Get in-depth knowledge in Graphical Models, Markov’s and Bayesian Networks through this course provided by Edureka.
This course offered by Edureka will enable the candidates to understand what Graphical models are, their components, types, how to represent graphical models, and decision making using them. Candidates who are interested or are currently working in the field of Data Science with basic knowledge in Machine Learning or in Graphical Modelling, Artificial Intelligence, and Machine Learning enthusiasts, and Researchers can take up this course.
Graphical Models Certification Training offered by Edureka provides the candidates with the practical and hands-on knowledge required through cloud lab on a pre-configured environment and real-life case studies which involves implementing various Graphical Models concepts. The candidates are expected to have prior knowledge of Python, Probability theories, statistics, and fundamentals of ML and AI.
The course on graphical models is made to teach in brief the Graphical Models, Probabilistic Theories, fundamentals of Graphical Models, types of Graphical Models which include Bayesian and Markov’s Networks, decision making and its assumption and theories, representation of Markov and Bayesian Networks, concepts related to Markov and Bayesian Networks, learning and inference in Graphical Models.
The fees for the course Graphical Models Certification Training is -
*No Cost EMI starts at Rs. 2,250 / month
Yes
Edureka
The course can be taken up by the following candidates:
Certification Qualification Details
The candidates will be eligible based on the project they submit. Hence, once the project is duly submitted and the course is completed properly, candidates will be given the certification of completion.
After the candidates complete the course on they will be familiar with and understand the following terms and concepts:
The candidates who are interested to take up the course Graphical Models Certification Training will have to follow the below steps:
Step 1: Visit the course website.
Step 2: Click on Enroll on the right side of the page.
Step 3: Login in using your e-mail id and mobile number.
Step 4: After logging in the candidates can choose their desired batch for learning.
Step 5: Proceed to pay and join the course.
This Graphical Models classes course will enable the candidates to understand various concepts and terms under Graphical Models. It is specifically designed to teach the fundamentals of Graphical Models, types of Graphical Models that is Bayesian which is directed and Markov’s which is undirected, Representation of both Bayesian and the Markov’s network models, probabilistic theories, concepts relating to Markov’s and Bayesian networks, learning and inference in Graphical Models, and the decision making using the theories and assumption.
This course will benefit those candidates who are currently working or are interested in the field of Data Science, researchers, artificial intelligence, and machine learning enthusiasts.
Through this Graphical Models online course the candidates will gain practical knowledge with the help of the Cloud lab access provided in this course and will also benefit from the live online sessions, case studies, the assignments, quizzes, and tests given during this course, the candidates will get 24x7 expert support and will have access to the online forum where they can interact with the faculty and their peers to clarify their doubts.
The course comes with the added benefit of if the candidates miss their scheduled live class they can either view the recorded session or sign up for the same session in the next upcoming batch.
Yes, the candidates require knowledge in Python, statistics, probability theories, and fundamentals of ML and AI.
The candidates can view the recorded session or join the next live session batch if they miss their scheduled session.
As soon as the candidates complete the enrolment process they will gain full access to all the course contents.
The candidates will have lifetime access to the LMS after they enroll in the Graphical Models live course.
The candidates will have 24x7 lifetime access to the support team who they can call to clarify their doubts.
The candidates will be using the Cloud Lab to do their practicals and get real life experience.
Yes, the required system requirements are a system with an Intel i3 processor or above, an operating system with either 32 or 64 bit, and a minimum of 3GB RAM.
This course will improve the candidate’s employability as Machine Learning Engineers is a top emerging job on LinkedIn.
Yes, the candidates can choose their desired batch during the enrolment process.
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