8-Week Deep Learning Developer Course

Course Description
Organized by :
Supported by :


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.


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.


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 :

  1. you get to apply what you are learning to real world projects that can help the companies you work for; and
  2. 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.


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 Here

Course 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...

Organized by :
Supported by :

For the 8-week course, consisting of 16 separate 3-hour sessions, the fees are as follows:

  • Full fees without subsidy
    S$ 3,000 / person
  • Subsidized fees for Singapore Citizens/Permanent Residents
    S$ 900 / person
    with WSG's funding support


These topics have all been raised by people either on email, or face-to-face (at, for instance, the TF&DL MeetUp events) :

This is actually explained above in 'Requirements', but perhaps we need to explain a little. We're not expecting any in-depth knowledge of the workings of Python, but would recommend that you're at least familiar with the basic syntax. It will be feasible to complete the course using code implemented in Jupyter notebooks, for instance. On the mathematics side, we hope that participants have at least a hazy recollection about calculus, and a willingness to try to figure out how to translate complex-looking expressions into code.
Monday and Wednesday evenings from 7pm-10pm, for 8 weeks starting on 25-Sept-2017. We may insert a 'catch-up week' or two, if the class starts to feel that more time is required for digestion of the material or getting the projects to work.
The SGInnovate offices at 32 Carpenter Street (nearest MRT: CLarke Quay). Note that this won't be in the main auditorium, since it's not a great teaching space, but rather on one of the upper floors, which has a conference room, and other, more practical space for the classes.
SC/PR students can already use the WSG subsidy. For foreign students, there is a only slim chance that we can provide a scholarship, but it will only be on a case-by-case basis. Please contact us to discuss.

Spots are very limited, click here to apply now

Apply Here

Red 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.


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).