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Feature Engineering and Data Preparation for Analytics

  • Tuition USD $2,100
  • Reviews star_rate star_rate star_rate star_rate star_half 531 Ratings
  • Course Code DMDP41
  • Duration 3 days
  • Available Formats Classroom
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This course introduces programming techniques to craft and feature engineer meaningful inputs to improve predictive modeling performance. In addition, this course provides strategies to preemptively spot and avoid common pitfalls that compromise the integrity of the data being used to build a predictive model. This course relies heavily on SAS programming techniques to accomplish the desired objectives.

Skills Gained

  • extract data from a relational data table structure
  • define population qualifications and create a target sample
  • use feature engineering techniques to transform transactional data into meaningful inputs into a predictive model
  • transform low-, mid-, and high-cardinality categorical input variables into meaningful predictive modeling inputs
  • use ZIP codes and latitude/longitude points to calculate great-circle distance, driving distance, and estimated driving time
  • use Bayes' theorem to estimate meaningful predictive modeling inputs, impute missing observations, and partition the target sample into training and validation data sets for honest assessment of the predictive model.

Who Can Benefit

  • Analysts, data scientists, and IT professionals looking to craft better inputs to improve predictive modeling performance

Prerequisites

  • This course assumes some experience in both predictive modeling and SAS programming. Before attending this course, you should have
  • exposure to DATA step programming equivalent to SAS(R) Programming I: Essentials
  • exposure to querying data in PROC SQL and building and deploying a predictive model
  • familiarity with the SAS macro language is helpful but not required
  • exposure to programming in SQL or the SQL procedure
  • familiarity with the analytical process of building predictive models and scoring new data.

Course Details

Extracting Relevant Data

  • data difficulties
  • assessing available data
  • accessing available data
  • drawing a representative target sample
  • drawing an uncontaminated input sample

Transforming Transaction and Event Data

  • advantages and disadvantages of transactions data
  • common transaction structures
  • defining the time horizon
  • fixed and variable time horizon methods
  • implementing common transaction transformations

Using Non-Numeric Data

  • definitions and difficulties of non-numeric data
  • miscoding and multicoding detection
  • controlling degrees of freedom
  • geocoding

Managing Data Pathologies

  • explore input variable distributions
  • detect data anomalies
  • create custom exploratory tools for candidate input variables
  • missing value imputation
  • data partitioning
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How do I enroll?

A comprehensive listing of ExitCertified courses can be found here. You can register directly for the required course/location when you select "register". If you have any questions or prefer to speak with an ExitCertified education consultant directly, please submit your query here. A representative will contact you shortly.

How do I pay for a class?

You can pay at the time of registration using credit card (Mastercard/Visa/American Express) cheque or PO.

What if I have training credits?

ExitCertified honors all savings programs from the partners we work with. ExitCertified also offers training credits across multiple partners through our FLEX Account.

When does class start/end?

Classes begin promptly at 9:00 am, and typically end at 5:00 pm.

Lunchtime?

Lunch is normally an hour long and begins at noon. Coffee, tea, hot chocolate and juice are available all day in the kitchen. Fruit, muffins and bagels are served each morning. There are numerous restaurants near each of our centers, and some popular ones are indicated on the Area Map in the Student Welcome Handbooks - these can be picked up in the lobby or requested from one of our ExitCertified staff.

How can someone reach me during class?

If someone should need to contact you while you are in class, please have them call the center telephone number and leave a message with the receptionist.

What languages are used to deliver training?

Most courses are conducted in English, unless otherwise specified. Some courses will have the word "FRENCH" marked in red beside the scheduled date(s) indicating the language of instruction.

The training is very helpful. The lab is very well written and easy to follow. The instructor is very knowledgeable.

Thank you for training on AWS development. Course was good and encouraging but labs need to be improved and provide more information and ask students to more work than provide solutions.

Very well organized course and labs were clear. Instructor Sean Mohseni was an excellent. Will highly recommend this course/vendor and instructor to others.

The training was excellent which is what I expecting for Amazon software training.

The class is a good review of the services available in AWS.

In my mind. Myles Brown is an excellent instructor. His teaching approach agrees with me. No discernible stress about public speaking. Very engaging.

Enroll in the course offerings? Will enroll at the drop of a hat if approved. To ask mgmt to approve enrolment is another matter for me. Nothing to do with your company. Just a statement of fact.

Maybe a course on Google and MS Azure like this will be nice. If you have alternative options to mgmt, it is more likely that they shall have to choose one. Allow us to enroll.

0 options available

There are currently no scheduled dates for this course. If you are interested in this course, request a course date with the links above. We can also contact you when the course is scheduled in your area.

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