Data fundamentals training

Prerequisites

Good Excel skills are a must.

Objectives

◗ Integrating the basics of AI algorithms

◗ Use tools and data analysis useful in corporate finance

◗ Reinforce your ability to interpret numerical results to inform financial decision-making

Training program

◗ Identify data and variable types

- Differentiate between categorical and numerical variables (discrete/continuous)
- Understand the nature of a population, an individual, and associated variables
- Visualize distributions and identify the shape of data

✔ UNDERSTAND | Illustration: variable classification and distribution typology
✔ ASSESS | Quiz: what do you think... Is an "age" variable always numerically continuous?

◗ Describe data using simple statistics

- Measures of central tendency: mean, median, mode
- Measures of dispersion: range, interquartile range, standard deviation
- Visual representations: histogram, whisker box

✔ APPLY | Case study: calculate and interpret statistical indicators from a customer file
✔ EXPERIMENTATE | Excel workshop: build a moustache box and interpret the shape of a series
✔ ASSESS | Quiz: in your opinion... When is the median more reliable than the mean?

◗ Measuring the relationship between variables

- Correlation between categorical variables (Chi², Cramer)
- Correlation between categorical and numerical variables: inter/intra variance
- Linear correlation between quantitative variables: correlation coefficient, regression line

✔ APPLY | Case study: build a crosstab and measure the intensity of a Chi-square relationship
✔ EXPERIMENTALIZE | Case study: analyze performance by age group
✔ EVALUATE | Quiz: what do you think... Does a strong correlation imply causation?

◗ Modeling a relationship: simple and multiple regression

- Linear fit, errors, coefficient of determination
- Interpretation of coefficients (slope, y-intercept)
- Multiple regression: integration of several explanatory variables

✔ APPLY | Case study: predicting performance according to several business factors
(quality, experience, conditions)
✔ EXPERIMENTATE | Excel workshop: using Excel's Regression tool with reading of key results.
✔ EVALUATE | Quiz: what do you think... How do you identify a redundant explanatory variable?

◗ Advanced approaches : Bayes, classification, bias

- Conditional probabilities and Bayes' law applied to management (customer risk, scoring)
- Classification methods: hierarchical/non-hierarchical segmentation
- Euclidean and cosine distances, intra/intergroup inertia

✔ APPLY | Case study: segmenting customers according to payment behavior or OD type
✔ EXPERIMENTATE | Workshop: classification with Excel Solver and interpretation of results.
✔ ASSESS | Quiz: what do you think... Why is cosine distance better suited to binary data?

Why choose this course?

Knowledge of the fundamentals of statistics and associated mathematical calculations is a prerequisite for Data Analytics. This course takes a fun, visual approach to these concepts, making them accessible to everyone. The majority of FinHarmony's Data Analytics training courses are based on the knowledge acquired during these two days.

Teaching and assessment methods

Before : practical information sheets on each tool, self-assessment quiz

During the session: alternating theoretical developments, illustrations and fun, interactive case studies, scripted in several stages. These numerous exchanges help validate the acquisition of skills throughout the course.

After: the participant keeps all Excel templates.
The trainer is available to answer any questions relating to the training.

General training | FinHarmony Conseil & Formation

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Price

1,860 EXCL.

Testimonials

Data fundamentals training

Jonathan C.
Company
Training

Generalist trainings