John Shipp is a veteran in the field of technology with 30 years of experience as a programmer and 17 years of professional experience as a web development expert. He holds professional certificates from MIT and CompTIA and has a diverse background working for Inc. 500 companies, Fortune 500 companies, small businesses and a number of startup companies.
John has been a mentor, tutor and a teacher to hundreds of people during his time as a professional developer and can help you learn to code, but can also provide insight into the world of freelance development and other industry specific areas.
In addition to the core languages of Internet development, John can also help you learn all the latest frameworks and libraries such as Ionic for mobile development, Angular.js for frontend development and Laravel for PHP (any many others).
Was in charge of the day-to-day marketing operations. I created a full-color catalog which was distributed to over 6000 homes. I also created the stockseed.com website while working for this company.
Network administration of a small community school system. Worked with Active Directory and other Microsoft technologies. Set up numerous Intranet sites, as well as an Internet site while employed. Implemented wireless strategies. Fixed computers.
Understand the challenges posed by Big Data (volume, velocity, and variety,) its sources and its potential impact for your industry.
Determine how and where Big Data challenges arise in a number of domains, including social media, transportation, finance, and medicine
Investigate m ulticore challenges and how to engineer around them
Explore the relational model, SQL, and capabilities of new relational systems in terms of scalability and performance
Understand the capabilities of NoSQL systems, their capabilities and pitfalls, and how the NewSQL movement addresses these issues
Learn how to maximize the MapReduce programming model: What are its benefits, how it compares to relational systems, and new developments that improve its performance and robustness
Learn why building secure Big Data systems is so hard and survey recent techniques that help; including learning direct processing on encrypted data, information flow control, auditing, and replay
Discover user interfaces for Big Data and what makes building them difficult Manage the development of data compression algorithms
Formulate the “data integration problem”: semantic and schematic heterogeneity and discuss recent breakthroughs in solving this problem
Understand the benefits and challenges of open-linked data
Comprehend machine learning and algorithms for data analytics
General understanding of the Internet and it's technologies.