Master Designing, Integrating & Deploying Enterprise AI Apps | Data Science Online Course by Udemy

Development Online Course by Udemy, On Sale Here

Become an expert in modern tech stack (asyncio, flatbuffers, NATS, and Docker) to design, integrate and deploy AI apps

An excellent training about Data Science

Master Designing, Integrating & Deploying Enterprise AI Apps

Target Audience Machine Learning Engineers & Data ScientistsWhat is unique about this course & What will you learn?Why What & How of designing, integrating & deploying Enterprise Level Data Science/AI/ML applicationsHow to translate requirements into scalable architectural components?How to break a big complex problem into simple & manageable parts using microservices style architecture?An End-to-End real-world enterprise-level machine learning solutionAsynchronous IO – Foundations & Writing I/O bound applications in python 3NATS – A Cloud Native Computing Foundation open source project to connect distributed applicationsFlatBuffers – A language-independent, compact and fast binary structured data representation languageDocker & Docker-compose – The gold standard in deploying and orchestrating applicationsWhy should you learn all this?A statistical or deep learning model is not an application rather it is an important component of a solution to real-world problems. A sophisticated solution to a complex problem generally consists of multiple applications written using different languages and running on a cluster of machines. Your role as a Data Scientist and Machine Learning engineer is not just limited to a model building or tuning its performance rather it is expected that at the very minimum you will design your applications so that they can easily integrate with other applications of a big solution as well as are easily deployable using modern DevOps methodologies. Mastering how to make AIapplications integrate with other applications while ensuring scalability and upgradability will offer you a competitive advantage over others. The good news is that mastering them is not difficult at all! How is this course taught?My teaching style covers 3 key aspects of mastering any technology: IntuitionTheoryCodeFor any solution first I describe the overall goal, its associated challenges, and how to break down a big complex problem into manageable components. This process of simplifying the problems into components will guide you in identifying & selecting the best technology to use. I then explain the why, what & how of the selected technologies (AsyncIO, NATS, Flatbuffers, Docker) with code examples. These code examples start simple and I then iteratively add features to bring them to the level of real-world applications. I have taken immense care in preparing the material that has great animations to help you develop intuition behind the solutions.I have made sure that coding sessions follow an iterative development style and more importantly are clear & delightful. All the source code from the iterative cycles as well as full end to end solution has been provided in the resources.

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