Applied AI & Data Analytics
summary
Describes a consulting-style practicum that solves a defined business problem in a 16-week cycle under client NDAs with weekly team and technical reviews, handing over deliverables: code visualizations documentation and using client cloud accounts (AWS Azure or GCP). Claims include concrete wins: 10% of rental listings were fraudulent, predictive model for postsurgical infection, and proactive maintenance for ATMs and airline fleets. Tooling and methods: Python SQL NLP classification models often using XGBoost and 9 of 13 projects on Google Cloud Platform.
AI-written summary · about
chapters (10)
- 0:00MSBA program intro
- 1:04Client partnership model
- 3:41Shaping business problems
- 6:10Projects as consulting
- 8:57AI/analytics project examples
- 10:45Weekly meetings
- 12:08Grading process
- 15:44Practicum partners
- 17:50Tech/tools used
- 20:24Q&A
related talks
29mExploring Tech Career in Data Analytics and Science
16mKey Points and Lessons Learned in AI Projects in Mechanical Engineering
54mGradient ascent for your career
46mThe AI dominated world – skills required for successfully navigating it
25mFrom Zero to AI Hero
18mSmall AI Teams with Huge Impact
26mHow to Break into Business Intelligence & Data Analytics
01h 27mLaunch your career in AI
