Artificial Intelligence & Data Science
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Expand Your Knowledge of Artificial Intelligence

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Course Report - Expand Your Knowledge of Artificial Intelligence

Course Report

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Course Features

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Duration

3 months

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Effort

15 hours per week

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Teaching Type

Self Paced

Course Description

This program will help you to be a better Artificial Intelligence/ Machine Learning Engineer. It will show you how to apply classical AI algorithms to common problems. Projects and exercises will include search, optimization and planning. These techniques are used in Artificial Intelligence applications such as logistics, operations research and automation. These concepts are the basis for many of the latest advances in AI. Every project you create will allow you to show what you have learned in lessons and will become part of your career portfolio, which will prove your mastery of these skills for potential employers.

Course Overview

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Job Assistance

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Personlized Teaching

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International Faculty

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Post Course Interactions

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Hands-On Training

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Case Studies, Captstone Projects

Skills You Will Gain

Prerequisites/Requirements

Basic knowledge of linear algebra and calculus

The ability to apply basic probability and statistics

Programming experience in Python

Some experience implementing computer science algorithms and object-oriented programming

The ability to run programs and interpret output from a command line terminal or shell

Access to a Windows, macOS, or Linux computer with Python 34 or later installed, and admin permissions to install new programs

What You Will Learn

Use constraint propagation and search to build an agent that reasons like a human would to efficiently solve any Sudoku puzzle

Build agents that can reason to achieve their goals using search and symbolic logic—like the NASA Mars rovers

Extend classical search to adversarial domains, to build agents that make good decisions without any human intervention—such as the DeepMind AlphaGo agent

Model real-world uncertainty through probability to perform pattern recognition

Target Students

Engineer

Developer

Course Instructors

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Peter Norvig

Research Director, Google

Peter Norvig is a Director of Research at Google and is co-author of Artificial Intelligence: A Modern Approach, the leading textbook in the field.
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Sebastian Thrun

Instructor

As the founder and president of Udacity, Sebastian’s mission is to democratize education. He is also the founder of Google X, where he led projects including the Self-Driving Car, Google Glass, and more.
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Thad Starner

Professor Of Computer Science, Georgia Tech

Thad Starner is the director of the Contextual Computing Group (CCG) at Georgia Tech and is also the longest-serving Technical Lead/Manager on Google's Glass project.

Course Reviews

Average Rating Based on 6 reviews

5.0

100%

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