Industrial curriculum overview with charts and machinery

Curriculum Overview

Your structured path to mastering industrial data analytics

What You'll Learn

Sensors and data sources in manufacturing
Day 1: Industrial Data Sources
  • Understanding sensor, machine, and process data
  • Identifying high-value data points
  • Exploring typical formats in manufacturing
Cleaning and preparing industrial data
Day 2: Data Preparation & Quality
  • Handling missing values and noise
  • Structuring datasets for analysis
  • Industrial data quality metrics
Statistical analysis for manufacturing
Day 3: Statistical Analysis
  • Core statistics for manufacturing
  • Detecting anomalies and bottlenecks
  • Data-driven process optimization
Predictive maintenance and dashboards
Day 4-5: Predictive & Visualization
  • Building simple predictive models
  • Forecasting equipment issues
  • Creating visual dashboards

Five-Day Course Structure

1

Introduction to Industrial Data Sources

Gain an overview of key data types and sources in modern manufacturing—from IoT sensors to PLCs and quality systems.

  • Types of industrial data: time series, event, and transactional
  • Understanding data flow in factories
  • How to recognize actionable information
2

Data Collection, Cleaning, and Quality Control

Develop skills to handle, prepare, and assure the quality of raw manufacturing data.

  • Common data preparation techniques
  • Filtering noise and managing outliers
  • Measuring data integrity
3

Statistical Analysis for Operations

Apply practical statistical methods for deeper insight into production processes.

  • Descriptive analytics: mean, median, trends
  • Variance and control charts
  • Identifying process improvement opportunities
4

Predictive Maintenance Essentials

Start building models that predict when equipment will need maintenance, reducing unplanned downtime.

  • Intro to predictive maintenance techniques
  • Early failure detection with simple models
5

Visualization & Actionable Dashboards

Learn to design dashboards that turn analysis into clear, actionable insights for stakeholders.

  • Principles of effective data visualization
  • Building simple dashboards for industrial KPIs

Each module blends concise explanations, practical examples, and hands-on exercises.

Total commitment: 30 minutes per day, for 5 days.

Featured Mini-Projects

Data Cleaning Challenge

Work with a sample machine log to clean, filter, and prepare a dataset ready for meaningful analysis.

Detecting Anomalies

Use real production data to identify outliers and visualize process variations with custom charts.

Simple Predictive Model

Build and interpret a basic model that forecasts equipment maintenance needs from sensor data.

Reserve Your Spot Today

Start learning immediately after registration