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2021-03-17 18:41:22
30-Day Money-Back Guarantee
Development Data Science Python

250+ Exercises - Data Science Bootcamp in Python

Improve your Python programming skills and solve over 250 data science exercises!
Rating: 4.3 out of 54.3 (11 ratings)
5,075 students
Created by Paweł Krakowiak
Last updated 4/2021
English
English
30-Day Money-Back Guarantee

What you'll learn

  • solve over 250 exercises in data science in Python
  • deal with real programming problems
  • deal with real problems in data science
  • work with libraries numpy, pandas, seaborn, plotly, scikit-learn, opencv, tensorflow
  • work with documentation
  • guaranteed instructor support

Course content

31 sections • 64 lectures • 37m total length

  • Info
    00:12
  • Requirements
    00:14
  • Preview02:55
  • Preview03:47
  • Preview09:57
  • Preview04:07
  • Preview02:56
  • Preview04:40

  • A few words from the author
    00:20
  • Tip
    01:02

  • Intro
    00:04

  • Exercises
    00:07
  • Exercises + Solutions
    00:07

  • Exercises
    00:07
  • Exercises + Solutions
    00:07

  • Exercises
    00:07
  • Exercises + Solutions
    00:07

  • Exercises
    00:07
  • Exercises + Solutions
    00:07

  • Exercises
    00:07
  • Exercises + Solutions
    00:07

  • Exercises
    00:07
  • Exercises + Solutions
    00:07

  • Exercises
    00:07
  • Exercises + Solutions
    00:07

Requirements

  • completed course '200+ Exercises - Programming in Python - from A to Z'
  • completed course '210+ Exercises - Python Standard Libraries - from A to Z'
  • completed course '150+ Exercises - Object Oriented Programming in Python - OOP'
  • completed course '100+ Exercises - Python Programming - Data Science - NumPy'
  • completed course '100+ Exercises - Python Programming - Data Science - Pandas'
  • completed course '100+ Exercises - Python - Data Science - scikit-learn'

Description

------------------------------------------------------------------------------

RECOMMENDED LEARNING PATH

------------------------------------------------------------------------------

  • 200+ Exercises - Programming in Python - from A to Z

  • 210+ Exercises - Python Standard Libraries - from A to Z

  • 150+ Exercises - Object Oriented Programming in Python - OOP

  • 100+ Exercises - Unit tests in Python - unittest framework

  • 100+ Exercises - Python Programming - Data Science - NumPy

  • 100+ Exercises - Python Programming - Data Science - Pandas

  • 100+ Exercises - Python - Data Science - scikit-learn

  • 250+ Exercises - Data Science Bootcamp in Python

------------------------------------------------------------------------------

COURSE DESCRIPTION

------------------------------------------------------------------------------

The course consists of 250 exercises (exercises + solutions) in Python with data science. The emphasis is on knowledge of data science libraries such as:

  • numpy

  • pandas

  • seaborn

  • plotly

  • scikit-learn

  • opencv

  • tensorflow

This is a great test for people who are learning the Python language and are looking for new challenges. The course is designed for people who already have basic knowledge in Python and knowledge about data science libraries. Exercises are also a good test before the interview. Many popular questions have been discussed in the course.


Don't hesitate and take the challenge today!

Who this course is for:

  • everyone who wants to learn by doing
  • everyone who wants to improve their programming skills in Python
  • people who are preparing for interviews
  • people interested in data science
  • data scientists
  • data analytics
  • machine learning engineers

Instructor

Paweł Krakowiak
Data Scientist, Securities Broker
Paweł Krakowiak
  • 4.6 Instructor Rating
  • 1,475 Reviews
  • 42,600 Students
  • 37 Courses

EN

Data Scientist/Python Developer/Securities Broker

Founder at e-smartdata[.]org.

A big fan of new technologies, especially in the areas of artificial intelligence, big data and cloud solutions.

A graduate of postgraduate studies at the Polish-Japanese Academy of Information Technology in the field of Computer Science in the Big Data specialization.

A graduate of Master's Degree in Financial and Actuarial Mathematics at the Faculty of Mathematics and Computer Science of the University of Lodz.

Stockbroker license holder with experience in teaching at a university.

Lecturer at the GPW Foundation (technical analysis, behavioral finance and portfolio management).

The main areas of interest are artificial intelligence, machine learning, deep learning and financial markets.

PL

Data Scientist, Securities Broker

Założyciel platformy e-smartdata[.]org

Miłośnik nowych technologii, szczególnie w obszarze sztucznej inteligencji, big data oraz rozwiązań chmurowych.

Absolwent podyplomowych studiów na Polsko-Japońskiej Akademii Technik Komputerowych na kierunku Informatyka, spec. Big Data.

Absolwent studiów magisterskich z matematyki finansowej i aktuarialnej na wydziale Matematyki i Informatyki Uniwersytetu Łódzkiego.

Od 2015 roku posiadacz licencji maklera papierów wartościowych z uprawnieniami do czynności doradztwa inwestycyjnego.

Wykładowca w Fundacji GPW prowadzący szkolenia dla inwestorów z zakresu analizy technicznej, finansów behawioralnych i zasad zarządzania portfelem instrumentów finansowych.

Z doświadczeniem w prowadzeniu zajęć dydaktycznych na wyższej uczelni z przedmiotów związanych z rachunkiem prawdopodobieństwa i statystyką.

Główne obszary zainteresowań to sztuczna inteligencja, uczenie maszynowe, uczenie głębokie i rynki finansowe.

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