Preliminary Skills Evaluation for Student Success

NOTE: Students & Instructors are encouraged to read & review our AFAQs . Scope : Data Analysis, Mining, and Visualization, Machine Learning, & Python Programming Math modelling of partial data to regress variable output (s) as a function of inputs Validate math model with rest of the non-leveraged data in the DB Estimate probability of variable output (s) based on relevant variable inputs

Right to Disconnect Solution For Public and Private Sector Corporations

Notes: Students & Instructors are encouraged to read & review our AFAQs . Please review student incentives available, upon successful Project completion. Details of Kiosk Model : Benchmark RTD Industry Best Practice from Australia State status of RTD Bill as of Date in State of CA Define, Identify & Quantify Gaps for Private & Public Sectors Using Data Devise Algorithms based on Operational Excellence to Overcome Gaps on RTD Simulate Algorithm for Public & Private Sector Environments on Productivity Losses Design, Develop & Test OSSS Algorithm to Suite OSSS Platform Engagement OSSS Platform Developed & Tested For Robustness in Public & Private Sectors OSSS Platform Deployment Planning for Seamless RTD Transition End Game: Payoff Model RTD Bill Passage

AI Rendered Tax Return Filing Process Excellence

- Charting the As-Is Process Map of the entire tax filing from Docuentation compilation through refund receipt and/or payments to IRS incuding extension filings. - Charting a "To-Be" Process Map to achieve Charter Goals and Objectives - Illustrate the User Design and Requirements based on wireframe for Mobile and Web Applications - Quantifying the relationship between all those input parameters to the Output (Refund or Payment) - Developing Algorithm that applies to any year, individual based on their prior data (for a given category of fining) - Demonstrating a methodology using technology to leverage the Algorithm and populate form to arrive at a projected return and/or a payment Filing for refund and/or payment

Predictive Analytics For VFA Related Wellness

NOTE: Students & Instructors are encouraged to read & review our AFAQs . Scope: Our goal is to extract established quantitative impact of excessive Visceral Fat Accumulation (VFA) on increased risk of early onset (or premature occurrence) of diseases via mathematical modelling. This leveraging is to be used in a non-invasive system of ours to assess incremental VFA in patient’s biological system as opposed to conventional invasive detection techniques. Reviewing available literature and established studies on quantitative models predicting VFA (Visceral fat Accumulation) Extracting literature with published graphical relationships and quantitative information relating to VFA Seeking access to clinical databases on causal factors for VFA Generating predictive analytics using this data to assist employees in assessing risk to VFA related illnesses.