This advanced deep learning course provides a more rigorous, mathematically based view of modern neural networks, their training, applications, strengths and weaknesses. It focuses on key architectures such as convolutional nets for image processing and recurrent nets for text and time series. This course will also include use of dedicated hardware such as GPUs and multiple computing nodes on the cloud. There will also be an overview of the most common available platforms for neural computation. Some topics touched in the introduction will be revisited in more thorough detail. Optional advanced topics may include Generative Adversarial Networks, Reinforcement Learning, Transfer Learning and probabilistic neural networks.
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Discounts
Face to face public courses: early bird pricing is available until 2 weeks prior. Group discounts: 5% for 2–4 people, 10% for 5–6 people, 15% for 7–8 people, and 20% for 9 or more people. Discounts are calculated during checkout.
Online public courses: available at a 25% off the face-to-face courses as a special introductory price. to groups or to individuals who want to follow a curriculum program and attend multiple courses:
- 2-4 courses/attendees 10% off
- 5+ courses/attendees 20% off
Hurry as bookings will close 1 week before each course. Group discounts are calculated during checkout on individual courses. Individuals can book multiple courses at a discount – please enquire.
Additional Information – Advanced Deep Learning
| Audience | Expert This course is for data scientists who want to develop skills with this most recent and exciting technology in the machine-learning domain, as well as for data ops engineers who would be supporting the training and deployment of neural nets. |
| Objective | The purpose of this course is to provide more advanced data scientists, those already familiar with the basics of deep learning with a deeper understanding of the methods, underlying theory and hardware technology used in modern deep learning. |
| Prerequisites | Students should have completed or have equivalent knowledge to the course Deep Learning and AI |
| Format | Class |
| Duration | 2 days |
| Level | 5 |
| Course Author | Dr Eugene Dubossarsky |
| Trainer | Courses are taught by Dr Eugene Dubossarsky and/or his hand-picked team of highly skilled instructors. |
| Delivery Method | In-person at AlphaZetta Academy locations or on-premise for corporate groups |
Private and Corporate Training
In addition to our public seminars, workshops and courses, AlphaZetta Academy can provide this training for your organisation in a private setting at your location or ours, or online. Please enquire to discuss your needs.
Scheduled Public Courses
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Private and Corporate Training
In addition to our public seminars, workshops and courses, AlphaZetta Academy can provide this training for your organisation in a private setting at your location or ours, or online. Please enquire to discuss your needs.
Other Core Data Science Curriculum Courses
Testimonials
Eugene’s courses are not your standard technical courses where you learn how to put data into a model and get a result. The real life experiences – warts and all – he brings to the instruction mean that attendees walk away with a better understanding of the real life challenges of analytics as well as the technical know-how. We routinely send our team members on these courses to help them get the capabilities that really help our clients get better insights from their data.
Eugene’s introductory course to data science was outstanding.
I found the subject matter and delivery fascinating, accessible and informative. I found Eugene approachable, interesting to listen to and excellent at simplifying complex concepts. I highly recommend this course for anyone who wants to know what data science—and all the buzz surrounding it!—are all about.
