Disclosure: when you buy through links on our site, we may earn an affiliate commission.

# 100+ Exercises – Python – Data Science – NumPy – 2022

4.9
4.9/5
(134 reviews)
42,474 students

## 9.4

CourseMarks Score®

10.0

Freshness

8.8

Feedback

8.8

Content

Platform: Udemy
Video: 45m
Language: English
Next start: On Demand

## Description

100+ Exercises – Python Programming – Data Science – NumPy
Welcome to the 100+ Exercises – Python Programming – Data Science – NumPy course, where you can test your Python programming skills in data science, specifically in NumPy.

Some 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
•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

This course is designed for people who have basic knowledge in Python and NumPy package. It consists of 100 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.

Stack Overflow Developer Survey
According to the Stack Overflow Developer Survey 2021, Python is the most wanted programming language with NumPy being the second most used tool in the “Other Frameworks and Libraries” category. Python passed SQL to become our third most popular technology. Python is the language developers want to work with most if they aren’t already doing so.

#### You will learn

✓ solve over 100 exercises in NumPy
✓ 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
• completion of all courses in the Data Scientist learning path
• basic knowledge of NumPy library
• I have courses which can assist in obtaining all the necessary skills for this course

#### 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
• data scientists / data analytics / machine learning engineers

#### Paweł Krakowiak

Python Developer/Data Scientist/Stockbroker
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.
Lecturer at the GPW Foundation (technical analysis, behavioral finance and portfolio management).
PL
Data Scientist, Securities Broker
Założyciel platformy e-smartdata[.]orgMiłośnik 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.
Browse all courses by on Coursemarks.
Platform: Udemy
Video: 45m
Language: English
Next start: On Demand