Analyst
• Data Visualization Specialist

Energy & Utilities Roles

• Energy Data Analyst
• Utility Performance Analyst
• Asset Performance Coordinator

Project Roles

• Project Controls Analyst
• Engineering Planning Coordinator
• Performance Reporting Officer

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Entry Requirements

Suitable For

• Engineers
• Engineering Technicians
• Engineering Students
• Project Engineers
• Maintenance Professionals
• Energy Professionals
• Recent Graduates

Recommended

Basic computer skills and familiarity with engineering concepts.

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Programme Benefits

Every student receives:

✅ Engineering Analytics Portfolio

✅ Power BI Dashboard Projects

✅ Industry Case Studies

✅ Career Coaching

✅ Technical CV Development

✅ LinkedIn Optimization

✅ Professional Certification

✅ Interview Preparation

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Why Choose GDSL?

📊 Industry-Focused Engineering Analytics Training

⚙️ Designed for Engineers & Technical Professionals

📈 High-Demand Digital Skills

🔍 Practical Data Analysis Projects

⚡ Power BI, SQL & Python Training

💼 Career Development Support

🌍 Applicable Across Multiple Engineering Industries

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Duration

8 Weeks

Tuition Fee

£1,250

Delivery Mode

In-Person + Practical Labs

Next Intake

Monthly

Included

• Advanced Excel
• SQL Fundamentals
• Power BI Dashboards
• Python for Analytics
• Predictive Maintenance
• Engineering Data Visualization
• Career Coaching

Buttons

Apply Now | Download Programme Brochure | Book a Free Consultation

Ideal Candidates

⚙️ Engineers

🔧 Engineering Technicians

📊 Operations Professionals

⚡ Energy Sector Employees

🏭 Manufacturing Professionals

🎓 Engineering Graduates

This programme is particularly attractive because it combines engineering knowledge with one of the most sought-after skills in industry today: data analytics. It can serve as a bridge between traditional engineering roles and higher-paying digital, operational excellence, and business intelligence careers. Discover how our eight-week course equips engineers with vital data analytics skills through practical, hands-on learning and expert guidance.