Course Description
Organized by :
Supported by :
Organized by :
Supported by :
Aims
The Deep Learning Developer Course is built to take you from being a standard programmer to being able to add the Deep Learning Engineering skill set to your repertoire and CV. It goes beyond just theory and focuses on giving you the real world skills needed to prepare you for the position of being a key first hire for any company looking to develop an AI team, whether that be a start-up, SME or MNC.
Why Deep Learning Engineer?
Deep Learning is being adopted extensively not only by big tech companies but in the fields of finance, healthcare, insurance, biotech, education, and entertainment. Anywhere there are large amounts of data, Deep Learning is becoming a crucial skill. The demand for AI talent is exploding across the world. Both start-ups/SMEs and multinational companies are actively looking for engineering talent with not only a knowledge and understanding of Deep Learning but with a track record of having built models and systems that work in the real world.
Requirements
You need to be able to read and write code fluently. This is not a beginners course. Ideally, you will also have some experience with the Python language and its various APIs. While not 100% necessary, experience with NumPy and the Python SciPy libraries will be an advantage. Developers with no prior Python experience will be given some pre-learning materials to get up to speed on Python.
Course Details
The course will consist of 48 hours of in-person tuition. This will be spaced across 8 weeks - each week having two 3 hour sessions. Each week, one of the 3-hour sessions will be devoted to theory and instruction related to concepts, applications and implementation of Deep Learning to build Artificial Intelligence applications. The second 3-hour session will be a hands-on lab where you will have the chance to implement the learning by creating real applications, models, and projects, using the skills that you are learning.
After the full 8 weeks, you will have created a portfolio of applications that you have built which will be uniquely yours. You will be expected to bring real-world problems (or at least figure out something cool that you'd like to build during the course).
We are planning to limit the number of course participants so that we can make sure that everyone gets the attention they deserve.
Projects
During the program you will be expected to complete foundation projects that are assigned in the program as well as 2 personal projects that relate to your work (or outside interests). The goal behind the personal projects is that :
- you get to apply what you are learning to real world projects that can help the companies you work for; and
- it allows you to create a portfolio of original work that sets you apart from other job candidates in the market, which is crucial in demonstrating your skill set to future employers.
Instructors:
- Dr Martin Andrews
- Martin has over 20 years experience in Machine Learning and using it to solve problems in financial modelling and creating AI automation for companies. His current area of focus and specialty is in natural language processing and understanding.
- Sam Witteveen
- Sam has used Machine Learning and Deep Learning to build multiple tech startups, including a children’s educational app provider which has over 4 million users worldwide. His current focus is AI for conversational agents to allow humans to interact easier and faster with computers.
Spots are very limited, click here to apply now
Apply HereCourse Outline
The following is a rough outline of the course contents. However, we anticipate that "new stuff" will get substituted in if/when exciting papers appear.
The Implementation Clinics may also have side-talks, where additional material gets discussed, which you may find super-interesting, or perhaps a bit of a distraction from the project work...
Cost
Organized by :
Supported by :
Organized by :
Supported by :
For the 8-week course, consisting of 16 separate 3-hour sessions, the fees are as follows:
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Full fees without subsidyS$ 3,000 / person
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Subsidized fees for Singapore Citizens/Permanent ResidentsS$ 900 / person
with WSG's funding support
FAQ
These topics have all been raised by people either on email, or face-to-face (at, for instance, the TF&DL MeetUp events) :
Spots are very limited, click here to apply now
Apply HereRed Dragon AI is Singapore-based AI startup. In addition to product development (currently in stealth mode), we are conducting Deep Learning courses to help build Singapore's talent pool.
Latest Activities
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TF & DL MeetUp : Happy 3rd Birthday TensorFlow, Google Brain, HUB-GANS and BERT
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Community
Red Dragon AI's founders also organise the TensorFlow and Deep Learning MeetUp (hosted at Google), and the PyTorch and Deep Learning MeetUp (hosted at Facebook).