Information Technology

Python Instructor

Project Description:

Work Statement

We are looking for Consutant to deliver Machine learning (Python) training described below.

Loction: Cleveland, OH.

Background

The course shall provide training on Machine Learning. Machine Learning is a type of data analysis technology that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Data from a variety of potential sources (such as applications, sensors, networks, and devices) is fed to the Machine Learning system, which uses that data to build its own logic and to solve a problem or derive some insight.

Prerequisite:
The vendor (teachers) must be well versed in Machine Learning and using Python to build, evaluate, and use Machine Learning models. The vendor must have experience providing courses using a flipped learning model.

Objectives:
Upon completion of the course, students shall be able to:
• Understand supervised and unsupervised learning methods of Machine Learning.
• Create models using different Machine Learning methods using Python.
• Understand situations best suited for learningmethods.
• Understand pitfalls of Machine Learning and best practices for model selection.
• Knowledge of best practices/strategies for using Python to build, evaluate and use Machine Learning models for problem solving.

Specifications

Teachers must be U.S. citizens or permanent residents.
Course should be modeled after flipped-learning courses. Time between in-person sessions should be dedicated to students working on reading or viewing materials and on
assignments. In-person sessions should focus on reviewing solutions to assignments. Minimum of three teachers for in-person sessions. A minimum of one teacher must meet the requirement of having extensive experience and knowledge in topics covered in the statement of work. Extensive experience is defined as:

• Experience with conducting flipped learning classesfor engineers, scientists, and business personnel
• In-depth knowledge and understanding of the course content
• Experience with teaching people with no prior knowledge of machine learning
• Knowledge in topics covered in statement of work and experience with providing training to Government engineers, scientists, and business personnel.

Three to four in-person sessions at NASA Glenn Research Center are required. Inperson sessions should focus on reviewing course assignments and assigned reading
and viewing materials.

Minimum 24 hours total for in-person sessions.

Two to three weeks in between in-person sessions.

Course must use Python 3.7.x and strongly prefer tools and libraries commonly used for machine learning.

The teacher with extensive experience needs to be remotely available for questions in between in-person sessions. The teacher should be available for a minimum of 4 hours per week between the hours of 10 a.m. and 3 p.m. Eastern time.

Course work per topic should require no more than 4 hours per week per participant. Course work is to be completed before each in-person session.

Course materials must include lessons, problems, assignments and solutions.

Course must provide hands-on practice with examples that are of interest to GRC.

Period of Performance:

The course must be taught between the dates September 1, 2019 through December 13, 2019.

If you are interested please send us your resume, hourly rate, and three references.

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