Einstein said "In theory, theory and
practice are the same. In practice, they
are not." This course is about the
practice of predictive analytics, and is taught in partnership with a company
with years of consulting experience with telecoms (predicting churn), large
retailers (predicting holiday sales), online merchants (microtargeting), and
more
This is a fully practical and applied course -
you should have some familiarity with predictive modeling before taking
it. In part 1 of this course, you will
get some hands-on experience with real-world data and the issues of problem
definition and data prep. In Part 2 you
will take a defined dataset, develop models, assess them, and submit your best
model. Your instructor will serve as
your personal guide in this effort.
Mr. Mohan Singh will present his course
“Applied Predictive Analytics, in partnership with CrowdANALYTIX” online at
Statistics.com. For more details please visit at Applied Predictive Analytics, inpartnership with CrowdANALYTIX.
Aim of Course:
The goal of this course is to teach users (who
have basic knowledge of R programming, predictive analytics and statistics) to
apply machine learning techniques in real world case studies. This course
provides hands on approach, presenting the opportunity to participate in a
private educational competition hosted by CrowdANALYTIX.
Business Case Study: We will study
data from the "daily deals" industry (consisting of websites like
Groupon, Living Social etc. which source local deals to offer each day). The
daily deals industry is emerging and highly competitive. The goal will be to
predict the revenue from each offering using the given data.
Course Walkthrough: Each week,
participants will be given a set of exercises and instructions to work on the
raw data or processed data (details below). Users will apply their
statistical/machine learning knowledge, along with their business
understanding, to solve the problems and interpret the modeling results for the
given business objective. The course will follow an iterative approach for
problem solving, in which users are required to submit modeling responses
multiple times.
Who Should Take
This Course:
Business analysts, R users, SAS users,
statistical analysts who want to learn to implement and apply machine learning
techniques to solve predictive analytics problems in a real world business
case. Data mining analysts who want extend their knowledge to include machine
learning techniques for data modelling.
Course Program:
WEEK 1: Business Case Study,
Introduction and Data Pre-processing
- Course
and business case study introduction
- Data
Cleaning, pre-processing & data visualization
- Understanding
business objective to be modelled based on the case study
Assignment: To read data in R and
perform simple statistical measures. Perform data cleaning, data pre-processing
and data manipulation as required by the case study problem.
WEEK 2: Classification Problem, Data Sampling, Feature Selection and Model Building
- Introduction
to machine learning
- Supervised classification problem (Machine learning
packages in R)
- Perform
feature selection and processing on given data
- Model
building based on classification techniques
Assignment: To perform simple exercises for
machine learning packages in R. Converting raw data into features or creating
new features, if needed for the modelling objective.
WEEK 3: Evaluation Metrics, Scoring Model Output, Leaderboard Prediction
- Build
machine learning model like decision trees, ensemble modelling etc.
- Evaluation
metric like confusion matrix, RMSE etc.
- Leaderboard
scoring for peer-2-peer feedback
Assignment: Perform basic to intermediate
level machine learning model for the problem. These scores will be reflected on
the private contest leaderboard for all participants.
WEEK 4: Visualization of Modeling Output and Analysis of Features & Model for Business Case Study
- Model building and Leaderboard updates on a daily basis visualize the output of the model
- Interpret modelling results for case study objective
Assignment: Final week assignment is based
on understanding the various model outputs for the business objective.
The instructor, Mr. Mohan Singh, is a
senior data scientist at CrowdANALYTIX with extensive research experience in
healthcare and imaging. He has taught
data mining & computer science at University College Dublin and UC,
Irvine. Participants can ask questions
and exchange comments with Mr. Singh via a private discussion board throughout
the period.
You will be able to ask questions
and exchange comments with the instructors via a private discussion board
throughout the course. The courses take place online at
statistics.com in a series of 4 weekly lessons and assignments, and require
about 15 hours/week. Participate at your own convenience; there are no
set times when you must be online. You have the flexibility to work a bit every
day, if that is your preference, or concentrate your work in just a couple of
days.
We, the Center for eLearning and Training
(C-eLT), Pune, partner with Statistics.com and offer these courses to Indian
participants at special prices payable in INR.
Call: 020 6680 0300 / 322
Websites:
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