Industrial Data Science Training

From live OPC UA and SQL Server plant data to machine learning models and a working predictive dashboard — one connected, hands-on learning path for engineers moving into Industry 4.0 analytics.

OPC UASQL ServerPythonPandasMachine LearningPower BI

Three-Level Industrial Data Science Path

Level 01

Industrial Data Acquisition, SQL Server & Python Wrangling

Connect to OPC UA and SQL Server historian data, clean sensor data, and handle missing values and outliers.

OPC UASQL ServerPandasCleaning

Level 02

Statistical Process Control, Feature Engineering & EDA

Build SPC charts, engineer rolling/lag/FFT features, and explore multivariate process relationships.

SPCFeature EnggEDAPCA

Level 03

Machine Learning, Predictive Maintenance & Power BI Dashboards

Train anomaly detection, RUL and quality-prediction models, then publish results to a live dashboard.

MLRULXGBoostPower BI

Curriculum For Industrial Data Science Training

Plant Data Sources (OPC UA / SQL)

What you'll learnConnect to OPC UA tags and SQL Server historian tables; understand tag structure, timestamps and data types from the plant floor.

OPC UA ClientpyodbcHistorian TagsSQL Server

Data Wrangling & Cleaning

What you'll learnHandle missing sensor readings, irregular sampling, outliers and timestamp misalignment across multiple sources.

PandasNumPyResamplingOutlier Detection

Statistical Process Control

What you'll learnBuild X-bar, R, EWMA and CUSUM charts to catch process drift before it becomes a defect or failure.

Control ChartsProcess LimitsDrift DetectionPython

Feature Engineering for Sensor Data

What you'll learnCreate rolling statistics, lag features and frequency-domain (FFT) features from vibration, temperature and pressure signals.

Rolling WindowsLag FeaturesFFTSignal Processing

Predictive Maintenance Modeling

What you'll learnTrain anomaly detection and Remaining Useful Life (RUL) models on equipment sensor data.

Isolation ForestXGBoostRUL RegressionVibration Data

Quality & Defect Prediction

What you'll learnBuild classification models predicting product defects from process parameters, and identify key drivers with feature importance.

Random ForestSHAPClassificationMetrics

Model & SQL Integration

What you'll learnWrite model predictions and scores back into SQL Server tables alongside live plant data for reporting.

SQL ServerINSERT/UPDATEPrediction Loggingpyodbc

Automated Python Reporting

What you'll learnGenerate shift, daily and monthly analytics reports (Excel, PDF) directly from model outputs and plant KPIs.

PandasopenpyxlPDF AutomationScheduling

Alerts & Notifications

What you'll learnTrigger email/SMS alerts when models flag anomalies, predicted failures or quality deviations.

SMTPThreshold AlertsScheduled JobsPython

Interactive Predictive Dashboard

What you'll learnBuild a live dashboard showing OEE, RUL estimates, defect risk scores and anomaly alerts.

Power BIPlotly DashLive KPIsModel Scores

Why Choose Softwell Automation

🏭

Real Plant Data

Training is built around real sensor, SCADA and historian data patterns, not toy datasets.

🧰

Hands-on Practice

Practice on OPC UA, SQL Server, Python and ML models instead of only theory.

📊

Full Data Lifecycle

Learn the complete flow from raw sensor data to a live predictive dashboard.

🎯

Job-Oriented Modules

Course modules match data analyst, reliability engineer and Industry 4.0 roles.

Frequently Asked Questions About Industrial Data Science Training

Who should join this Industrial Data Science training?

Instrumentation engineers, automation engineers, maintenance engineers, mechanical/electrical engineers and working professionals who want to apply data science and machine learning to plant, process and sensor data can join this course.

Do I need prior programming experience?

Basic computer familiarity is enough to begin. Python programming, SQL and statistics are taught from the fundamentals as part of the course.

Is corporate or in-plant training available?

Yes. Softwell Automation provides customized corporate and in-plant Industrial Data Science training for engineering and analytics teams.

What tools and software are covered in this course?

OPC UA, SQL Server, Python, Pandas, scikit-learn, XGBoost and Power BI or Plotly Dash are covered across the three training levels.