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Artificial Intelligence

The main goal of this course is to familiarize you with all aspects of Artificial Intelligence so that you can start your career as an artificial intelligence engineer.

What you will learn

  • Basics of Deep Learning techniques
  • Understanding artificial neural networks
  • Training a neural network using the training data
  • Convolutional neural networks and its applications
  • TensorFlow and Tensor processing units
  • Supervised and unsupervised learning methods
  • Machine Learning using Python
  • Applications of Deep Learning in image recognition, NLP, etc.
  • Real-world projects in recommender systems, etc.
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Classroom

30000.00

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ILO

22000.00

Audience

  • Professionals working in the domains of analytics, Data Science, e-commerce, search engine, etc.
  • Software professionals and new graduates seeking a career change.

Pre-requisites

  • Strong hold on Mathematics
  • Strong experience of programming languages
  • Writing algorithm for finding patterns and learning
  • Strong data analytics skills
  • Good knowledge of Discrete mathematics

Table of Content

1.Course Overview

This Microsoft Internet of Things workshop will guide you through an implementation of an end-to-end IoT solution simulating high velocity data emitted from smart meters and analyzed in Azure. You will design a lambda architecture, filtering a subset of the telemetry data for real-time visualization on the hot path, and storing all the data in long-term storage for the cold path.

2.Pre-requisties

There are no prerequisites for this course.

3.Objective

At the end of this Microsoft Cloud Workshop, you will be better able to construct an IoT solution implementing device registration with the IoT Hub Device Provisioning Service and visualizing hot data with Power BI.

4.Course Outline

Module 1: Whiteboard Design Session - Internet of ThingsLessons

  • Review the customer case study
  • Design a proof of concept solution
  • Present the solution

Module 2: Hands-on Lab - Internet of ThingsLessons

  • Environment setup
  • IoT Hub provisioning
  • Completing the Smart Meter Simulator
  • Hot path data processing with Stream Analytics
  • Cold path data processing with HDInsight Spark
  • Reporting device outages with IoT Hub Operations Monitoring