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

Improve your machine learning skills and solve over 100 exercises in python, numpy, pandas and scikit-learn!
4.7
4.7/5
(13 reviews)
5,340 students
Created by Paweł Krakowiak

9.2

CourseMarks Score®

9.9

Freshness

8.4

Feedback

8.8

Content

Platform: Udemy
Price: $11.99
Video: 45m
Language: English
Next start: On Demand

Top Python courses:

Detailed Analysis

CourseMarks Score®

9.2 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness Score

9.9 / 10
This course was last updated on 3/2021.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Student Feedback

8.4 / 10
We analyzed factors such as the rating (4.7/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Content Score

8.8 / 10
Video Score: 7.7 / 10
The course includes 45m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 7 hours 24 minutes of 1,300 Python courses on Udemy.
Detail Score: 8.8 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.9 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

106 articles.
0 resource.
102 exercises.
0 test.

Table of contents

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
——————————————————————————
100+ Exercises – Python – Data Science – scikit-learn
Welcome to the course 100+ Exercises – Python – Data Science – scikit-learn, where you can test your Python programming skills in machine learning, specifically in scikit-learn library.
The course is designed for people who have basic knowledge in Python, numpy, pandas and scikit-learn. It consists of over 100 exercises with solutions.
This is a great test for people who are learning the Python language and machine learning and are looking for new challenges. Exercises are also a good test before the interview.
If you’re wondering if it’s worth taking a step towards Python, don’t hesitate any longer and take the challenge today.

Requirements

Requirementscompleted 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 – Num
• Py’completed course ‘100+ Exercises – Python Programming – Data Science – Pandas’basic knowledge of scikit-learn and machine learning concepts

You will learn

✓ solve over 100 exercises in numpy, pandas and scikit-learn
✓ deal with real programming problems in data science
✓ work with documentation and Stack Overflow
✓ guaranteed instructor support

This course is for

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

How much does the 100+ Exercises - Python - Data Science - scikit-learn course cost? Is it worth it?

The course costs $11.99. And currently there is a 40% discount on the original price of the course, which was $19.99. So you save $8 if you enroll the course now.
The average price is $19.0 of 1,300 Python courses. So this course is 37% cheaper than the average Python course on Udemy.

Does the 100+ Exercises - Python - Data Science - scikit-learn course have a money back guarantee or refund policy?

YES, 100+ Exercises – Python – Data Science – scikit-learn has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any SCHOLARSHIPS for this course?

Currently we could not find a scholarship for the 100+ Exercises – Python – Data Science – scikit-learn course, but there is a $8 discount from the original price ($19.99). So the current price is just $11.99.

Who is the instructor? Is Paweł Krakowiak a SCAM or a TRUSTED instructor?

Paweł Krakowiak has created 10 courses that got 141 reviews which are generally positive. Paweł Krakowiak has taught 42663 students and received a 4.2 average review out of 141 reviews. Depending on the information available, Paweł Krakowiak is a TRUSTED instructor.

More info about the instructor, Paweł Krakowiak

Data Scientist, Securities Broker
ENData Scientist/Python Developer/Securities BrokerFounder 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.PLData Scientist, Securities BrokerZałożyciel platformy e-smartdata[.]orgMiłośnik 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.

9.2

CourseMarks Score®

9.9

Freshness

8.4

Feedback

8.8

Content

Platform: Udemy
Price: $11.99
Video: 45m
Language: English
Next start: On Demand

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