[#Udemy 100% Off] Connect the Dots: Linear and Logistic #Regression

About This Course

 Published 2/2017  English

Course Description

Taught by a Stanford-educated, ex-Googler and an IIT, IIM - educated ex-Flipkart lead analyst. This team has decades of practical experience in quant trading, analytics and e-commerce. 

This course will teach you how to build robust linear models and do logistic regression in Excel, R and Python.

Let’s parse that.

Robust linear models : Linear Regression is a powerful method for quantifying the cause and effect relationships that affect different phenomena in the world around us. This course will teach you how to build robust linear models that will stand up to scrutiny when you apply them to real world situations. 

Logistic regression: Logistic regression has many cool applications : analyzing consequences of past events, allocating resources, solving binary classification problems using machine learning and so on. This course will help you understand the intuition behind logistic regression and how to solve it using cookie-cutter techniques. 

Excel, R and Python :  Put what you've learnt into practice. Leverage these powerful analytical tools to build models for stock returns. 

What's covered?

Simple Regression : 

• Method of least squares, Explaining variance, Forecasting an outcome
• Residuals, assumptions about residuals 
• Implement simple regression in Excel, R and Python
• Interpret regression results and avoid common pitfalls

Multiple Regression : 

• Implement Multiple regression in Excel, R and Python
• Introduce a categorical variable

Logistic Regression : 

• Applications of Logistic Regression, the link to Linear Regression and Machine Learning
• Solving logistic regression using Maximum Likelihood Estimation and Linear Regression
• Extending Binomial Logistic Regression to Multinomial Logistic Regression
• Implement Logistic regression to build a model stock price movements in Excel, R and Python

Talk to us!

• Mail us about anything - anything! - and we will always reply :-)

What are the requirements?

• No statistics background required. Everything is built up from basic math
• The models are implemented in Excel, R and Python. Install these environments to follow along with the demos

What am I going to get from this course?

• Build robust linear models that stand up to scrutiny in Excel, R and Python
• Use simple and multiple regression to explain variance
• Use simple and multiple regression to predict an outcome
• Intepret the results of a regression
• Understand the risks involved in regression and avoid common pitfalls

Who is the target audience?

• Yep! Data analysts who want to move from summarizing data to explaining and prediction
• Yep! Folks aspiring to be data scientists
• Yep! Any business professionals who want to apply Linear regression to solve relevant problems

About Mustapha

I am online instructor at Udemy. My passions are: Mobile and Web Development, Entrepreneurship and Management. You can read my full biography on My Udemy Page. Feel free to follow me social media to know more about me and the topics and courses I'm teaching.

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