Introduction to Python for Data-analysis

English-language course

Introduction

Worldwide, Python is the most popular language for data science. Python is free and open source, allowing professionals worldwide to continuously update and add functionality. Although Python is a general programming language at its core, it offers numerous modules specifically designed for data analysis, data science, and machine learning. At the UG, both R and Python are widely used for data science. R is generally preferred for statistics and visualization, while Python is favored for larger programs and machine learning, including neural networks, deep learning, and large language models.

In this beginner's course, we will guide you through the basics of importing data, cleaning and restructuring data, visualizing and summarizing data, and finally applying statistical models to your data.

Result

At the end of the course, you will not only be able to work with Python, but you will also be able to expand your knowledge for your own specific work field. If you want to learn more about general programming using Python you can follow the course Introduction to Programming using Python either before or after this course. The content of this Python for Data-analysis course will be used as a prerequisite for a Python for Machine Learning course (under construction; mail Theo van Mourik (t.j.van.mourik rug.nl if you want to be kept up to date on the progress).

Interactive Learning Experience

This course relies heavily on highly interactive (online or hybrid) sessions where we review what you’ve done in the reader. During a review the teacher will share his screen and go through the code asking you by voting and chatting to find the error or complete the code. These reviews are used to rehearse material, show tips and tricks, warn for common mistakes, explain error messages, show how to use the helpfiles and the program (IDE) in general, and overall to motivate you to keep up the pace. Participants report they are highly involved during these sessions and the course is consistently highly evaluated. On average this course is rated with an 8.2 (10% gives a 10!) by students, PHD’s and other employees alike.

Practical Information

Goal

This introductory course is designed for anyone who wants to (re)learn the basics of the Python programming language necessary for data handling.

This course is suitable for beginners who are new to Python and those who have some experience with Python but never had the opportunity to grasp the fundamentals.

Content

Preparing your Python journey
Getting started with Numpy
Reading and writing data with Pandas
Data transformations with Pandas
Exploratory data analysis with Mathplotlib: Graphics
Exploratory data analysis: descriptive statistics
Statistical tests (how to run the tests, not how to interpret them)
What's more (other useful packages and more classical Programming)

Prerequisits

None, but a dream of what you’d like to do with Python would be nice.
Please note that Python has a steep learning curve. Expect you’ll need 3-4 hours between sessions to prepare for the next one and plan accordingly. Please be kind to yourself and allow yourself at least 48 hours to complete the course.

Enrollment and course fee

Fill out this form to enroll

You can unenroll until 8 days prior to the first session.
Late enrollments are fine, but please also contact the teacher to avoid the risk of being overlooked.
Participants will receive the course material via email a few days before the course starts.

For more information, you can email Theo van Mourik (t.j.van.mourik@rug.nl).

Prices for individuals

€100 BSc/MSc student at UG, other Dutch University or Hanze Hogeschool
€300 PHD-student at UG or other Dutch University
€650 Employee UG or other Dutch university/UMCG/Hanze Hogeschool
€650 UG Alumni
€1250 Other participants

Prices for groups

20 or more PHD’s €200 pp (minimum price of €4.000)

10 or more employees €400 pp (minimum price of €4.000)

20 or more employees €250 pp (minimum price of €5.000)

5 or more others €1.000 pp (minimum price of €5.000, we’ll also need to send a separate contract for this)

When enrolling a group of participants, you need to provide a single financial contact person/cost center number and the mailing addresses of all participants. You can enroll a group using the normal enrollment link.

You can also request a customized course and discuss dates, audience, and content. For more information mail Theo van Mourik (t.j.van.mourik rug.nl). This is also possible within the curriculum.

Date, time and location

Below you will find the dates and times of the upcoming courses. The content of these courses remains the same each time.

If these dates do not suit you and you would like to be notified of future courses, please contact the coordinator, Theo van Mourik (t.j.van.mourik@rug.nl).

(Premiere) July 2024: 2 week morning course

There a 6 sessions in total. Each session takes 4 hours and is expected to take 3-4 hours of preparation.
For this premiere the sessions are on-site only at the Zernike Campus in Groningen. Location: Mercator Building, room 5415.0031 (Landleven 1 Groningen).
All presentations are given via the Kaltura classroom (no account needed).
All presentations will be recorded and the recordings will be available for about 6 months after the course.
You will receive a certificate of attendance for attending 5 out of 6 sessions or (if preferred) after successfully completing a final assignment.
Since this is the premiere of this course we want to celebrate and add some catering during the sessions and organize a closing lunch. Also since this is the premiere, we will be regularly asking you for feedback.
Trainer: Emin Tatar

Session	Date (time 9:00 - 13:00)	Preparation
1	Mon July 1	Install Python and Spyder or start in UWP/VRW
2	Wed July 3	H1 – H2.7 Intro and Basics
3	Fri July 5	H2.8 – H3 Basics and import data
4	Mon July 8	H4 Working with tables
5	Wed July 10	H5 Graphs
6	Fri July 12	H6 – H8 Descriptives, tests, programming

October 2024 – 6 online morning sessions over 3 weeks

All sessions take 4 hours and take 3-4 hours of preparation each.
All presentations will be given via the Kaltura classroom (no account needed) and are fully online.
All presentations will be recorded and recordings will be available for about 6 months after the course.
You’ll receive a certificate, acknowledging a workload of 48 hours, after attending 5 of 6 sessions or (if you prefer) after completing a final assignment.
Trainer: Emin Tatar

Session	Date (time 9:00 - 13:00)	Preparation
1	Tue Oct 1	Install Python and Spyder or start in UWP/VRW
2	Fri Oct 4	H1 – H2.7 Intro and Basics
3	Tue Oct 8	H2.8 – H3 Basics and import data
4	Fri Oct 11	H4 Working with tables
5	Tue Oct 15	H5 Graphs
6	Fri Oct 18	H6 – H8 Descriptives, tests, programming

More information

For more information on this or similar courses, please mail the coordinator, Theo van Mourik (t.j.van.mourik rug.nl)

Last modified:

13 June 2024 3.55 p.m.

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