This course prepares you for the 300-835 Automating and Programming Cisco Collaboration Solutions (CLAUTO) certification exam.
You will also learn how to use Application Programming Interfaces (APIs) interfaces such as Representational State Transfer (REST) and Simple Object Access Protocol (SOAP), parsing data in Extensible Markup Language (XML) and JavaScript Object Notation (JSON) formats, and leverage frameworks such as Python. Through a combination of lessons and hands-on labs, you will combine tools and processes to tackle communication challenges using key platforms including Cisco Unified Communications Manager, Cisco IP Phone Services, Cisco Unity® Connection, Cisco Finesse®, Cisco Collaboration Endpoints, Cisco Webex Teams™, and Cisco Webex® Meetings. Participants without any prior experience with Python should work through the proposed introductory materials before the course.The Implementing Automation for Cisco Collaboration Solutions (CLAUI) v1.0 course teaches you how to implement Cisco® Collaboration automated, programmable solutions for voice, video, collaboration, and conferencing on-premises or in the cloud. Our strategy is to continue to expand rapidly through product innovation, selective acquisitions and technical collaboration. Competence in Python or in another language such as Java, C/C++, MATLAB, or Mathematica is absolutely required. This school is targeted at Master or PhD students and Post-docs from all areas of science. We show how clean language design, ease of extensibility, and the great wealth of open source libraries for scientific computing and data visualization are driving Python to become a standard tool for the programming scientist.
Here, you consider not just particular values of your arrays, but you go to the. Python works as a simple programming language for beginners, but more importantly, it also works great in scientific simulations and data analysis. Something a little bit more advanced than subsetting, if you will, is slicing. Python programming, recommender systems library Correlation-based collaborative filtering, latent factor models, neural collaborative filtering, deep learning. Whether you're a student, a data scientist or an AI researcher, Colab can make your work easier. We use the Python programming language for the entire course. Colab, or 'Colaboratory', allows you to write and execute Python in your browser, with. New skills will be tested in a real programming project: we will team up to develop an entertaining scientific computer game. In this course we will present a selection of advanced programming techniques, incorporating theoretical lectures and practical exercises tailored to the needs of a programming scientist.
We will be using the Google Collab platform for todays workshop.
As a result, instead of doing their research, they spend far too much time writing deficient code and reinventing the wheel. Python 2.0 - A more advanced look into Python that focuses on how to analyze data. While techniques for doing this efficiently have evolved, only few scientists have been trained to use them. Scientists spend more and more time writing, maintaining, and debugging software. Tool/Resource: Conferences, Workshops and Meetings