Advanced Data Analysis Techniques

Scientific Management with Data Analytics

5 Found
17-21 Jul 20235 Days London - UKUS$4,450
18-22 Sep 20235 Days Dubai - UAEUS$3,450
25-29 Dec 20235 Days Dubai - UAEUS$3,450
15-19 Jul 20245 Days London - UKUS$4,450
16-20 Sep 20245 Days Dubai - UAEUS$3,450
23-27 Dec 20245 Days Dubai - UAEUS$3,450

Course Overview

We live through the Age of Data Analysis, Information and Statistics and the challenging times of tectonic shifts within geopolitical realms. Data is no longer scarce today – it’s overpowering and can help avoid mistakes and pitfalls. The main focus is going through the overwhelming volume of data available to organisations and businesses and correctly interpreting its implications. However, for organisations and employees to sort through all this information, data and its relations, there is a great need for the right statistical data analysis without falling into the chasm of buzzwords and bad data.

As the industry is in its current obsession with Big Data and Data Analytics, the software companies and statisticians have produced a lot of valuable tools and techniques available to large organisations. This Advanced Data Analytics training course shows by example how to build on the methods learned and to create a variety of powerful modelling, simulation, and predictive analytical methods.

The methods introduced include Bayesian models, Newtonian and genetic optimisation methods, Monte Carlo simulation, Markov models, advanced What If analysis, Time Series models, Linear Programming, and more, as well as the introduction and use of several available software for data analytics, from the basic ones to the very complex and advanced ones.

Course Objectives

After the training course, the participants will learn to:

  • Use measurement systems for data gathering
  • Adequately prepare and optimise the process designs
  • Conduct accuracy tests for error resolution within the data gathered
  • Develop data-gathering plan
  • Apply statistical methods for statistical experiment designs

Target Audience

This training course is dedicated to professionals working within data analytics in every industry using the data for process optimisation, systems improvement, and experiment design. It also describes the sensors used and the methods to test and improve the accuracy of statistical measurement.

It is suitable for a wide range of working professionals, including (but not limited to) the following:

  • Process Engineers
  • Data Scientists
  • Project Managers
  • Anyone involved in the Digitalisation of Operations

Training Methodology

This training course will utilise various proven adult learning techniques to ensure maximum understanding, comprehension and retention of the information presented. This includes the theoretical presentation of the concepts, the actual implementation of statistical tools and techniques, setting up and conducting the experiment and verifying and interpreting results. The delegates will use software for data visualisation, analysis, and simulation.

Course Outline

Day One

Measurement Systems for Data Collection

  • Signal Gathering, Processing, and Control
  • Measurement System Calibration
  • Uncertainty Analysis in Measurement Systems
  • Signal Statistical Parameters
  • Digital Signal Measurement and Analysis
  • Removing the Noise and Bias from the Data
Day Two

Basic Statistics and Probability Concepts

  • Sets, Union, and Intersection
  • Probability Density Functions
  • Data Rejection, Single and Paired Variable Outlier Determination
  • Chi-Squared Distribution
  • Hypothesis Testing
Day Three

Correlation and Regression

  • Correlation and Causation
  • Least Squares Regression Analysis
  • Linear Regression
  • Regression Confidence Analysis
  • Determining Autocorrelation
  • Determining Cross-correlation
Day Four

Statistics for Process Control

  • Statistical Process Control (SPC) Charts
  • Statistics for Process Capability Analysis
  • Identifying Sources of Error
    • Systematic Errors
    • Random Errors
  • The calculation for the estimate of the combined uncertainties
  • Experiment Design
Day Five

Data Analysis for Managerial Decision Making

  • Capacity, Utilisation, and Bottlenecks
  • The Dangers of Process Variability
  • Data Analysis Use
  • Clustering
  • Predictive and Prescriptive Analytics


Upon successful completion of this training course, Newage Certificate will be awarded to the delegates.

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