DS404
Python Refresher for Masters
Faculty
Alexandra Sumarokova
Software and ML engineer
Course length
Duration
Total hours
Credits
Language
Course type
Fee for single course
Fee for degree students
Skills you’ll learn
Overview
The course covers basic Python methods for data analysis: pandas, numpy, scipy, and sklearn, along with advanced techniques for their application. We’ll also review basic integrations of Python with external libraries like xgboost, tensorflow, and pytorch, along with data wrangling and some hyperparameter optimisation methods. Jupyter notebook usage and tricks will also be given as an organic part of the course.
At the end of the module, everyone is expected to be ready to work with ssh and git as long as they come up with a simple data wrangling system.
Learning highlights
- Learning basic Python methods for data analysis
- Learn basic git and ssh operations.
- Use of Python’s external libraries
- Learn how to effectively use the Jupyter notebook
Course outline
15 classes
Session 1
Jupyter notebook intro, tricks, hotkeys, platforms, Git, and ss Python methods integrated with jupyter.
Session 2
Memory, functions, decorators, and generators. Data manipulation. Pandas. Reading .csv files, Titanic dataset. Hands-on manipulating the datasets.
Session 3
Data visualization. Matplotlib, seaborn, bokeh, and plotly.
Session 4
OOP, libraries. Sklearn. Basic ML concepts: cross validation, fit/predict. Preparing prediction for Titanic dataset.
Session 5
Checking homework assignments on data manipulation, visualisation and git. Sklearn and numpy methods.
Session 6
Data versioning. Git. Working with enterprise data analysis systems, pitfalls, and techniques.
Session 7
Weekly homework revisiting. Performing data analysis at scale.
Session 8
Start working on general projects. Open discussion about what can and cannot be done with Python in seven days. Very basic custdev.
Session 9
Storing custom approximators as custom. Sklearn classes. Sklearn pipelines.
Session 10
Working with textual, visual, and audio data in Python.
Session 11
Advanced basic approximators to use in practice: xgboost, catboost, and vw. Off the shelf hyperparameter optimization. Automl.
Session 12
Integrating via Python. Google docs, chatbots, interface prototyping, data annotation, scrapping, and no-code platforms.
Session 13
Heavy dataset processing with Python instruments, Cython.
Session 14
Consultations on student projects.
Session 15
Finals
Course materials
Media
Prerequisites
Knowledge of Python on the level of snakify.org is highly recommended. A general interest in statistics and data analysis is also a plus.
Methodology
We will study a set of practical jupyter notebooks, interrupted by relatively short theoretical parts. There will be two big homework assignments designed to emulate a relatively real data science project. There will also be personal projects based on Python integrations and capabilities of data analysis; this will be a good example of time management in a DS project. Finally, students will have a final exam and a student project demonstration at the end of the course.
Grading
Alexandra has a solid 6-year background as a researcher, data analyst, and developer. After completing a degree in physics at MIPT, she spent six years at the university. There, she became an engineer and worked in a laboratory, conducting extensive data analysis. Concurrently, she provided private lessons in mathematics and physics to students to help them prepare for exams.
She then continued her career as an analyst at Yandex, gaining significant expertise in data analysis, mathematical statistics, and probability theory. She worked extensively with both online and offline product metrics. Afterward, she ventured into software engineering at the startup Rebels.ai, rapidly advancing her career. She served as a backend developer, team leader, project manager, and system architect.
See full profileApply for this course
Python Refresher for Masters
by Alexandra Sumarokova
Total hours
45 Hours
Dates
Nov 27 - Dec 15, 2023
Fee for single course
€1500
Fee for degree students
€750
How to secure your spot
Complete the form below to kickstart your application
Schedule your Harbour.Space interview
If successful, get ready to join us on campus
FAQ
Will I receive a certificate after completion?
Yes. Upon completion of the course, you will receive a certificate signed by the director of the program your course belonged to.
Do I need a visa?
This depends on your case. Please check with the Spanish or Thai consulate in your country of residence about visa requirements. We will do our part to provide you with the necessary documents, such as the Certificate of Enrollment.
Can I get a discount?
Yes. The easiest way to enroll in a course at a discounted price is to register for multiple courses. Registering for multiple courses will reduce the cost per individual course. Please ask the Admissions Office for more information about the other kinds of discounts we offer and what you can do to receive one.