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The Python Programming Fundamentals For Data Science course will take place on Zoom every other Friday between 15:00 and 16:00 starting 15 October. It is intended for everyone who wants to learn the fundamentals of programming with Python: design, algorithms, testing, and debugging. The introduction to programming with Python will cover what happens when a program is executed step-by-step, handling data using multiple data types (numbers, text, data sets, files) and data sources using relational data bases and web services. While writing code, we will learn how to document and organise code so it is more easily readable and understandable when shared with colleagues.

Each seminar consists of two parts: theoretical and practical. The aim of practical part is to get hands on experience in writing computer programs using Python.

Language: English and Latvian

About the instructor

Uldis Doniņš is a researcher and the Head of the Information Systems Unit of the RSU IT Department. He holds a PhD (Dr.sc.ing.) in Computer Science and his field of study is software modeling and modeling formalisation. Doniņš has expanded his knowledge and experience in the fields of machine learning and data intensive computing at the University at Buffalo (State University of New York, USA), School of Engineering and Applied Sciences. Being a part of Artificial Intelligence Machine Learning provides computer learning and decision-making based on the provided data that can be developed using supervised, unsupervised or reinforcement learning models. Data intensive computing deals with diverse data formats, storage models, application architectures, programming models and algorithms and tools for large-scale data analytics.

Contents

15 Oct

15:00 – 16:30

Introduction

course organisation, integrated development environment used in this course, programming assignments, how to submit them, content in e-studies. How to set up programming environment on your computer. First steps in Python.

29 Oct

15:00 – 16:30

Python programming I

basics, data types, variables, mathematical operations.

12 Nov

15:00 – 16:30

Python programming II

choices, loops, arrays, file handling.

26 Nov

15:00 – 16:30

Python programming III

functions, introduction to object oriented programming, advanced data types.

10 Dec

15:00 – 16:30

Working with data I

working with API (Application Programming Interface), handling data in XML and JSON formats.

7 Jan

15:00 – 16:30

Working with data II

relational database concepts, working with data using SQL.

21 Jan

15:00 – 16:30

Machine Learning solutions with Python

Prerequisites
  • Experience in Python or any other programming language is not required.
  • Understanding of data structures, experience using electronic spreadsheets like Microsoft Excel for data analysis.
  • Laptop or desktop PC with internet connection, microphone and webcam (for active participation in online seminar).
Assignments

Programming assignments will be released after each seminar on the following due dates:

  1. 31 October
  2. 14 November
  3. 28 November
  4. 12 December
  5. 9 January
  6. 23 January
  7. 30 January

All programming assignments are to be submitted using JupyterHub.

Materials
  1. Paul Gries, Jennifer Campbell, Jason Montojo: Practical Programming, Third Edition: An Introduction to Computer Science Using Python 3.6
  2. Python: https://www.python.org/
  3. Python Tutorial: https://www.w3schools.com/python/
Classroom management
  • E-studies - course general information, access to all tools used in course
  • Panopto - lecture recordings
  • JupyterHub - IDE, used for submitting homeworks
  • GitLab -  git repository for code sharing
Course work / Grading

To get Certificate of Compliance participants must comply with the following:

  1. Participation – attend least 5 seminars
  2. Assignments – complete and submit at least 5 programming assignments
  3. Quizzes – complete 2 quizzes
    Room
    online
    Date:

    Contacts