🔥 Top 5 AI Certifications 2023 | 5 Best AI… | 質問の答えを募集中です! 🔥 Top 5 AI Certifications 2023 | 5 Best AI… | 質問の答えを募集中です!

🔥 Top 5 AI Certifications 2023 | 5 Best AI…

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🔥 Post-Graduate Program In AI And Machine Learning:
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Are you interested in learning Aritifiical intelligence concepts but not sure where to start? Look no further! In this video, we will introduce you to the 5 best courses to learn Ariticial intelligence. From beginners to advanced learners, we have got you covered. Our experts have curated a list of courses that will help you understand the basics of Aritificial intelligene concepts and subset of AI, which is machine Learning and take you through advanced concepts.

00:00 introduction to AI
00:52 What is Aritifical intelligence?
01:53 Future trends of AI
04:48 Artificial intelligence engineer masters program
05:51 Caltech AI and ML Bootcamp
07:01 MS in Artificial intelligence
08:41 Wharton’s AI for Decision making: Business strategies and applications
10:08 Caltech Post Graduate Program in AI/ML

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About Post Graduate Program In AI And Machine Learning Course:

A form of artificial intelligence, Machine Learning is revolutionizing the world of computing as well as all people’s digital interactions. Machine Learning powers such innovative automated technologies as recommendation engines, facial recognition, fraud protection and even self-driving cars.This Machine Learning course prepares engineers, data scientists and other professionals with knowledge and hands-on skills required for certification and job competency in Machine Learning.

What skills will you learn from this Machine Learning course?

By the end of this Machine Learning course, you will be able to:
1. Master the concepts of supervised, unsupervised and reinforcement learning concepts and modeling.
2. Gain practical mastery over principles, algorithms, and applications of Machine Learning through a hands-on approach which includes working on 28 projects and one capstone project.
3. Acquire thorough knowledge of the mathematical and heuristic aspects of Machine Learning.
4. Understand the concepts and operation of support vector machines, kernel SVM, naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more.
5. Be able to model a wide variety of robust Machine Learning algorithms including deep learning, clustering, and recommendation systems

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🔥🔥 *Interested in Attending Live Classes? Call Us:* IN – 18002127688 / US – +18445327688
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Get the Android app: http://bit.ly/1WlVo4u
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