Learning Tracks

The perfect learning program for your specific needs

Our learning tracks are collections of training courses, designed to address specific needs.

You do not have to worry about choosing the courses from our list, just find yourself in one of the following tracks and the courses are already selected for you.

Cannot find what you were looking for? Contact us and let’s build your perfect track together!

Apply Science - Digital Innovation Starter Kit
Data Modeling - Apply Science

Digital Innovation Starter Kit

This top selling learning track will give you all the basis you need to gain a data driven mindset and the skills to analyse data, find relations and to identify and quantify the most important features in your data. The track begins with some modules from our Efficient Data Science methodology, then goes on with Basic Statistics, or with Minitab Essentials if you want to use exclusively Minitab.

Topics include:

    • Introduction to Data Science and Statistics: definition and importance in real use cases
    • Creation of a data driven mindset: why and how collect, organise and use data
    • Artificial Intelligence and machine learning: definition and when and how are useful
    • Descriptive Statistics: mean, median, IQR, range, percentiles, standard deviation
    • Understanding and using location and variation like a pro
    • Graphs: using the correct graph and reading it correctly (histograms, bar charts, Pareto charts, scatterplots, boxplots)
    • Statistical inference: definition, importance and main tests (t-tests, normality test)
    • Analysis of Variance (ANOVA) and regression models. Definition, vital importance and relation
    • Definition of interaction between variables and how to identify and quantify it
    • Introduction to response optimisation and multi optimisation

Duration: 2 days

Quality Statistics - quality control - Apply Science
Statistical Process Control - Minitab - Apply Science

Mastering Quality and Process Control

Another top selling learning track, designed to provide every statistical tool you need for statistical process control (SPC) and quality control (QC). Starting from basic statistics, you will learn all the main topics of statistical quality analysis and many advanced techniques and tools that will turn you into a complete professional of quality. This learning track include courses such as Minitab Essentials (or Basic Statistics), Statistical Quality Analysis and Additional Topics in Statistical Quality Analysis.

Topics include:

    • Introduction to Statistics: what is it, what you need it and why you will love it by the end of this track
    • Descriptive Statistics: location and variation indexes, main graphs, common errors and expert guidelines
    • Statistical tests: t-test, Analysis of Variance (ANOVA), normality test, test for equal variance
    • The curse of variability and the definition of quality
    • Measurement systems analysis (MSA): Gage R&R, attribute agreement, gage linearity and bias
    • Control charts: for variable and for attribute data (I, Xbar, R, S, MR, P)
    • Capability analysis for normal and non normal data (Ppk Cpm, Cp, Pp)
    • Between/Within capability analysis
    • Advanced control charts: rare events, short run processes, EWMA

Duration: 3 days

Process and cost optimisation - Apply Science
Process optimisation - Apply Science

Improving Processes and Products

This learning track is focused on optimisation and improvement. The tools you will learn are the tools you need when your quality and/or costs are not like you want them to be. Starting from the very basics, as in any of our tracks, you will acquire distinctive professional skills in design of experiment (DOE) and optimisation. Contents come from Basic Statistics, Factorial Designs, Response Surface Designs and DOE in Practice. Also, this amazing learning track takes some exclusive contents from our famous methodology Efficient Data Science.

Topics include:

    • Introduction to Data Science and Statistics: definition and importance in real use cases
    • Definition of optimisation and practical mathematical tools for optimisation
    • Descriptive Statistics and Inferential Statistics (Location and variation indexes, tests, ANOVA, regression models)
    • Introduction to DOE and sequential experimentation
    • Factorial Designs, Response Surface Designs, Split Plot Designs, Screening Designs
    • Optimisation and multi optimisation
    • Monte Carlo simulation and application to DOE regression models

Duration: 4 days

Statistics for Pharmaceuticals - Apply Science

Statistics for Pharmaceuticals

This learning track is completely dedicated to Pharmaceuticals. You will learn all the statistical tools required by the main guidelines, like FDA guidelines. Your PQR will be statistically perfect and clear and you will understand and manage every statistical tool you need to embrace the philosophy of Quality by Design (QbD). The topics included are really many, so you can chose to follow this track as a company, with different teams following different specific contents.

Topics include:

    • Basic Statistics and Statistical Quality Analysis
    • Design of Experiment also with Formulation and Mixture Design
    • Quality by Design and Data Integrity