AI Fundamentals

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5

(3)

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Course Features

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Duration

4 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Teaching Type

Self Paced

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Video Content

4 hours

Course Description

What's the truth behind all the AI hype? What's the truth behind the hype surrounding Machine Learning, Deep Learning, and Predictive Analytics. What are the limitations of machine learning? Machine Learning can be used for recognition of written numbers, prediction of customer turnover, and structure in Elon Musk's tweets. All of these topics will be covered in this course. This course will introduce you to AI in a gentle, but very practical manner.

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Highlights

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Pedagogy

Top 20 Percentile

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Rating & Reviews

Top 30 Percentile

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Parameters

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Pedagogy

Acquire all major Computer Vision skills in this course for seamless integration into your daily life. Develop a versatile skill set, allowing you to confidently apply what you've learned in various practical scenarios, enhancing your daily experiences and overall proficiency. An exceptional course in Computer Vision, this stands out for its Self Paced learning approach. Learners have the flexibility to progress at their own speed, tailoring the experience to their individual needs.

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Rating & Reviews

This highly acclaimed course is among the top-rated in Computer Vision, boasting a rating greater than 4 and an overall rating of 5.0. Its exceptional quality sets it apart, making it an excellent choice for individuals seeking top-notch learning experience in Computer Vision.

Course Overview

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Virtual Labs

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International Faculty

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Post Course Interactions

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Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

What You Will Learn

Learn the fundamentals of AI. No programming experience required!

Understand the definition of AI ( “general” and “narrow”), the relationship between AI and Machine Learning

Learn about supervised learning, work with labeled data and train regression models

Learn about unsupervised learning, divide data into clusters, detect anomalies and select the right model for the job

Learn about deep learning, create your first neural networks, and train a model to recognize digits

Course Instructors

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Nemanja Radojković

Senior Data Scientist @ Dataroots

Nemanja's areas of expertise include Machine Learning, Text Mining and Computer Vision. He is currently a Senior Data Scientist at Dataroots, where he helps businesses to harvest the power of their d...

Course Reviews

Average Rating Based on 3 reviews

5.0

100%

Course Cover