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Tara-Su edited this page Apr 16, 2023 · 4 revisions

Welcome to the AI-Program-Home wiki!

Foundational level

Intermediate level

Advance level

The goal is to help students understand how real-world AI/ML efforts are developed. The significant steps and challenges. The Advance level (Industry Success Bootcamp) is organized into product and project delivery formats. The students are held accountable to drive and deliver the results. The lead instructor is considered the accountable executive (AE), who is the major stakeholder from the company side. The program instructors are the product/project sponsors who lead the teams to deliver the results.

Differentiator:

  1. Coaching from high-level executives and experts with extensive industry experience. Networking with high-potential peers and previous star students.
  2. End-to-end development of products starting from the ideation stage to the business delivery provides learning and experiences that can’t be gained in school and regular project study.
  3. Learn solid knowledge from the multiple job families in AI/ML domain: Data science, Product manager, Project manager, and UX designer.
  4. Preparation not only for job interviews but real-world success from early career to executive level.
  5. Build an online profile with clear business and technical outcomes with NFT badges from the program, if complete projects with high quality.

Challenges:

  1. You are responsible for your own success with the program instructor’s support.
  2. You are deliverable will be reviewed with critical feedback as in the real world.
  3. You are expected to come up with your own ideas, and collect and process your own data, just like you will be doing many times in your future career as a data scientist.

Success - Earn an NFT badge through the delivery of all of the below milestones:

  1. Product problem statement
  2. Product solution design
  3. Product technical solution design
  4. Project roadmap
  5. Project prototype
  6. Project summary and final report
  7. Project presentation and delivery
  8. Github documentation
  9. Final review and retrospective (preparation for job interview)

Project topics:

  1. Meet fresh object recognition
  2. Blockchain free-topic project (Definer, or self-selected projects)

Elective： Depending on the student’s level, we may organize real-world consulting work or additional self-selected project work.

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