Project Management

case study:

anakysing a data base ( preferred mckinsey) for a project from a specific industry. breaking the project into building blocks and predicting the success of the project via share performance through deep machine learning algorythems.

The basic concept is to take a case study of 2-3 data bases of large scale projects (semi con industry is top priority) and perform analysis in regards to project goals (we can break down one by one what are the

one of the key analysis points will be to predict a success of a project (what is success...? )or not based on the key decision points.

Total of the work should be 35 pages. 2-3 case studies including graphs, etc. 1 month total for the report which should be in academic format. no need for conclusion abstract, etc.

1) When you say semicon industry, do you mean industries such as Samsung electronics, Intel, Toshiba etc.? - Yes

(2) If so, what do you have in mind to measure success of the industry? For example using revenue/profit generated? Amount of sales made etc? - Yes. i would like to check revenue/profit per project progress - for example specific technology Vs project progress. i would like to know in advance the chosen companies to avoid conflicts.

check (3) What type of mathematical tool you have in mind? - I would like to analyze the data using Random Forest or GBT and extrapolate from that share performance prediction for future projects.

1 month duration. total work should include 35 pages with the following pages ratio:

5 will be data presentation of the data (no need for background, etc)

5 will be modeling

20 data analysis

5 conclusion and discussion

method of analysis should be based on Random forest regression trees (or GBT). work should include graphs, tables and modeling.

the main idea is to investigate success of a project (need to explain what is success) as a number of decision points during the project life.