Scientific Director

Emmanuel Tsiritakis,

Professor, Department of Banking and Financial Management, University of Piraeus

Target Audience

The Course is aimed at university graduates/professionals and students of informatics, economics and other technical schools who wish to be introduced to Python and to understand and make use of the tools available in the field of Data Analysis.

Admission Requirements

Participants must have:

• Education: Secondary
• Foreign language level: good
• Computer skills: basic computer literacy
• Internet access
• Personal email account
• Knowledge of a programming language is desirable.

Successful completion of the unit "Introduction to Python" is a prerequisite for attending the unit "Data Analysis with Python". Some knowledge of statistics is desirable, so that trainees can study the subject in greater depth and better understand the second unit.

Delivery Method

The Course is attended exclusively online through simple educational software (an asynchronous e-learning platform); digital Educational Material and continuous educational support are provided. Once a candidate is admitted to the Course, a user account is created on the e-learning platform, giving access to the unit of their choice. Within each unit, electronic Educational Material prepared by the responsible instructor is posted on the e-learning platform on a weekly basis. The Educational Material includes electronic notes with theory and examples in PDF format, which can be saved and printed so that study is also possible offline. During the course, assignments may be set. Trainees have access at any time and from anywhere with an Internet connection to all activities, information sources and announcements of each course, and are given contact details for the instructor so that they can resolve any questions. Participants must:

• study the material and the notes
• use the links related to the course material
• submit assignments and final examination answers

Type of Certificate

Trainees who successfully complete all the Units of the Course are awarded a Training Certificate by KEDIVIM of the University of Piraeus. Participants who choose to attend only some of the thematic units are awarded a Training Certificate listing the Teaching/Thematic Units they have successfully completed. If successful completion of the Course is not possible due to discontinuation of studies or failure in the examinations, the trainee is awarded a Certificate of Attendance by KEDIVIM of the University.

See a sample of the certificates awarded, as applicable, here

Teaching/Thematic Units

Learning Outcomes

Upon successful completion of the course, trainees will:

know how Python can help a Data Analyst

are able to read data from and save data to disk

✔️ know ndarray objects, ways of reshaping arrays (reshaping arrays, repeat, take, put) and sorting (argsort, lexsort)

understand useful commands for interacting with the operating system, as well as additional features of IPython

✔️ understand data modelling using ready-made libraries (statsmodels), with an introduction to scikit-learn for machine learning

understand the NumPy library through examples

are able to install Python and become familiar with its environment

can use variables and variable types, and modify the values they contain

know and understand Python variables, lists and classes

can use useful guides, tools and libraries of Python

can use the pandas library, with examples

are able to load, store and modify data

can use data visualisation and representation tools

can use data grouping capabilities through the groupby function

✔️ can use pandas to categorise data by converting lists into categorical data types, as well as further uses of groupby

can use loops, handle errors and add further libraries

✔️ are able to use the tools and structures that a Data Analyst needs to know and use in order to transform data

can handle time series – using datetime, time, calendar

Assessment

The examination process takes place remotely via the e-learning platform, with the final examination questions and exercises posted in the form of an assignment with a deadline for submitting answers. Late participation in the final examination may be arranged in consultation with the trainee, provided that no more than one year has passed since their registration in the relevant teaching unit.

Discount Policy

The following discount categories apply:

1. GROUP A: Unemployed persons, members of large families and families with three children, persons with disabilities, graduates and students of the University of Piraeus, employees of the University of Piraeus (permanent or under contract), municipal employees
2. GROUP B: Undergraduate students of universities/technological institutes (AEI/TEI) or persons up to 30 years of age holding a European Youth Card, participants of previous cycles, registration for at least two courses in the same period

Please note that:

• Discounts are not cumulative.
• Each trainee may benefit from only one discount category.
• Participants entitled to a discount must submit the supporting documents that will be requested.

Course Fee after discount

Payment of Fees

Fees are payable in a single payment or in equal monthly instalments, the number of which corresponds to the duration of the Teaching Unit in months, provided that the fees are paid in full 2 weeks before the end of the Teaching Unit. Failure to pay any instalment will result in the automatic exclusion of the candidate from the remainder of the Course, the examinations and the award of the certificate.