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DS404

Python for Data Scientists

Barcelona Campus
Nov 28, 2022 - Dec 16, 2022
By the end of the Python for Data Scientists course, students will be familiar with standard Python for data analysis, usage of Jupyter, and simple packages compatible with Python methods.
Barcelona Campus
Nov 28, 2022 - Dec 16, 2022
Maxim Musin

Faculty

Maxim Musin

CEO at rebels.ai

Course length

3 weeks

Duration

3 hours
per day

Total hours

45 hours

Credits

6 ECTS

Language

English

Course type

Offline

Fee for single course

€1500

Fee for degree students

€750

Skills you’ll learn

Data AnalysisPythonData ManagementAdvanced codingData WranglingStandard Python for Data Analysis
OverviewCourse outlineCourse materialsPrerequisitesMethod & grading

Overview

The course will cover basic python methods for data analysis: pandas, numpy, scipy, sklearn, along with advanced techniques of their application. Basic integrations of python with external libraries like xgboost, tensorflow, pytorch along with data wrangling and some hyperparameter optimization methods will be also included. Jupyter notebook usage and tricks will be also given as an organic part of the course. At the end of module, everyone is expected to be ready to come up with a simple data wrangling system.

Learning highlights

  • Learning basic Python methods for data analysis.
  • Use of Python’s external libraries.
  • Learn how to effectively use the Jupyter notebook.

Course outline

15 classes

Dive into the details of the course and get a sense of what each class will cover.
Monday
Tuesday
Wednesday
Thursday
Friday
Monday
1

Session 1

Jupyter notebook intro, tricks, hotkeys, platforms.

Python methods integrated with jupyter.

Tuesday
2

Session 2

Data manipulation. Pandas. Reading .csv files, Titanic dataset. Hands-on manipulating the datasets.

Wednesday
3

Session 3

Data visualization. Matplotlib, seaborn, bokeh and plotly.

Thursday
4

Session 4

Sklearn. Basic ML concepts: cross validation, fit/predict. Preparing prediction for Titanic dataset.

Friday
5

Session 5

Checking homework assignments on data manipulation and visualization. Sklearn and numpy methods.

Monday
6

Session 6

Data versioning. Working with enterprise data analysis systems, pitfalls and techniques.

Tuesday
7

Session 7

Weekly homework revisiting. Performing data analysis at the scale.

Wednesday
8

Session 8

Start working on general projects. Open discussion about what can, and what cannot be done with Python in seven days. Very basic custdev.

Thursday
9

Session 9

Storing custom approximators as custom sklearn classes. Sklearn pipelines.

Friday
10

Session 10

Working with textual, visual and audio data in Python.

Monday
11

Session 11

Heavy dataset processing with Python instruments, Cython.

Tuesday
12

Session 12

Integrating via python. Google docs, chatbots, interface prototyping, data annotation, scrapping, no-code platforms

Wednesday
13

Session 13

Heavy dataset processing with Python instruments, Cython.

Thursday
14

Session 14

Consultations on student projects.

Friday
15

Session 15

Finals.

Course materials

Media

Prerequisites

Knowledge of Python on the level of snakify.org is highly recommended.

General interest in statistics and data analysis is also a plus.

Methodology

We will study a set of practical jupyter notebooks, interrupted with 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. Also, there will be a final exam and student project demonstration at the end of the course.

Grading

The final grade will be composed of the following criteria:
60% - Session 5 and session 10 homework + extra points for sending homework before deadline
20% - Exam Results
20% - Final Project Demonstration Score
Maxim Musin

Faculty

Maxim Musin

CEO at rebels.ai

Maxim Musin comes from a background in statistics, advanced multidimensional probability, and random processes. During his career in these fields, he found himself developing skills and gathering experience through working in both academic environments and the private sector. For the last 5 years Maxim is a CEO of for profit AI development laboratory rebels.ai, integrating AI in enterprise and helping startups reach the orbit.

His academic experience ranges from teaching probability and statistics at MSU and MIPT, as a member of the faculty of innovation and high technology, FIHT, which at the time was among the few places worldwide with capabilities for advanced statistics study. During his time there, he produced several notable projects with his students, particularly in regards to the stochastic convergence of neural networks. His course on applied modern statistics became mandatory for the data analysis division of the FIHT MIPT Masters.

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Apply for this course

Snap up your chance to enroll before all spaces fill up.

Python for Data Scientists

by Maxim Musin

Total hours

45 Hours

Dates

Nov 28 - Dec 16, 2022

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.