Data-X Course Model
Data-X is an advanced project course. The skillset learned in this course can be applied to a broad range of industry sectors and applications. A key part of the course is an open-ended project. The first 4 weeks are used to generate a story and low-tech demo for a real-world project. The remaining 8 weeks are used for an agile sprint which results in a demonstration of working project code by the end of the course.
The project development is based on the development framework of Innovation Engineering, which includes the story development, execution while learning, innovation behaviors, and leadership.
|Session||Lecture Modules||Project Guidelines and Assignments||Readings
Weekly Instructions: Write a ½-page to 1-page maximum reflection and/or critique about which concepts relevant to the project.
|1||010: Introduction Basics
020: Project: Getting Started
030: Installation Instructions
|P01: Project Introduction
||THE PROBLEM and Caviar Case (5 points)|
|2||100A and 100B: Prediction and Linear Regression Part I and II||P02: Team Formation 1
||THE SOLUTION EXPLAINED IN 12 PRINCIPLES and THE PROCESS
Ref: 12 Principles video
|3||110: NumPy A, Arrays
120: Pandas A
|P03: Team Formation 2 and Navigator
|4||130A: Visualization A
140: Logistic Regression
|P04: Low Tech Demo
||Suggested: A STEP-BY-STEP GUIDE TO INNOVATION PROJECTS|
|5||160: Predictive Classification, Titanic Example||P05: Starting Agile Implementation and Navigator
||Case Study: “Starting an Agile Implementation for Technical Delivery” in Appendix. Turn in 1 per person, within 1 week. (5 points)|
|6||170: ML Overview
180: Cross-Validation and Regularization
|P06: Minimum Viable Demo
Any module from '03: Data Handling' to aid the project
|P07: Project Progress 1
||Suggested: DEVELOPING A BETTER STORY (5 points)|
|8||410: Intro to Tensor FlowOption||P08: Project Progress 2
||INNOVATION LEADERSHIP (5 points)|
|9||500: NLP Text Processing||P09: Project Progress 3 and Navigator
|10||Track Option: 420: Neural Networks or 510: NLP Feature Engineering & Text Representation||P10: Project Progress 4
||Suggested: CULTURE, MINDSET, AND BEHAVIOR (5 points)|
Track Option: 430: CNN or 520: NLP Learning Models
|P11: Final Demo Preparation and Navigator
|12||Options for an elective module||P12: Final Demo Preparation
|13||Options for an elective module||P13: Final Demo Preparation
|14||Final Demo Preparation||P14: Final Demo|
Project Final Guidelines
Be prepared to showcase your work during reading week.
The Team will have to turn in the following:
- Slides and demo (50 points) graded on
- 20 points effort
- 20 points quality in work,
- 10 points creativity or project or presentation style
- Code via github link (10 points for code check)
- The slides should include a reflection of what happened over the journey project and what the team learned. (10 points for reflection)
- A news write up in 3rd 1-2 paragraphs that tell the news story of what your team created. (5 points)
Individuals should plan to turn in:
- 360 assessment of contribution of each team member including yourself.
- Course feedback form and reflection
- Sign up for Facebook/Linkedin alumni group.
Advisors and Mentor Directory for Data-X
The Data-X course and project brings together students, technical experts, start-up companies, and executives. Each brings a different perspective to data, algorithms, and scale. See the People page for more information.