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Big Data Manipulation in R Exercises

June 9, 2017
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Big Data Manipulation in R Exercises

Some times it is necessary to download really big csv files to deliver some analysis. When you hit file sizes in Gigabytes it is useful to use R instead of spreadsheets. This exercise teaches us to manipulate this kind of files. Answers to the exercises are available here. Exercise 1 Create a directory canada immigration/Work/Income Related exercise sets: Forecasting: ARIMAX...

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Canada Labour Market: Future Perspectives

June 1, 2017
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Canada Labour Market: Future Perspectives

For anyone looking for job opportunities, it is nice to have an idea how the job market will perform in the future for your chosen career or industry. Many countries have open data sets that offer this kind of data. In these exercises we will use R to analyze the future perspective of Canadian labour Related exercise sets:Reshape 2...

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Canada Immigration: Where to settle in? Exercises

May 26, 2017
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Canada Immigration: Where to settle in? Exercises

Many people around the globe would like to immigrate to Canada as a Skilled Worker. These candidates must prove language proficiency in French and English, at least 2 years of working experience after graduation, and more. But, many immigrants that arrive in canada face unemployment rates sometimes even higher than in their original countries. So, Related exercise sets:Cross Tabulation...

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Call Center Productivity Boosting with ML Exercises

May 14, 2017
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Call Center Productivity Boosting with ML Exercises

The telephone had rung when Jean was watching her favorite TV Show. It was a call center selling newspaper, so she got really upset. This situation is not unpleasant just for Jean. The call center is losing too! By calling a person the will never buy whatever is been sold, the call center is wasting Related exercise sets:Intermediate Tree...

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Data Science for Operational Excellence (Part-5)

May 3, 2017
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Data Science for Operational Excellence (Part-5)

Operations need to have demand forecasts in order to establish optimal resource allocation policies. But, when we make predictions the only thing that we assure is the occurrence of prediction errors. Fortunately, there is no need to be 100% accurate to succeed, we just need to perform better than our competitors. In this exercise we Related exercise sets:Forecasting: Exponential...

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Data Science for Operational Excellence (Part-4)

April 27, 2017
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Data Science for Operational Excellence (Part-4)

Suppose your friend is a restaurant chain owner (only 3 units) facing some competitors challenges related to low price, lets call it a price war. Inside his business he knows that there’s no much cost to be cut. But, he thinks that, maybe if he tries harder to find better supplier with low freight and Related exercise sets:Lets Begin...

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Data Science for Operational Excellence (Part-3)

April 24, 2017
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Data Science for Operational Excellence (Part-3)

Optimized transportation planning is a task usually left to the firm’s logistic department. However, it is often difficult to visualize, specially if there are many points involved in the logistic network. R and its packages can help solving this issue. Our goal here is to expand logistics networking visualization. In order to do that, we Related exercise sets:Descriptive Analytics-Part...

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Data Science for Operational Excellence Exercises (Part-2)

April 14, 2017
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Data Science for Operational Excellence Exercises (Part-2)

Network problems are everywhere. We can easily find instances in logistics, telecom, project mangement, among others. In order to attack these problems using linear programming we need to go beyond assign and transportation problems that we saw in part I. Our goal here is to expand the problems we can solve using lpsove and igraph Related exercise sets:Data Hacking...

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Data Science for Operational Excellence (Part-1)

April 6, 2017
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Data Science for Operational Excellence (Part-1)

 R has many powerful libraries to handle operations research. This exercise tries to demonstrate a few basic functionality of R while dealing with linear programming. Linear programming is a technique for the optimization of a linear objective function, subject to linear equality and linear inequality constraints. The lpsolve package in R provides a set Related exercise sets:Data science...

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