SEO stands for search engine optimization. It is a powerful data analytics tool that can enhance a company’s online platform. The goal of SEO is to utilize Google’s algorithm in order to have your website ranked #1 on the SERP (search engine results page). This will increase user traffic to your site because more users will click on your page. My eyes were first opened to the SEO industry during my internship at Clutch where we used a balance of intercept and intent traffic to capture a large target audience in order to convert them into paying customers. Even though SEO is a newer strategy, it has a higher return on investment than typical paid advertisements. With this, smaller companies can learn SEO and outsmart the bigger companies, while using a smaller marketing budget.

The purpose of this paper is to discuss the history of artificial intelligence (AI) and its future implications in the healthcare industry. Utilizing information from research and medical journals, this paper will examine the foundations of AI and the people and events that influenced its development. Further, the various subsets of AI and its use in contemporary life will be discussed. While the technological evolution of AI will be discussed, this paper is not a technical treatise on the inner workings of AI software and technology, rather, it is a basic history of the development of AI and its respective subsets, and a look at current and potential future applications of AI. This information will be applied to the healthcare industry to discuss the history of AI in this field, detailing how AI was developed to find innovative solutions to complex medical problems. Finally, future prospects of AI in the medical industry will be discussed, explaining potential applications of this technology as well as various challenges and implications.

The objective of this project was the creation of a web app for undergraduate CIS/BDA students which allows them to search for jobs based on criteria that are not always directly available with the average job search engine. This includes technical skills, soft skills, location and industry. This creates a more focused way for these students to search for jobs using an application that also attempts to exclude positions that are looking for very experienced employees. The activities used for this project were chosen in attempt to make as many of the processes as automatable as possible.
This was achieved by first using offline explorer, an application that can download websites, to gather job postings from Dice.com that were searched by a pre-defined list of technical skills. Next came the parsing of the downloaded postings to extract and clean the data that was required and filling a database with that cleaned data. Then the companies were matched up with their corresponding industries. This was done using their NAICS (North American Industry Classification System) codes. The descriptions were then analyzed, and a group of soft skills was chosen based on the results of Word2Vec (a group of models that assists in creating word embeddings). A master table was then created by combining all of the tables in the database. The master table was then filtered down to exclude posts that required too much experience. Lastly, the web app was created using node.js as the back-end. This web app allows the user to choose their desired criteria and navigate through the postings that meet their criteria.