【2022年】十大迴歸分析課程熱門排行推薦與優惠精選!

 

本文章推薦「Deep Learning Prerequisites: Linear Regression in Python」、「Deep Learning Foundation : Linear Regression and Statistics」、「Complete Linear Regression Analysis in Python」等相關迴歸分析線上課程,讓您滿足學習的慾望。

你是否想透過線上學習得到更多的技能,增加自己的技能樹?現在是學生的您,透過線上學習可以將更多專業知識用在課業學習上更加強所學。還是您是朝九晚五的上班族,尋找可以為工作上帶來更上一層樓的技能?或您是因為興趣或想培養其他興趣?

線上課程不受地理位置影響,不受時間早晚影響,老師來自世界各地,也不受學習程度影響的特色,讓您無時無刻想學都可以,想多看幾次增加熟悉度也可以。不同領域的老師將針對不同主題滿足您的學習目的,推薦的課程項目會陸續更新,絕對提供您最熱門人氣高的線上課程。

  • 線上課程老師來自於全球,文章推薦的熱門課程除了繁中課程以外還會有機會看到簡中和英文課程,可以針對自己喜好挑選。
  • 呈現的價錢會因為一些活動而有折扣,但折扣有可能一段時間後結束而調整回原價,最終價錢煩請到課程頁面進行確認。





迴歸分析課程總覽

為了節省您的時間,本列表整理每個課程精要,讓您可以快速瀏覽這文章所提供的課程是否是您所需要的,點選您有興趣課程的「課程名稱」或「課程圖示」可以進一步跳到文章所屬課程的介紹區塊瞭解更多資訊。

課程名稱Complete Linear Regression Analysis in PythonML for Business Managers: Build Regression model in R StudioLinear Regression and Logistic Regression in PythonDeep Learning Prerequisites: Linear Regression in PythonDeep Learning Foundation : Linear Regression and StatisticsRegression Analysis / Data Analytics in RegressionRegression Analysis for Statistics & Machine Learning in RMachine Learning Regression Masterclass in PythonLinear Regression, GLMs and GAMs with RThe STATA OMNIBUS: Regression and Modelling with STATA
課程圖示
1

Complete Linear Regression Analysis in Python

2

ML for Business Managers: Build Regression model in R Studio

3

Linear Regression and Logistic Regression in Python

4

Deep Learning Prerequisites: Linear Regression in Python

5

Deep Learning Foundation : Linear Regression and Statistics

6

Regression Analysis / Data Analytics in Regression

7

Regression Analysis for Statistics & Machine Learning in R

8

Machine Learning Regression Masterclass in Python

9

Linear Regression, GLMs and GAMs with R

10

The STATA OMNIBUS: Regression and Modelling with STATA

課程原價NT$ 590NT$ 590NT$ 590NT$ 2,790NT$ 590NT$ 2,690NT$ 2,690NT$ 2,790NT$ 2,790NT$ 1,790
課程售價NT$ 470NT$ 470NT$ 470NT$ 470NT$ 470NT$ 470NT$ 470NT$ 470NT$ 490NT$ 470
課程評價(人數)4.5 分(1,077 個評分)4.5 分(242 個評分)4.6 分(203 個評分)4.7 分(4,918 個評分)4.2 分(1,353 個評分)4.3 分(796 個評分)4.5 分(491 個評分)4.5 分(422 個評分)4.0 分(200 個評分)4.3 分(262 個評分)
課程時長7.5 小時6.5 小時8.5 小時6.5 小時6.5 小時2 小時7.5 小時10.5 小時8 小時19.5 小時
學生人數129,773 人55,463 人39,021 人27,503 人9,173 人4,327 人4,008 人3,966 人1,929 人1,542 人
課程特色Linear Regression in Python| Simple Regression, Multiple Regression, Ridge Regression, Lasso and subset selection alsoSimple Regression & Multiple Regression| must-know for Machine Learning & Econometrics | Linear Regression in R studioBuild predictive ML models with no coding or maths background. Linear Regression and Logistic Regression for beginnersData science, machine learning, and artificial intelligence in Python for students and professionalsLearn linear regression from scratch, Statistics, R-Squared, Python, Gradient descent, Deep Learning, Machine LearningGain Important and Highly Marketable Skills in Regression Analysis – Tame the Regression Beast Today!Learn Complete Hands-On Regression Analysis for Practical Statistical Modelling and Machine Learning in RBuild 8+ Practical Projects and Master Machine Learning Regression Techniques Using Python, Scikit Learn and KerasHow to extend linear regression to specify and estimate generalized linear models and additive models.4 COURSES IN 1! Includes introduction to Linear and Non-Linear Regression, Regression Modelling and STATA. Updated Freq.
連結UdemyUdemyUdemyUdemyUdemyUdemyUdemyUdemyUdemyUdemy



迴歸分析課程介紹

推薦的課程以倒序的方式呈現,越往下查看會看到越熱門的,期望您能找到滿意的學習主題!

10

The STATA OMNIBUS: Regression and Modelling with STATA

4 COURSES IN 1! Includes introduction to Linear and Non-Linear Regression, Regression Modelling and STATA. Updated Freq.
NT$ 1,790
NT$ 470

點擊看Udemy

課程老師F. Buscha
課程評價4.3 分(262 個評分)
課程時長19.5 小時
學生人數1,542 人

課程介紹

Make sure to check out my twitter feed for promo codes and other updates (easystats3).

4 COURSES IN ONE!

Learn everything you need to know about linear regression, non-linear regression, regression modelling and STATA in one package.

Linear and No

瞭解更多細節

哪些人適合這堂課?

  • Students working with data and quants
  • Anyone wanting to work with Stata
  • Anyone who wants to understand regression easily
  • Business managers using quantitative evidence
  • Those in the Economics/Politics/Social Sciences

學習目標

  • The theory behind linear and non-linear regression analysis.
  • To be at ease with regression terminology.
  • The assumptions and requirements of Ordinary Least Squares (OLS) regression.
  • To comfortably interpret and analyse regression output from Ordinary Least Squares.
  • To learn and understand how Logit and Probit models work.
  • To learn tips and tricks around Non-Linear Regression analysis.
  • Practical examples in Stata
  • Tips for building regression models
  • An introduction to Stata
  • Data manipulation in Stata
  • Data visualisation in Stata
  • Data analysis in Stata
  • Regression modelling in Stata
  • Simulation in Stata
  • Survival analysis
  • Count Data analysis
  • Categorical Data analysis
  • Panel Data Analysis
  • Epidemiology
  • Instrumental Variables
  • Power Analysis
  • Difference-in-Differences

關注這課程的人也購買了這些…

9

Linear Regression, GLMs and GAMs with R

How to extend linear regression to specify and estimate generalized linear models and additive models.
NT$ 2,790
NT$ 490

點擊看Udemy

課程老師Geoffrey Hubona, Ph.D.
課程評價4.0 分(200 個評分)
課程時長8 小時
學生人數1,929 人

課程介紹

Linear Regression, GLMs and GAMs with R demonstrates how to use R to extend the basic assumptions and constraints of linear regression to specify, model, and interpret the results of generalized linear (GLMs) and generalized additive (GAMs) models. T

瞭解更多細節

哪些人適合這堂課?

  • This course would be useful for anyone involved with linear modeling estimation, including graduate students and/or working professionals in quantitative modeling and data analysis.
  • The focus, and majority of content, of this course is on generalized additive modeling. Anyone who wishes to learn how to specify, estimate and interpret GAMs would especially benefit from this course.

學習目標

  • Understand the assumptions of ordinary least squares (OLS) linear regression.
  • Specify, estimate and interpret linear (regression) models using R.
  • Understand how the assumptions of OLS regression are modified (relaxed) in order to specify, estimate and interpret generalized linear models (GLMs).
  • Specify, estimate and interpret GLMs using R.
  • Understand the mechanics and limitations of specifying, estimating and interpreting generalized additive models (GAMs).

關注這課程的人也購買了這些…



8

Machine Learning Regression Masterclass in Python

Build 8+ Practical Projects and Master Machine Learning Regression Techniques Using Python, Scikit Learn and Keras
NT$ 2,790
NT$ 470

點擊看Udemy

課程老師Dr. Ryan Ahmed, Ph.D., MBA
課程評價4.5 分(422 個評分)
課程時長10.5 小時
學生人數3,966 人

課程介紹

Artificial Intelligence (AI) revolution is here! The technology is progressing at a massive scale and is being widely adopted in the Healthcare, defense, banking, gaming, transportation and robotics industries.

Machine Learning is a subfield of Arti

瞭解更多細節

哪些人適合這堂課?

  • Data Scientists who want to apply their knowledge on Real World Case Studies
  • Machine Learning Enthusiasts who look to add more projects to their Portfolio

學習目標

  • Master Python programming and Scikit learn as applied to machine learning regression
  • Understand the underlying theory behind simple and multiple linear regression techniques
  • Apply simple linear regression techniques to predict product sales volume and vehicle fuel economy
  • Apply multiple linear regression to predict stock prices and Universities acceptance rate
  • Cover the basics and underlying theory of polynomial regression
  • Apply polynomial regression to predict employees’ salary and commodity prices
  • Understand the theory behind logistic regression
  • Apply logistic regression to predict the probability that customer will purchase a product on Amazon using customer features
  • Understand the underlying theory and mathematics behind Artificial Neural Networks
  • Learn how to train network weights and biases and select the proper transfer functions
  • Train Artificial Neural Networks (ANNs) using back propagation and gradient descent methods
  • Optimize ANNs hyper parameters such as number of hidden layers and neurons to enhance network performance
  • Apply ANNs to predict house prices given parameters such as area, number of rooms..etc
  • Assess the performance of trained Machine learning models using KPI (Key Performance indicators) such as Mean Absolute error, Mean squared Error, and Root Mean Squared Error intuition, R-Squared intuition, Adjusted R-Squared and F-Test
  • Understand the underlying theory and intuition behind Lasso and Ridge regression techniques
  • Sample real-world, practical projects

關注這課程的人也購買了這些…

7

Regression Analysis for Statistics & Machine Learning in R

Learn Complete Hands-On Regression Analysis for Practical Statistical Modelling and Machine Learning in R
NT$ 2,690
NT$ 470

點擊看Udemy

課程老師Minerva Singh
課程評價4.5 分(491 個評分)
課程時長7.5 小時
學生人數4,008 人

課程介紹

            With so many R Statistics & Machine Learning courses around, why  enroll for this ?

Regression analysis is one of the central aspects of both statistical and machine learning based analysis. This course will teach you regression analysi

瞭解更多細節

哪些人適合這堂課?

  • People who have completed my course on Statistical Modeling for Data Analysis in R (or equivalent experience)
  • People with basic knowledge of R based statistical modelling
  • People with knowledge of linear regression modelling
  • People wanting to extend their knowledge of regression modelling for solving real world problems.
  • People wanting to learn how to apply machine learning based regression models using R
  • Undergraduates and postgraduates seeking to deepen their knowledge of statistical and machine learning analysis
  • Academic researchers seeking to learn new techniques for data analysis
  • Business data analysts who wish to use regression modelling for predictive analysis

學習目標

  • Implement and infer Ordinary Least Square (OLS) regression using R
  • Apply statistical and machine learning based regression models to deals with problems such as multicollinearity
  • Carry out variable selection and assess model accuracy using techniques like cross-validation
  • Implement and infer Generalized Linear Models (GLMS), including using logistic regression as a binary classifier
  • Build machine learning based regression models and test their robustness in R
  • Learn when and how machine learning models should be applied
  • Compare different different machine learning algorithms for regression modelling

關注這課程的人也購買了這些…



6

Regression Analysis / Data Analytics in Regression

Gain Important and Highly Marketable Skills in Regression Analysis – Tame the Regression Beast Today!
NT$ 2,690
NT$ 470

點擊看Udemy

課程老師Quantitative Specialists
課程評價4.3 分(796 個評分)
課程時長2 小時
學生人數4,327 人

課程介紹

November, 2019.

Get marketable and highly sought after skills in this course while substantially increasing your knowledge of data analytics in regression. All course videos created and narrated by an award winning instructor and textbook author of

瞭解更多細節

哪些人適合這堂課?

  • Anyone interested in learning more about regression analysis.
  • This course is not for those looking for a general introduction to statistics course. For this we recommend taking a look at our descriptive statistics or inferential statistics courses. (This course specializes in regression analysis.)
  • Those looking to increase their knowledge of regression.

學習目標

  • Understand when to use simple, multiple, and hierarchical regression
  • Understand the meaning of R-Square and the role it plays in regression
  • Assess a regression model for statistical significance, including both the overall model and the individual predictors
  • Effectively utilize regression models in your own work and be able to critically evaluate the work of others
  • Understand predicted values and their role in the overall quality of a regression model
  • Understand hierarchical regression, including its purpose and when it should be used
  • Use regression to assess the relative value of competing predictors
  • Make business decisions about the best models to maximize profits while minimizing risk
  • Critically evaluate regression models used by others
  • Learn how to conduct correlation and regression using both IBM SPSS and Microsoft Excel

關注這課程的人也購買了這些…

5

Deep Learning Foundation : Linear Regression and Statistics

Learn linear regression from scratch, Statistics, R-Squared, Python, Gradient descent, Deep Learning, Machine Learning
NT$ 590
NT$ 470

點擊看Udemy

課程老師Jay Bhatt
課程評價4.2 分(1,353 個評分)
課程時長6.5 小時
學生人數9,173 人

課程介紹

Hi Everyone welcome to new course which is created to sharpen your linear regression and statistical basics. linear regression is starting point for a data science this course focus is on making your foundation strong for deep learning and machine le

瞭解更多細節

哪些人適合這堂課?

  • Python developers curious about data science
  • data science and machine leaning engineers

學習目標

  • Mathematics behind R-Squared, Linear Regression,VIF and more!
  • Deep understating of Gradient descent and Optimization
  • Program your own version of a linear regression model in Python
  • Derive and solve a linear regression model, and implement it appropriately to data science problems
  • Statistical background of Linear regression and Assumptions
  • Assumptions of linear regression hypothesis testing
  • Writing codes for T-Test, Z-Test and Chi-Squared Test in python

關注這課程的人也購買了這些…



4

Deep Learning Prerequisites: Linear Regression in Python

Data science, machine learning, and artificial intelligence in Python for students and professionals
NT$ 2,790
NT$ 470

點擊看Udemy

課程老師Lazy Programmer Inc.
課程評價4.7 分(4,918 個評分)
課程時長6.5 小時
學生人數27,503 人

課程介紹

This course teaches you about one popular technique used in machine learning, data science and statistics: linear regression. We cover the theory from the ground up: derivation of the solution, and applications to real-world problems. We show you how

瞭解更多細節

哪些人適合這堂課?

  • People who are interested in data science, machine learning, statistics and artificial intelligence
  • People new to data science who would like an easy introduction to the topic
  • People who wish to advance their career by getting into one of technology’s trending fields, data science
  • Self-taught programmers who want to improve their computer science theoretical skills
  • Analytics experts who want to learn the theoretical basis behind one of statistics’ most-used algorithms

學習目標

  • Derive and solve a linear regression model, and apply it appropriately to data science problems
  • Program your own version of a linear regression model in Python

關注這課程的人也購買了這些…

3

Linear Regression and Logistic Regression in Python

Build predictive ML models with no coding or maths background. Linear Regression and Logistic Regression for beginners
NT$ 590
NT$ 470

點擊看Udemy

課程老師Start-Tech Academy
課程評價4.6 分(203 個評分)
課程時長8.5 小時
學生人數39,021 人

課程介紹

You’re looking for a complete Linear Regression and Logistic Regression course that teaches you everything you need to create a Linear or Logistic Regression model in Python, right?

You’ve found the right Linear Regression course!

After completing

瞭解更多細節

哪些人適合這堂課?

  • People pursuing a career in data science
  • Working Professionals beginning their Data journey
  • Statisticians needing more practical experience
  • Anyone curious to master Linear and Logistic Regression from beginner to advanced level in a short span of time

學習目標

  • Learn how to solve real life problem using the Linear and Logistic Regression technique
  • Preliminary analysis of data using Univariate and Bivariate analysis before running regression analysis
  • Understand how to interpret the result of Linear and Logistic Regression model and translate them into actionable insight
  • Indepth knowledge of data collection and data preprocessing for Linear and Logistic Regression problem
  • Basic statistics using Numpy library in Python
  • Data representation using Seaborn library in Python
  • Linear Regression technique of Machine Learning using Scikit Learn and Statsmodel libraries of Python

關注這課程的人也購買了這些…



2

ML for Business Managers: Build Regression model in R Studio

Simple Regression & Multiple Regression| must-know for Machine Learning & Econometrics | Linear Regression in R studio
NT$ 590
NT$ 470

點擊看Udemy

課程老師Start-Tech Academy
課程評價4.5 分(242 個評分)
課程時長6.5 小時
學生人數55,463 人

課程介紹

You’re looking for a complete Linear Regression course that teaches you everything you need to create a Linear Regression model in R, right?

You’ve found the right Linear Regression course!

After completing this course you will be able to:

· Ident

瞭解更多細節

哪些人適合這堂課?

  • People pursuing a career in data science
  • Working Professionals beginning their Data journey
  • Statisticians needing more practical experience
  • Anyone curious to master Linear Regression from beginner to advanced in short span of time

學習目標

  • Learn how to solve real life problem using the Linear Regression technique
  • Preliminary analysis of data using Univariate and Bivariate analysis before running Linear regression
  • Predict future outcomes basis past data by implementing Simplest Machine Learning algorithm
  • Understand how to interpret the result of Linear Regression model and translate them into actionable insight
  • Understanding of basics of statistics and concepts of Machine Learning
  • Indepth knowledge of data collection and data preprocessing for Machine Learning Linear Regression problem
  • Learn advanced variations of OLS method of Linear Regression
  • Course contains a end-to-end DIY project to implement your learnings from the lectures
  • How to convert business problem into a Machine learning Linear Regression problem
  • How to do basic statistical operations in R
  • Advanced Linear regression techniques using GLMNET package of R
  • Graphically representing data in R before and after analysis

關注這課程的人也購買了這些…

1

Complete Linear Regression Analysis in Python

Linear Regression in Python| Simple Regression, Multiple Regression, Ridge Regression, Lasso and subset selection also
NT$ 590
NT$ 470

點擊看Udemy

課程老師Start-Tech Academy
課程評價4.5 分(1,077 個評分)
課程時長7.5 小時
學生人數129,773 人

課程介紹

You’re looking for a complete Linear Regression course that teaches you everything you need to create a Linear Regression model in Python, right?

You’ve found the right Linear Regression course!

After completing this course you will be able to:

Id

瞭解更多細節

哪些人適合這堂課?

  • People pursuing a career in data science
  • Working Professionals beginning their Data journey
  • Statisticians needing more practical experience
  • Anyone curious to master Linear Regression from beginner to Advanced in short span of time

學習目標

  • Learn how to solve real life problem using the Linear Regression technique
  • Preliminary analysis of data using Univariate and Bivariate analysis before running Linear regression
  • Predict future outcomes basis past data by implementing Simplest Machine Learning algorithm
  • Understand how to interpret the result of Linear Regression model and translate them into actionable insight
  • Understanding of basics of statistics and concepts of Machine Learning
  • Indepth knowledge of data collection and data preprocessing for Machine Learning Linear Regression problem
  • Learn advanced variations of OLS method of Linear Regression
  • Course contains a end-to-end DIY project to implement your learnings from the lectures
  • How to convert business problem into a Machine learning Linear Regression problem
  • Basic statistics using Numpy library in Python
  • Data representation using Seaborn library in Python
  • Linear Regression technique of Machine Learning using Scikit Learn and Statsmodel libraries of Python

關注這課程的人也購買了這些…



迴歸分析課程總覽

看完了一連串課程的介紹後,你是否還想要再一次進行課程總比較呢?

課程名稱Complete Linear Regression Analysis in PythonML for Business Managers: Build Regression model in R StudioLinear Regression and Logistic Regression in PythonDeep Learning Prerequisites: Linear Regression in PythonDeep Learning Foundation : Linear Regression and StatisticsRegression Analysis / Data Analytics in RegressionRegression Analysis for Statistics & Machine Learning in RMachine Learning Regression Masterclass in PythonLinear Regression, GLMs and GAMs with RThe STATA OMNIBUS: Regression and Modelling with STATA
課程圖示
1

Complete Linear Regression Analysis in Python

2

ML for Business Managers: Build Regression model in R Studio

3

Linear Regression and Logistic Regression in Python

4

Deep Learning Prerequisites: Linear Regression in Python

5

Deep Learning Foundation : Linear Regression and Statistics

6

Regression Analysis / Data Analytics in Regression

7

Regression Analysis for Statistics & Machine Learning in R

8

Machine Learning Regression Masterclass in Python

9

Linear Regression, GLMs and GAMs with R

10

The STATA OMNIBUS: Regression and Modelling with STATA

課程原價NT$ 590NT$ 590NT$ 590NT$ 2,790NT$ 590NT$ 2,690NT$ 2,690NT$ 2,790NT$ 2,790NT$ 1,790
課程售價NT$ 470NT$ 470NT$ 470NT$ 470NT$ 470NT$ 470NT$ 470NT$ 470NT$ 490NT$ 470
課程評價(人數)4.5 分(1,077 個評分)4.5 分(242 個評分)4.6 分(203 個評分)4.7 分(4,918 個評分)4.2 分(1,353 個評分)4.3 分(796 個評分)4.5 分(491 個評分)4.5 分(422 個評分)4.0 分(200 個評分)4.3 分(262 個評分)
課程時長7.5 小時6.5 小時8.5 小時6.5 小時6.5 小時2 小時7.5 小時10.5 小時8 小時19.5 小時
學生人數129,773 人55,463 人39,021 人27,503 人9,173 人4,327 人4,008 人3,966 人1,929 人1,542 人
課程特色Linear Regression in Python| Simple Regression, Multiple Regression, Ridge Regression, Lasso and subset selection alsoSimple Regression & Multiple Regression| must-know for Machine Learning & Econometrics | Linear Regression in R studioBuild predictive ML models with no coding or maths background. Linear Regression and Logistic Regression for beginnersData science, machine learning, and artificial intelligence in Python for students and professionalsLearn linear regression from scratch, Statistics, R-Squared, Python, Gradient descent, Deep Learning, Machine LearningGain Important and Highly Marketable Skills in Regression Analysis – Tame the Regression Beast Today!Learn Complete Hands-On Regression Analysis for Practical Statistical Modelling and Machine Learning in RBuild 8+ Practical Projects and Master Machine Learning Regression Techniques Using Python, Scikit Learn and KerasHow to extend linear regression to specify and estimate generalized linear models and additive models.4 COURSES IN 1! Includes introduction to Linear and Non-Linear Regression, Regression Modelling and STATA. Updated Freq.
連結UdemyUdemyUdemyUdemyUdemyUdemyUdemyUdemyUdemyUdemy



從老師查找更多課程

以上推薦的課程還沒挑到自己有興趣的嗎?
還是您有熱衷某個老師開的課程呢?
本頁除了提供迴歸分析的課程以外,也列出這些課程所屬的老師的主要資訊頁,您可以從下列選單中了解更多相關介紹或看他們開的其他課程,期望您最終能找到自己想學習的項目。



【2022年】十大迴歸分析課程熱門排行推薦與優惠精選!

參考其他經濟學線上課程

除了本文介紹的課程種類以外,想要瞭解經濟學領域還有哪些不同類型的課程值得一探究竟嗎?讓您可以從不同面向更紮實的學習,點擊參考以下其他熱門主題文章。絕對提供您最優惠人氣滿檔的課程,歡迎繼續延伸閱讀。


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