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2022-05-12T08:39:47Z

DevelopmentData Science

230+ Exercises - Python for Data Science - NumPy + Pandas

Double pack! Improve your Python programming and data science skills and solve over 230 exercises in NumPy and Pandas!
Rating: 4.8 out of 54.8 (6 ratings)
4,225 students
Created by Paweł Krakowiak
Last updated 6/2022
English
English

What you'll learn

  • solve over 230 exercises in NumPy and Pandas
  • deal with real programming problems in data science
  • work with documentation and Stack Overflow
  • guaranteed instructor support

Requirements

  • completion of all courses in the Python Developer learning path
  • basic knowledge of NumPy and Pandas
  • I have courses which can assist in obtaining all the necessary skills for this course

Description

Welcome to the 230+ Exercises - Python for Data Science - NumPy + Pandas course where you can test your Python programming skills in data science, specifically in NumPy and Pandas.


Some numpy topics you will find in the exercises:

  • working with numpy arrays

  • generating numpy arrays

  • generating numpy arrays with random values

  • iterating through arrays

  • dealing with missing values

  • working with matrices

  • reading/writing files

  • joining arrays

  • reshaping arrays

  • computing basic array statistics

  • sorting arrays

  • filtering arrays

  • image as an array

  • linear algebra

  • matrix multiplication

  • determinant of the matrix

  • eigenvalues and eignevectors

  • inverse matrix

  • shuffling arrays

  • working with polynomials

  • working with dates

  • working with strings in array

  • solving systems of equations


Some pandas topics you will find in the exercises:

  • working with Series

  • working with DatetimeIndex

  • working with DataFrames

  • reading/writing files

  • working with different data types in DataFrames

  • working with indexes

  • working with missing values

  • filtering data

  • sorting data

  • grouping data

  • mapping columns

  • computing correlation

  • concatenating DataFrames

  • calculating cumulative statistics

  • working with duplicate values

  • preparing data to machine learning models

  • dummy encoding

  • working with csv and json filles

  • merging DataFrames

  • pivot tables


The course is designed for people who have basic knowledge in Python, NumPy and Pandas. It consists of 230 exercises with solutions.

This is a great test for people who are learning the Python language and data science and are looking for new challenges. Exercises are also a good test before the interview. Many popular topics were covered in this course.


If you're wondering if it's worth taking a step towards Python, don't hesitate any longer and take the challenge today.

Who this course is for:

  • everyone who wants to learn by doing
  • everyone who wants to improve Python programming skills
  • everyone who wants to improve data science skills
  • everyone who wants to prepare for an interview

Instructor

Paweł Krakowiak
Python Developer/Data Scientist/Stockbroker
Paweł Krakowiak
  • 4.6 Instructor Rating
  • 4,081 Reviews
  • 171,143 Students
  • 69 Courses

EN

Python Developer/Data Scientist/Stockbroker

Founder at e-smartdata[.]org.

Big fan of new technologies!

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

Graduate of MA studies in Financial and Actuarial Mathematics at the Faculty of Mathematics and Computer Science at the University of Lodz. Former PhD student at the faculty of mathematics.

Stockbroker license holder (no 3073).

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

PL

Data Scientist, Securities Broker

Założyciel platformy e-smartdata[.]org

Miłośnik nowych technologii, szczególnie w obszarze sztucznej inteligencji, języka Python 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 (nr 3073).

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 język Python, sztuczna inteligencja, web development oraz rynki finansowe.

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