Artificial Intelligence Certification Courses

Artificial Intelligence is one of the fastest-growing and most exciting fields in technology today! Knowledge of Deep Learning and Machine Learning is highly valued by companies that are creating cutting-edge technology and professionals with these skills can expect their career to skyrocket in the coming years. Edureka offers certification courses in TensorFlow and Mahout to help you take advantage of the career opportunities in Artificial Intelligence.

PG Program

PGP in AI & Machine Learning

NIT Warangal

Mentorship from NITW Professors
Networking with faculty
Alumni Status
Placement Assistance

Post Graduation Program

E&ICT, NITW

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Artificial Intelligence Bestseller Courses

AI & Deep Learning with TensorFlow

15k Enrolled Learners
Weekend/Weekday
Live Class

Reviews

4 (6150)

84% - Course completion rate

Next batch In 34 days - 25th October What will I learn?

Introduction to Deep Learning
Understanding Neural Networks with TensorFlow
Deep dive into Neural Networks with TensorFlow

Natural Language Processing with Python ...

1k Enrolled Learners
Weekend/Weekday
Live Class

Reviews

4.5 (550)

88% - Course completion rate

Next batch In 55 days - 16th November What will I learn?

Introduction to Text Mining and NLP
Extracting, Cleaning and Pre-processing Text
Analyzing Sentence Structure

Machine Learning with Mahout Certificati...

8k Enrolled Learners
Weekend/Weekday
Selfpaced

Reviews

4.4 (3350)

81% - Course completion rate

* Lifetime access for the course What will I learn?

Introduction to Machine Learning and Apache Mahout
Mahout and Hadoop
Recommendation Engine

Reinforcement Learning

1k Enrolled Learners
Weekend/Weekday
Live Class

Reviews

4.4 (500)

80% - Course completion rate

Next batch In 55 days - 15th November What will I learn?

Introduction to Reinforcement Learning
Bandit Algorithms and Markov Decision Process
Dynamic Programming & Temporal Difference Methods

Graphical Models Certification Training

1k Enrolled Learners
Weekend/Weekday
Live Class

Reviews

4.1 (450)

89% - Course completion rate

Next batch In 34 days - 25th October What will I learn?

Introduction to Graphical Model
Bayesian Network
Markov’s Networks

Load more courses1 more available live program(s)

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Artificial Intelligence Courses description

AI & Deep Learning with TensorFlow

Edureka's Deep Learning in TensorFlow with Python Certification Training is curated by industry professionals as per the industry requirements & demands. You will master the concepts such as SoftMax function, Autoencoder Neural Networks, Restricted Boltzmann Machine (RBM) and work with libraries like Keras & TFLearn. The course has been specially curated by industry experts with real-time case studies.

Natural Language Processing with Python Certification Course

Edureka’s Natural Language Processing with Python course will take you through the essentials of text processing all the way up to classifying texts using Machine Learning algorithms. You will learn various concepts such as Tokenization, Stemming, Lemmatization, POS tagging, Named Entity Recognition, Syntax Tree Parsing and so on using Python’s most famous NLTK package. Once you delve into NLP, you will learn to build your own text classifier using the Naïve Bayes algorithm.

Machine Learning with Mahout Certification Training

An online course designed to provide a blend of Machine learning & Big Data and where Mahout fits in the Hadoop Ecosystem.

Reinforcement Learning

In this course, you will be introduced to Reinforcement Learning, an area of Machine Learning. You will learn the Markov Decision Processes, Bandit Algorithms, Dynamic Programming, and Temporal Difference (TD) methods. You will be introduced to Value function, Bellman Equation, and Value iteration. You will also learn Policy Gradient methods. You will learn to make decisions in uncertain environment.

Graphical Models Certification Training

Graphical Models Course is designed to teach Graphical Models, fundamentals of Graphical Models, Probabilistic Theories, Types of Graphical Models – Bayesian (Directed) and Markov’s (Undirected) Networks, Representation of Bayesian and Markov’s Networks, Concepts related to Bayesian and Markov’s Networks, Decision Making – theories and assumption, Inference and Learning in Graphical Models.