Graphical Models Certification Training
Key Features of the Course
Qualification Type
Certification Training
Level
Certificate
Availability
UK and International
Qualification Title
Graphical Models Certification Training
Course Type
Live Online (Virtual Learning)
Machine learning made simple by using Graphical models. Graphical Models Certification Training will teach you the e fundamentals of Graphical Models, concepts, types and representations. The course will take you through directed graphs (Bayesian Networks) and undirected graphs (Markov’s Networks). These graphs are used in machine learning for diagnostics, speech recognition and intelligent systems. The course will focus on graph theory and how they can be applied and gain a comprehensive understanding of graph model structure and its parameters.
The Graphical Models Certification Training course is designed to teach you about the graph theory and probability theory that will let you have an apt understanding about the modules that are taught throughout the course.
The Graphical Models Certification Training will allow you to become proficient in using graphical models for learning as well as decision making. This course will allow you to explore more options and further your career.
When can I start?
| £239 | ||||
|---|---|---|---|---|
| Commencing Soon (Sat & Sun) | 04:00 PM to 7:00 PM | 3 Hours | Enquire Now |
| Group 2 | ||||
|---|---|---|---|---|
| Notified Later | 7.00pm – 9.00pm | 2 hrs | Notified Later |
Why You Should Consider Taking this Course at Study 365?
Study 365 is a leading online provider for several accrediting bodies, and provides learners the opportunity to take this exclusive course awarded by Edureka. At Study 365, we give our fullest attention to our learners’ needs and ensure they have the necessary information required to proceed with the Course. Learners who register will be given excellent support, discounts for future purchases and be eligible for a TOTUM Discount card and Student ID card with amazing offers and access to retail stores, the library, cinemas, gym memberships and their favourite restaurants.
♦ 1: Introduction to Graphical Model
♦ 2: Bayesian Network
♦ 3: Markov’s Networks
♦ 4: Inference
♦ 5: Model Learning
♦ Data Scientists
♦ Researchers
♦ AI Engineers
♦ Python Programmers
♦ Developers
What are the entry requirements?
♦ Learners should be over the age of 16, and have a basic understanding of English, ICT and numeracy.
♦ A sound educational background is recommended.
♦ Knowledge of Python theories is recommended.
♦ Understanding of Machine Learning (ML) and Artificial Intelligence (AI)
What qualification will I gain?
Upon the successful completion of the course, you will be awarded the ‘Graphical Models Certification Training’ certificate by Edureka.
Edureka is a pioneer in online learning and an agency that has frequently and consistently collaborated with educational and academic institutes. It guarantees expert commitment and is dedicated to learners taking their courses. Edureka is internationally recognised and takes learners a step closer to a leading career in the IT industry.
Once you successfully complete the course, you will gain an accredited qualification that will prove your skills and expertise in the subject matter. With this qualification you can further expand your knowledge by studying related courses on this subject, or you can go onto get a promotion or salary increment in your current job role. Below given are few of the jobs this certificate will help you in, along with the average UK salary per annum according to http://payscale.com
♦ Data Scientist – £70,000 (Approximately)
♦ Research Analyst – £49,000 (Approximately)
♦ AI Software Engineer – £70,000 (Approximately)
FAQs Please click on the link below…
Click Here for More Info Terms and Conditions
Learners can cancel the course and receive a full refund, 10 business days prior to the start date of the course. If we do not have 10 business days’ notice, we cannot offer a refund.
Study 365 reserves the right to reschedule any classroom session up to 48 hours prior to the classroom session. The session may be rescheduled due to tutor illness, low numbers of attendees for the session or other unforeseen circumstances.
