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Python Regression Analysis: Statistics & Machine Learning

Learn Complete Hands-On Regression Analysis for Practical Statistical Modelling and Machine Learning in Python
4.4
4.4/5
(190 reviews)
1,841 students
Created by

9.3

Classbaze Grade®

9.5

Freshness

8.4

Popularity

9.5

Material

Learn Complete Hands-On Regression Analysis for Practical Statistical Modelling and Machine Learning in Python
Platform: Udemy
Video: 6h 19m
Language: English
Next start: On Demand

Best Machine Learning classes:

Classbaze Rating

Classbaze Grade®

9.3 / 10

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

Freshness

9.5 / 10
This course was last updated on 11/2021.

Course content can become outdated quite quickly.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.

Popularity

8.4 / 10
We analyzed factors such as the rating (4.4/5) 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.

Material

9.5 / 10
Video Score: 8.5 / 10
The course includes 6h 19m 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 5 hours 48 minutes of 749 Machine Learning courses on Udemy.
Detail Score: 10.0 / 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:

2 articles.
2 resources.
0 exercise.
0 test.

In this page

About the course

HERE IS WHY YOU SHOULD ENROLL IN THIS COURSE:
Regression analysis is one of the central aspects of both statistical and machine learning based analysis.
This course will teach you regression analysis for both statistical data analysis and machine learning in Python in a practical hands-on manner. 
It explores the relevant concepts  in a practical manner from basic to expert level.
This course can help you achieve better grades, give you new analysis tools for your academic career, implement your knowledge in a work setting & make business forecasting related decisions…All of this while exploring the wisdom of an Oxford and Cambridge educated researcher.
Most statistics and machine learning courses and books only touch upon the basic aspects of regression analysis.
This does not teach the students about all the different regression analysis techniques they can apply to their own data in both academic and business setting, resulting in inaccurate modelling.
My course is Different; It will help you go all the way from implementing and inferring simple OLS (ordinary least square) regression models to dealing with issues of multicollinearity in regression to machine learning based regression models. 

LEARN FROM AN EXPERT DATA SCIENTIST:
My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate. I also just recently finished a PhD at Cambridge University (Tropical Ecology and Conservation).
I have +5 years of experience in analyzing real life data from different sources  using data science related techniques and producing publications for international peer reviewed journals.
This course is based on my years of regression modelling experience and implementing different regression models on real life data.  
THIS COURSE WILL HELP YOU BECOME A REGRESSION ANALYSIS EXPERT:
Here is what we’ll be covering inside the course:
•Get started with Python and Anaconda. Install these on your system, learn to load packages and read in different types of data in Python
•Carry out data cleaning Python
•Implement ordinary least square (OLS) regression in Python and learn how to interpret the results.
•Evaluate regression model accuracy
•Implement generalized linear models (GLMs) such as logistic regression using Python
•Use machine learning based regression techniques for predictive modelling 
•Work with tree-based machine learning models
•Implement machine learning methods such as random forest regression and gradient boosting machine regression for improved regression prediction accuracy.
•& Carry out model selection
THIS IS A PRACTICAL GUIDE TO REGRESSION ANALYSIS WITH REAL LIFE DATA:
This course is your one shot way of acquiring the knowledge of statistical and machine learning analysis that I acquired from the rigorous training received at two of the best universities in the world, perusal of numerous books and publishing statistically rich papers in renowned international journal like PLOS One.
Specifically the course will:
   (a) Take you from a basic level of statistical knowledge to performing some of the most common advanced regression analysis based techniques.
   (b) Equip you to use Python for performing the different statistical and machine learning data analysis tasks. 
   (c) Introduce some of the most important statistical and machine learning concepts to you in a practical manner so you can apply these concepts for practical data analysis and interpretation.
   (d) You will get a strong background in some of the most important statistical and machine learning concepts for regression analysis.
   (e) You will be able to decide which regression analysis techniques are best suited to answer your research questions and applicable to your data and interpret the results.
It is a practical, hands-on course, i.e. we will spend some time dealing with some of the theoretical concepts related to both statistical and machine learning regression analysis…
However, majority of the course will focus on implementing different  techniques on real data and interpret the results. After each video you will learn a new concept or technique which you may apply to your own projects. 
JOIN THE COURSE NOW!

What can you learn from this course?

✓ Harness The Power Of Anaconda/iPython For Practical Data Science
✓ Read In Data Into The Python Environment From Different Sources
✓ Implement Classical Statistical Regression Modelling Techniques Such As Linear Regression In Python
✓ Implement Machine Learning Based Regression Modelling Techniques Such As Random Forests & kNN For Predictive Modelling
✓ Neural Network & Deep Learning Based Regression

What you need to start the course?

• Be Able To Operate & Install Software On A Computer
• Have Prior Exposure To Common Machine Learning Terms Such As Regression Modelling & Supervised Learning

Who is this course is made for?

• Students Who Had Prior exposure to Python programming (Not Essential)
• Students Wanting To Master The Anaconda iPython Environment For Data Science & Scientific Computations
• Students Wishing To Learn The Implementation Of Supervised Learning (Regression) On Real Data Using Python
• Students Looking To Get Started With Artificial Neural Networks & Deep Learning

Are there coupons or discounts for Python Regression Analysis: Statistics & Machine Learning ? What is the current price?

The course costs $17.99. And currently there is a 82% discount on the original price of the course, which was $99.99. So you save $82 if you enroll the course now.
The average price is $13.6 of 749 Machine Learning courses. So this course is 32% more expensive than the average Machine Learning course on Udemy.

Will I be refunded if I'm not satisfied with the Python Regression Analysis: Statistics & Machine Learning course?

YES, Python Regression Analysis: Statistics & 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 financial aid for this course?

Currently we could not find a scholarship for the Python Regression Analysis: Statistics & Machine Learning course, but there is a $82 discount from the original price ($99.99). So the current price is just $17.99.

Who will teach this course? Can I trust Minerva Singh?

Minerva Singh has created 46 courses that got 16,390 reviews which are generally positive. Minerva Singh has taught 82,987 students and received a 4.5 average review out of 16,390 reviews. Depending on the information available, we think that Minerva Singh is an instructor that you can trust.
Bestselling Instructor & Data Scientist(Cambridge Uni)
I completed a PhD (University of Cambridge, UK) in 2017 where I focussed on implementing data science techniques for quantifying the impact of forest loss on tropical ecosystems. I hold an MPhil (School of Geography and Environment) and an MSc (Department of Engineering) from Oxford University. I have more than 10 year’s experience in conducting academic research (published in high level peer-reviewed international scientific journals such as PLOS One) and advising both non-governmental and industry stakeholders in data science, deep learning and earth observation (EO) related topics. I have a strong track record in implementing machine learning, data visualization, spatial data analysis, deep learning and natural language processing tasks using both R and Python. In addition to being educated at the best universities in the world, I have honed my statistical and data analysis skills through many MOOCs, including The Analytics Edge (R based statistics and machine learning course offered by EdX), Statistical Learning (R-based Machine Learning course offered by Stanford online) and the IBM Data Science Professional certificate Track. I specialise in a variety of topics ranging from deep learning (Tensorflow, Keras) to machine learning to spatial data analysis (including EO data processing), data visualizations, natural language processing, financial analysis among others. I have acted as a peer reviewer on highly regarded academic journals such as Remote Sensing and given guest lectures on prestigious forums such as Open Data Science Conference (ODSC).
Browse all courses by on Classbaze.

9.3

Classbaze Grade®

9.5

Freshness

8.4

Popularity

9.5

Material

Platform: Udemy
Video: 6h 19m
Language: English
Next start: On Demand

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