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.

Course Model

The project development is based on the development framework of Innovation Engineering, which includes the story development, execution while learning, innovation behaviors, and leadership.

References

Innovation Engineering Textbook. You can check here for the latest table of contents/reading assignments.

Navigator tool to reinforce inductive learning in the project

Low Tech Demo template deck

Example of the Berkeley course description and policies

Sample Syllabus

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 Write down 3 ideas a project, 1-3 sentences each. Due within one week. Submit here and shared spreadsheet to that everyone can see the concepts submitted. (5 points). Second spreadsheet: each student submits their technical and broad skills, interests, and what you can bring to a team. Lead Mentor: In class, explain team formation concepts. Collaborators communicate project concepts.	THE PROBLEM and Caviar Case (5 points)
2	100A and 100B: Prediction and Linear Regression Part I and II	P02: Team Formation 1 Collaborators/mentors communicate additional project concepts. Bring the three ideas to the class and be ready to discuss. Volunteer: Allow 10-15 people to pitch project ideas for 1 min each. 1 extra participation point per pitch. (When in person, use the remaining time to mingle, share ideas.) All students are either project proposers or project joiners. Mentors are project proposers. Use interviews to decide who is on which team. After interviews, teams may be formed. Use a different form (to be provided) to submit your project name, team members, contact information, and keywords that describe your project. Your project concept may still change.	THE SOLUTION EXPLAINED IN 12 PRINCIPLES and THE PROCESS (5 points) Ref: 12 Principles video
3	110: NumPy A, Arrays 120: Pandas A	P03: Team Formation 2 and Navigator In class, demonstrate Navigator During class, open the Innovation Navigator, make a copy, fill in the title page, and contact information for each team member, share the document with team members, mentors, instructors and GSIs. (5 points) In class, start brainstorming for 30 min. Continue over the next week for open-ended brainstorming, but then converge to a few key requirements for the project. As needed, collect data by talking to potential users of the project. The team should come up with a multiple project variations and then select one for implementation. Summarize your brainstorming in 1 page. Where did you start and end, what did you decide? Each person on team turn in your brainstorm and convergence summary by next week. (5 points)
4	130A: Visualization A 140: Logistic Regression	P04: Low Tech Demo Create a "low tech demo". This is a 5-slide presentation with no code. It can be up to 10 slides at most. Insert these slides into your Innovation Navigator just after the title slide. The team should make one presentation and record it as a video of approximately 5 min. Turn in a link to the slides and the video (which can be embedded on one of the slides) within 1 week. (10 points)	Suggested: A STEP-BY-STEP GUIDE TO INNOVATION PROJECTS
5	160: Predictive Classification, Titanic Example	P05: Starting Agile Implementation and Navigator Some teams to present live as case examples. Participation credits for live presentation (5 min) and Q/A (5 min). (2 point extra per person if volunteer) Fill the next 2 pages of the Innovation Navigator which are 1) initial conditions and 2) one of the execution/reflection pages. Send link when finished, within 1 week. (5 points) Create your first Minimal Viable Demo. Be ready to demonstrate it by next week.	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 Improve your first Minimal Viable Demo. Be ready to demonstrate it. Min Viable Demonstration (10 points)
7	200: Correlation Any module from '03: Data Handling' to aid the project	P07: Project Progress 1 Agile implementation. Turn in a summary of what is working, what is not working yet, and general reflection in less than one page 5 points. (When requested, demonstration updates are all 5 points)	Suggested: DEVELOPING A BETTER STORY (5 points)
8	410: Intro to Tensor FlowOption	P08: Project Progress 2 Agile implementation. Turn in a summary of what is working, what is not working yet, and general reflection in less than one page 5 points. (When requested, demonstration updates are all 5 points)	INNOVATION LEADERSHIP (5 points)
9	500: NLP Text Processing	P09: Project Progress 3 and Navigator Record project progress on Innovation Navigator with a new execution/reflection sheet. (5 points). Agile implementation. Be prepared to demonstrate what you have. (When requested, demonstration updates are all 5 points)
10	Track Option: 420: Neural Networks or 510: NLP Feature Engineering & Text Representation	P10: Project Progress 4 Agile implementation. Turn in a summary of what is working, what is not working yet, and general reflection in less than one page 5 points. Be prepared to demonstrate what you have. (When requested, demonstration updates are all 5 points)	Suggested: CULTURE, MINDSET, AND BEHAVIOR (5 points)
11	Track Option: 430: CNN or 520: NLP Learning Models	P11: Final Demo Preparation and Navigator Prepare for final demo. Agile implementation. Record project progress on Innovation Navigator with a new execution/reflection sheet. (5 points). Switch to checklist of remaining action items to get project ready. (5 points)
12	Options for an elective module	P12: Final Demo Preparation Prepare for the final demo. Agile implementation. Switch to the checklist of remaining action items to get project ready. (5 points)
13	Options for an elective module	P13: Final Demo Preparation Prepare for the final demo. Agile implementation. Switch to the checklist of remaining action items to get project ready. (5 points)
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 3^rd 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.