210+ Exercises - Python Standard Libraries - from A to Z
What you'll learn
- solve over 210 exercises in Python with standard libraries
- deal with real programming problems
- work with documentation
- guaranteed instructor support
Requirements
- completed course 200+ Exercises - Programming in Python - from A to Z
- basic knowledge of Python
Description
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RECOMMENDED LEARNING PATH
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PYTHON DEVELOPER:
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
150+ Exercises - Data Structures in Python - Hands-On
100+ Exercises - Advanced Python Programming
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
110+ Exercises - Python + SQL (sqlite3) - SQLite Databases
250+ Questions - Job Interview - Python Developer
SQL DEVELOPER:
SQL Bootcamp - Hands-On Exercises - SQLite - Part I
SQL Bootcamp - Hands-On Exercises - SQLite - Part II
110+ Exercises - Python + SQL (sqlite3) - SQLite Databases
200+ Questions - Job Interview - SQL Developer
JOB INTERVIEW SERIES:
250+ Questions - Job Interview - Python Developer
200+ Questions - Job Interview - SQL Developer
200+ Questions - Job Interview - Software Developer - Git
200+ Questions - Job Interview - Data Scientist
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COURSE DESCRIPTION
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210+ Exercises - Python Standard Libraries - from A to Z
Welcome to the course 210+ Exercises - Python Standard Libraries - from A to Z where you can test your Python programming skills.
Knowing the built-in packages and modules significantly improves our development skills. We will use, for example:
datetime
os
sys
copy
string
re
collections
pprint
pathlib
random
math
statistics
numbers
decimal
fractions
itertools
functools
pickle
zipfile
csv
json
urllib.request
timeit
The course is designed for people who have basic knowledge in Python. It consists of 210 exercises with solutions. The course is focused on practical learning.
This is a great test for people who are learning the Python language 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 their Python programming skills
- everyone who wants to prepare for an interview
Instructor
![Paweł Krakowiak](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.7 Instructor Rating
- 3,115 Reviews
- 131,116 Students
- 52 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.