Immersive Visualization for AI Governance

Number of individual students required: 6 Be part of solving the critical problem of AI explainability. Explainability of AI and Machine Learning is a significant challenge, as is humanity's capacity to keep up with & govern ever-improving algorithms. Objective of this project is to apply our patented technology for visualizing & explaining an AI or machine learning model of your choice. For inspiration, we have to-date applied the technology to visualizing nodes of a Tensorflow model and for seeing dimensions used to train a random forest classifier in context of model-determined outcomes vs. actual outcome from the training dataset. Immersion Analytics' patented technology and products make it possible to see up to 18 dimensions of data as a single, intuitive visualization. This is accomplished using special effects as added axes, intensity of each effect is varied at each data point to convey additional dimensions. Our Stepwise Storyboarding capability permits adding dimensions one at a time as you tell the data story. Students will receive a personal-use license for Immersion Analytics Visualizer, which can be used in concert with Python, MATLAB, Qlik Sense, and even CSV data files. We have many samples for use with Python, several for MATLAB, and extensive documentation and install support. Students should be prepared to: Identify an AI or machine learning project where up to 18 dimensions, primarily numeric, are used to train the model. This can be a project from github or elsewhere online, or one of the student's design. Develop immersive visualization using our Python package or MATLAB toolbox alongside our Visualizer product Prepare a 2-page data storytelling walkthrough of your creation, with screenshots (greenshot is fine). While we are open to your inspirations, a few areas of specific interest for us include: Predicting customer lifetime value Recommendation engines Fraud detection

Data Analysis and Machine Learning for HR

Positions Available: 4 We’d like students to help analyze our datasets to identify and evaluate key performance indicators for a standard HR department. This project will create a ready to use HR analytical solution for medium size companies. The solution will use Power BI as a visualization tool and will have a machine learning module used to identify employees at risk of leaving the company. Here are some of the topics we’d like students to explore throughout this project: KPI identification, predictive and prescriptive analysis using Power BI. Involvement in the development of the ML module using Python and Tensorflow. Highlight the benefits of the solution to HR departments in different industries.

Data Scientists: for a Fintech Start-up

Number of positions available: up to 2 (working individually or in a team) Our team is seeking up to two Data Science/ML/AI students who are passionate and creative. We want this (these) students to build our unique streaming data pipelines. This is an incredible opportunity for any student(s) that are looking to build their resume and portfolio. The students will have the chance to lead this project as well as execute on the development. A bit more detail on the project: Background: This (These) student(s) will have the opportunity to develop our specific streaming pipelines and data workflow. Our business and dev team will work closely with the student(s) and help them execute on this project. Students will be using Python and Google Cloud Platform. If you are in your last year of your program and are looking for an incredible opportunity this is it. To accomplish this, we expect the student(s) will: Have experience coding with Python or Java . Be comfortable learning new tools and technologies. Ideally have some experience with GCP products including Dataflow, Apache Beam, BQ, Non-SQL databases and Pub/Sub. Knowledge of GIT is required. If you like the sound of our culture and are ready to tackle this incredible challenge with us, then we'd love to hear from you.

Newsletter Communications Analysis (Virtual)

Number of students: 1 Background: HPCO creates a bi-weekly newsletter for our members and stakeholder using Constant Contact. Project Objective: To evaluate the effectiveness of the newsletter content by analyzing data on "open" rates of each newsletter edition and the "click through" rates of each article in the newsletter. Project Deliverables: Download Constant Contact newsletter data Analyze the "click through" data for each article in the newsletters Summarize the trends (most popular topic, content, design etc) Create a written report of findings Create a PowerPoint presentation of findings