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.
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:
- 31 October
- 14 November
- 28 November
- 12 December
- 9 January
- 23 January
- 30 January
All programming assignments are to be submitted using JupyterHub.
- Materials
- Paul Gries, Jennifer Campbell, Jason Montojo: Practical Programming, Third Edition: An Introduction to Computer Science Using Python 3.6
- Python: https://www.python.org/
- 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:
- Participation – attend least 5 seminars
- Assignments – complete and submit at least 5 programming assignments
- Quizzes – complete 2 quizzes
