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Learning Python Data Analysis

Analyze and understand your data with the power and simplicity of Python.
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8.7

CourseMarks Score®

9.5

Freshness

N/A

Feedback

7.5

Content

Platform: Simpliv Learning
Price: $149.99
Video: 5h55m
Language: English
Next start: On Demand

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Detailed Analysis

CourseMarks Score®

8.7 / 10

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

Freshness Score

9.5 / 10
This course was last updated on 11/2020.

Course content can become outdated quite quickly.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

We analyzed factors such as the rating and the ratio between the number of reviews and the number of students, which is a great signal of student commitment. If a course does not yet have a rating, we exclude Feedback Score from the overall CourseMarks Score.

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

7.5 / 10
Video Score: 7.6 / 10
The course includes 5h55m 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 Simpliv Learning.
Detail Score: 9.4 / 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: 5.5 / 10

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

This course contains:

0 article.
0 resource.
0 exercise.
0 test.

Table of contents

Description

Analyze and understand your data with the power and simplicity of Python.

Python features numerous numerical and mathematical toolkits such as: Numpy, Scipy, Scikit learn and SciKit, all used for data analysis and machine learning. With the aid of all of these, Python has become the language of choice for data scientists for data analysis, visualization, and machine learning.

This video aims to teach Python developers how to perform data analysis with the language by taking advantage of the core data science libraries in the Python ecosystem. The learning objective for viewers is to understand how to locate, manipulate, and analyse data with Python, with the ability to analyse large and small sets of data using libraries such as Numpy, pandas, IPython and SciPy.

This is a two part series. The first series is focused on getting and manipulation sizeable amounts of data using modern techniques. The second series is focused on advanced analysis of the data to include modern machine learning techniques.

About the Author

Ben spent3 years working as a software engineer and team leader doing graphics processing, desktop application development, and scientific facility simulation using a mixture of C++ and python. Which, sparking a passion for software development and developmental programming has lead him to exploring state of the art projects in Natural Language Processing, Facial Detection/Recognition, and Machine Learning.

You will learn

Advanced and recommend software engineering development practices
✓ How to scrape the twitter stream to collect real time data
✓ Smart storing of data using advanced abstractions and Object-Oriented programming
✓ Easy and practical data manipulation techniques for dealing with large volumes of data
✓ Natural Language Processing tools, special designed for working with sentences and other forms of textual data
✓ Predictive methods that can forecast and predict future trends based on current data
✓ Data analytics techniques to tease out unseen data relationships
✓ Dashboard application development to help share and monitor your progress/analysis

Requirements

• This video appeals to Python developers who want to be capable of performing core data analysis tasks with Python’s libraries and tools, including data retrieval, cleaning, manipulation, visualization and storage. Those who want to handle large sets of structured and unstructured data, and discovering and delivering insight with various forms of analysis will find this course spot-on!

This course is for

• Anyone interested in learning more about python, data science, or data visualizations.
• Anyone interested about the rapidly expanding world of data science!

How much does the Learning Python Data Analysis course cost? Is it worth it?

The course costs $149.99. And currently there is a 80% discount on the original price of the course, which was $749.99. So you save $600 if you enroll the course now.
The average price is $19.0 of 1,300 Python courses. So this course is -689% cheaper than the average Python course on Simpliv Learning.

Does the Learning Python Data Analysis course have a money back guarantee or refund policy?

YES, Learning Python Data Analysis has a 20-day money back guarantee. The 20-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 Learning Python Data Analysis course, but there is a $600 discount from the original price ($749.99). So the current price is just $149.99.

Who is the instructor? Is Packt Publishing a SCAM or a TRUSTED instructor?

Packt Publishing has created 2059 courses that got 58,562 reviews which are generally positive. Packt Publishing has taught 402,947 students and received a 4.0 average review out of 58,562 reviews. Depending on the information available, Packt Publishing is a TRUSTED instructor.

8.7

CourseMarks Score®

9.5

Freshness

N/A

Feedback

7.5

Content

Platform: Simpliv Learning
Price: $149.99
Video: 5h55m
Language: English
Next start: On Demand

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