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Python Fast Track for Data Science and Machine Learning

A Practical and the Easiest Python, Data Science And Machine Leaning Class for Absolute Beginners
4.1
4.1/5
(6 reviews)
28 students
Created by

9.5

CourseMarks Score®

9.8

Freshness

8.5

Feedback

9.5

Content

Platform: Udemy
Video: 12h 32m
Language: English
Next start: On Demand

Top Python courses:

Detailed Analysis

CourseMarks Score®

9.5 / 10

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

Freshness Score

9.8 / 10
This course was last updated on 4/2021.

Course content can become outdated quite quickly.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

8.5 / 10
We analyzed factors such as the rating (4.1/5) 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

9.5 / 10
Video Score: 9.5 / 10
The course includes 12h 32m 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: 9.5 / 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: 9.5 / 10

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

This course contains:

10 articles.
0 resource.
0 exercise.
0 tests or quizzes.

Table of contents

Description

The course is the easiest training you can get to start your journey as a data scientist. We help you prepare your portfolio by having you do tabular data classifications, image classifications, and more during eight mini-projects. Learning Python, NumPy, pandas, matplotlib, Seaborn, TensorFlow, or PyTorch is good, but working on real projects for data science is essential.
A lot of classes talk about mathematics and advanced statistics, but those things are not easy for an absolute beginner to learn. This course won’t teach you math or statistics. Instead, we’ll guide you through practical applications.
We are not saying math and statistics are not important. It is imperative that you understand those concepts to become a data scientist. But when you first learn how to drive, you don’t need someone to teach you the mechanical details of how your car runs. What you need is someone who can sit next to you and guide you from your home to school or the grocery store. If you get familiar with that, then you will want to go further. In the same way, after you do our projects step-by-step, you will want to know more about the math or statistics behind all that code.
We will start with Python, and then NumPy & pandas for some data manipulation. Then we will learn data visualization, preprocessing, machine learning, and modeling for binary classification with tabular data. Next, we will learn regression and multi-class classification with scikit-learn modules. After that, we’ll learn how to deal with unsupervised learning tasks like image classification, image generation, and so on.

You will learn

✓ Basic syntax in Python and learn how to use it for data analysis.
✓ Practical use of Numpy and pandas, learning how to handle data, especially how to deal with null values, imbalanced data, and so on.
✓ Data visualization techniques with matplotlib and Seaborn as well as other advanced visualization tools.
✓ Pre-processing techniques for binary classification, multi-class classification, and regression.
✓ Scikit-learn basics with supervised and unsupervised algorithms and modules
✓ 8 key hands-on practices for supervised and unsupervised data analytics tasks
✓ Image classification techniques with TensorFlow
✓ Basic concepts and practices for anomaly detection, GANs, and NLP.

Requirements

• No prior experience is required. This course is for absolute beginners, so it might be too easy for someone already familiar with data science and machine learning techniques.
• The only things you need are an internet connection and a Google account since this course will use the Google Colab website, which is free to use. You do not have to install anything. The only things you have to do are (1) download our ipynb notebooks and upload them to your Google Colab account (2) download the data we provide and upload it to your Google Colab account, (3) work on those notebooks, and (4) watch the videos to learn more.

This course is for

• Absolute beginners who are interested in data science or becoming data scientists

How much does the Python Fast Track for Data Science and Machine Learning course cost? Is it worth it?

The course costs $14.99. And currently there is a 83% discount on the original price of the course, which was $89.99. So you save $75 if you enroll the course now.
The average price is $19.0 of 1300 Python courses on Udemy.

Does the Python Fast Track for Data Science and Machine Learning course have a money back guarantee or refund policy?

YES, Python Fast Track for Data Science and Machine Learning 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 Python Fast Track for Data Science and Machine Learning course, but there is a $75 discount from the original price ($89.99). So the current price is just $14.99.

Who is the instructor? Is Fast Campus a SCAM or a TRUSTED instructor?

Fast Campus has created 1 courses that got 6 reviews which are generally positive. Fast Campus has taught 28 students and received a 4.1 average review out of 6 reviews. Depending on the information available, Fast Campus is a TRUSTED instructor.
The number one IT education provider in Korea
Fast Campus is the number one IT education provider in Korea. We have hundreds of courses available on our website including Data Science and programming. More than half a million students have attended our online and offline courses. By choosing Fast Campus, you have found the perfect place to start if you are a novice who wants to become a data scientist. More than one-hundred of our teachers have taught beginners just like you, and this course is the easiest way to start your journey as a data scientist with no math or statistics. You have to learn math and statistics eventually of course, but our experience has taught us that most beginners quit when they start with difficult math and statistics. So start learning with us, and when you need to learn math and advanced statistics, we will guide you through that as well.


9.5

CourseMarks Score®

9.8

Freshness

8.5

Feedback

9.5

Content

Platform: Udemy
Video: 12h 32m
Language: English
Next start: On Demand

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