Training Testimonial Page
Last Updated March 2020.
Machine Learning (DSWT_MLx)
The breadth of topics
covered was significant. The notes are very comprehensive and a
resource that remains available to review at my leisure. The
python resources are also comprehensive. The build up of ML from
Regression made the material more digestible and removed a lot of
the secrecy and fog shrouding the topic! Nayyar came across as
very passionate, yet humble and very approachable. The resources,
both theory and code, proved comprehensive and a great resource
to take away and digest in my own time. The course served as a
rewarding, albeit intense 2 days, which removed the shroud of
secrecy around Machine Learning and built it up from the basics.
The small group easily enabled discussion and questions in a
personable environment. I look forward to the next level!
Stephen Bradshaw
Spatial
Scientist BE(hons), GDipEd, MSc PhD Candidate
CSIRO/UTAS
Quantitative Marine Science Program
Fantastic overview of data
science, delivered by someone who is authoratitive in the field.
Suggestion to improve the course: maybe expand to an optional 3rd
day, with the 3rd day focussed purely on applications.
Nayyar is a great lecturer,
and he tries to break down the complicated statistics and machine
learning issue and explain it in a very understanding manner, he
covers advanced techniques and provides a few practical tips. He
provided a deep understanding of the machine learning concepts.
Since he offered efficient and practical tips, I highly recommend
his course to those who are interested in machine learning and
computer science.
The course really enhanced
my technical understanding of key ML models and how they operate.
This is invaluable information and I was really happy to move
beyond base level intuition, without feeling overwhelmed. I think
it is excellent as it stands, perhaps a few more practical
examples of application would be valuable, to illustrate how each
approach and model has been used to date. There were some
examples, but I think having a go-to example for each model type
could be really valuable and may assist those who are less
technical to understand the intuition behind each. That said, I
had to leave early and missed the section on model selection, so
it is quite possible you do that there! Amazing course! Thank you
very much!
It was great to be
introduced to new machine learning concepts I had no prior
experience working with, such as Recommender systems and
Multi-arm Bandits. Nayyar's explanations were valuable at
enhancing my fundamental understanding of the logic and
assumptions behind models that I use day-to-day. The course was
great at giving a broad overview to the majority of streams of
machine learning. It is very hard to run a course covering the
breadth of these topics while still making it accessible to a
large distribution of prior knowledge levels. In future, it could
be beneficial to run the course over three days, with the first
(optional) day targeted at building the programming and
statistical knowledge needed to explore the machine learning
models over the next two days. This could enable deeper technical
discussion and more time to build applications of the models in
the labs. The office space was convenient and a great environment
for the course to be delivered. More regular breaks and two-sided
activities could help promote a higher level of engagement from
the class.
Getting introduced to the
many machine learning techniques/models/algorithms while
understanding how data scientists are using them (for which
purpose). It has been a very useful and informative session and
it will help me out to continue exploring this field. There were
some topics that were completely new to me and it was great that
I could get some exposure to the basic concepts behind them -
like for example text related analyses (document representation,
latent semantic analysis and similarities measures) as well as
image processing (convolutional neural networks) and recommender
systems. Definitely, the material provided (slides) and the labs
are a key take away as well ! Finally, networking and hearing how
other people in the field are using machine learning is very
useful. Unfortunately, I don't think we had enough time to cover
the labs properly. I do appreciate that Nayyar did his best to
give us an idea of what examples and data sets he had prepared
for us but we just run out of time to cover this. Maybe extending
the duration of the course might be useful but on the other hand
people will always think that more time is needed to cover other
things. By the way, I will go through the labs on my own time and
and I am very thankful that Nayyar has kindly shared this
material with us. That's awesome ! I am very happy with this
course and it fulfilled my expectations. I believe that Nayyar
has done a great job on exposing us to all the many models and
techniques that machine learning has to offer. I believe that a
key aspect from this workshop is that Nayyar puts emphasis on
explaining the logic behind each ML algorithm, the assumptions
and the key aspects that we should consider when trying to
implement them. In many occasions I was not able to follow up on
the content being presented but if you hang in there, Nayyar will
eventually be able to remove the complexity out of it while
allowing you to get the basic ideas behind them.
There was a lot of great
material in the workshop; but I think that the most valuable part
was Nayyar's ability to cover such a vast amount of material and
methods and give an intuitive understanding of each one. I'm not
sure that people realise it, but it takes a lot of effort and
concentrated study to boil these models down to an intuitive
approach which was maybe taken for granted by some of the
participants. I have taken a couple other courses like this in
Sydney. This one really really stands out; it is valuable
information and you can see that its the quality of information
and understanding you would expect from an academic. The other
courses are money grabs for using R/python to solve kaggle and
its really sad. I think maybe some people just want to be told
how to use sklearn and don't care to understand how it actually
works. Maybe this would be more profitable for you... but it
would be sad if this course had to drop to that level.
A key takeaway was an
appreciation that despite the diversity of approaches and
techniques for machine learning, the fundamental principles are
largely the same and that there's "No free lunch". I realise that
despite the media hype there's no panacea that solves all
problems, but that the accumulation of experience and developing
an intuition is crucial to becoming a successful data scientist.
I really loved the sharing of 'intuitions' about how to use ML.
The venue was great; both the facilities and the accessibility of
location. There was A LOT of material covered and the workshop
did feel quite rushed. Aside from extending the length of the
workshop I'm not sure what else could be done. Again the schedule
was very tight but more opportunity to interact with other
participants about the material to learn together would have been
good. I was prepared for a lightning tour of machine learning and
I was not disappointed. We covered so much ground but I feel I
now have a better understanding of the ML landscape and know
where I can go for more details. Nayyar both knows his stuff and
the limits of his experience so he gently encourages us to seek
more for ourselves.
We signed up for the Data
Smelly course on Machine Learning to provide key members of our
team with a solid foundation in Machine Learinng. We weren't
disappointed. The two day course proved to be a great 'route-map'
through the subject, providing an overview which covered all the
main techniques and areas of interest. Nayyar was a great teacher
too - animated and clearly excited by his subject. I'd highly
recommend this course to anyone from a technical background who
wants to learn more about how machine learning might be applied
to their industry.
Nayyar managed to break
down the complex concepts behind machine learning in a way that
could be easily understood. I found his course valuable in
assisting me with communicating with data scientists and business
stakeholders in order to promote machine learning solutions
within my organisation. Thanks Nayyar!
What I liked best was the
instructor's ability to give alternative explanations for
challenging concepts, clear expertise, and willingness to help.
A good grounding of the
theory surrounding machine learning. Some insight into
application and strategy of use. Thanks for putting on an
interesting course. Good course material and a good insight into
machine learning.
Peter Lyons
Origin Energy
Dr Nayyar Zaidi is an
enthusiastic facilitator and an excellent data scientist. His
courses blend theory and practice, with practical hands-on
exercises, and a chance to network with like-minded data
practitioners. The best thing about Nayyar's courses is his
ability to distill industrial applications of data science into
easy-to-understand anecdotes and take-home insights for us.
Data Smelly’s course
Machine Learning was great. It provided both statistical and code
based learning of ML concepts. I found the Python Labs to be very
useful to get up and running with some good code provided. Nayyar
is an enthusiastic teacher and provides practical examples.
Really enjoyed the course and recommend it highly.
The course was a general
overview of many machine learning techniques, and it gave me a
general understanding of the benefits of each. The key take away
I took was the trade off between accuracy and bias that different
models gave. Nayyar was a friendly and approachable instructor.
Dylan Gajewski
Workforce
Analytics, ATO
It is a great course,
highly recommended for those who want to work in the AI / Data
Science field or get a better understanding of these
fast-developing and highly sought after skills. The course covers
various supervised and unsupervised techniques of machine
learning, along with guidelines of when to apply each of them and
what to do in case they don’t work.The practical labs were useful
to get hands-on experience on python and solve real-time data
problems. Nayyar, the course convenor designed the course to be
self-contained and that makes it stand out from other ML courses
online. Personally, I felt course had an intuitive concept of
gradient descent and gives sufficient introductions to advanced
ideas like Artificial Neural Networks and Unsupervised learning,
which helped me with sufficient foundations and curiosity to
pursue the field further study(research PhD)
Through this workshop, I
have learnt a lot about the machine learning fundamental and
how/when to use it. There are so many machine learning algorithms
were covered in this workshop. In addition, it is important to
learn the fundamental of specific algorithm better than applying
it blindly or without deep understand of the algorithm. Also, the
instructor, Dr Nayyar is very experienced in machine learning,
friendly, and will use example to explain very clearly about the
concept. Excellent workshop and value for money especially for
students who are doing machine learning or data science course.
Through this workshop will allow you to have better understand
the machine learning and importantly when/how to use it. This
workshop covered so many various topic of machine learning
including the hot topic deep learning.
The key take aways were the
underlying foundation of many statistical techniques which i can
now build on through self study. The workshop was very well
thought out and covered a large amount of content. Out of
everything, the use of mathematical notation to describe and
explain the concepts is far superior to just explaining the idea
with words, and personally, i found the intuition much easier to
grasp. Great workshop. Suggestion: Extend the duration of the
course so all the material and labs can be covered.
A grounding across many
current machine learning areas. A better understanding of how the
maths fits in. ..and lots of interesting approaches to use in
coming projects. It was great to be able to interact and clarify
as we went along. Nayyar, you did a great job of keeping us
moving and learning.
Anonymous
Aside from technical
details, the key lesson for me was the importance of
understanding the data you are analysing and selecting the
appropriate model for the data set. Nayyar has an outstanding
grasp of all the underlying concepts and presents them in a way
that makes it easy to move through (and retain) a lot of heavy
content in just two days. The only comment I would have is to
allow more time for the practical lab sessions, as these are
typically the best way to cement theoretical knowledge and ground
it in real-world examples
Anonymous
Machine learning is a
really powerful tool that can be used in data science. I found
the Model Selection, Supervised ML and Unsupervised ML sections
most relevant for the work I do. Would like more time for the
labs and practicing with python in the course. Found the course
taught a lot of content within the timeframe, and at times was
hard to take it all in. Thank you Nayyar for an enjoyable course.
Anonymous
I gained a much greater
understanding of the logic behind machine learning, and now feel
more confident in my ability to build these ideas into my work
and processes. Nayaar was great, fun, easy going guy who was very
approachable, and clearly passionate. Thanks for the great
workshop! I also really enjoyed the opportunity to discuss ideas
with the others in the room that shared a passion for data and
its potential.
Anonymous
Finding out about the
strengths and weakness of the different techniques, e.g.
bias/variance tradeoff, getting my head around the various terms
used in ML, and some of the applications of ML were very
interesting! I feel like I have a good idea of the different
things ML can do now. Thank you!
Anonymous
Overall, this was a very
good course. Theory was excellent. I'd prefer to do the course
again after doing some prior reading to prepare myself for the
onslaught of mathematical notation.
Anonymous
Learnt a great deal about
the mathematics of machine learning, which was my primary goal.
From this I can develop project plans for machine learning
projects, to allow them to be developed across the organisation.
Anonymous
The board overview of
higher level extensions on the second day provided me with a lot
of ideas to take away and apply to my own work.
Anonymous
Overall as very good and
useful.
Anonymous
Thanks to the workshop, I
used different algorithms in the model and took an average of the
predicted results. The model's accuracy is improved and can
generate better results in various situations.
I really appreciated the
breadth of the course - a wide selection of techniques was
covered over the day. Although the time did not permit us to go
into technical depth with each topic, I found that I was able to
gain an appreciation of the themes and keywords for my future
research. Thanks Nayyar for a very enjoyable and
thought-provoking presentation.
The course was excellent. A
lot of thought has been it into the course slides. This course
represented very good value for money.
Amanda Aitken
Actuarial
Edge
Good review on ML theories
and algorithms; met nice people :).
Ran Niu
Roy Morgan
Research
My take-away from the
workshop was that, "Machine learning is at one level easy to
comprehend. At another level, experience would be essential to
know what algorithms to select and sanity checking the results".
I Would like a more thorough practical component. I now know
someone (Nayyar) to turn to if ML becomes part of my product. He
seems very knowledgeable
Deep Learning (DSWT_DLx)
Nayyar's Deep Learning
course covers an astounding amount of information. While the
breadth of this course is a lot to absorb in one day there is
plenty of material to go back to and deepen your understanding.
What is really invaluable is Nayyar's intuition for the topics
covered that only comes with experience and practice. This is
combined with clear explanation of concepts always tied back to
simpler models. I would highly recommend this course to anyone
who is just starting in Deep Learning and wants to get up to
speed; or anyone who has a background in ML/statistics and
perhaps has been having moderate success with these models who
wants to get to the forefront of methods used in industry.
It's rare to find a course
that is able to balance highly technical content with practical
and engaging applications. This course definitely erred towards
the technical content - which I really enjoyed. Nayyar has a
knack for illustrating complex concepts using relatable examples,
which is great for building a fundamental understanding of any
topic. The volume of content covered in one day is equivalent to
two semesters of a post-graduate university course and is great
value for money. Nayyar also provides a lot of detailed readings
and exercises to further your development outside the course.
Nayyar delivers a
comprehensive and in-depth survey of the key motivations and
directions in the research and practice of deep learning. The
content is communicated and explained very clearly. The material
would suite potentially 2 or 3 days worth of delivery sessions
however, and he did very well to cover an extensive range of
material in the one day. The material is provided at an
appropriate level of technical treatment and insights are drawn
from the delivery as to potential applications to commercial
problem domains. Overall this was an intellectually generous,
well communicated, very well researched and engaging workshop. It
is a good grounding for further research activities, or
assessment of where value can be derived from the variety of
available modelling approaches to your potential application
domain. If you are evaluating this form of modelling for your
problem domain, this course is highly recommended.
Anonymous
Software
Engieer
I really enjoyed the day
and I have LOTS to explore with a greater context gained from the
course.
Anonymous
Dalivery
Manager, BPM & Integration
I really enjoyed learning
about the Representation Learning and CNN as these are techniques
I have not used before. I found Nayyar very knowledgeable and
good at explaining the theory. I felt the course content was
rushed as there was such a large amount of content, this made it
hard to absorb at times. The labs are very beneficial, and gave
me more confidence to put the theory into practical use. Would be
great to have more focus on this in the future. Thank you for
sharing your knowledge with us!
It is a good course and
value for in deep learning for those who are mathematically
inclined.
Some of the concepts are
more clear now. Got a couple of ideas that we could try in our
projects. In general, the instructor came across a very humble
and approachable person. We were able to interact with him
freely.
I learned the clear
definition of Deep Learning and the most original concept of Deep
Learning. If it can be much longer and has some practice or
exercise, it would be wonderful. I hope it can be last for at
least a week.
I gained a better
theoretical understanding of how CNN and RNN works, with good
illustrations to cover the key concepts.
Anonymous
All of Data Science (DSWT_AODSx)
The course was a great
introduction to AI & ML, pitched perfectly at a recent university
graduate such as myself. The flow from revision of mathematical
foundations to application of complex methods ensured I was not
lost at any point along the way; and if I did find myself with a
question, Nayyar was always prepared to provide a helpful answer.
My take-away from the course -- How you approach AI & ML for a
project. I didn't previously appreciate how much thought goes
into understanding your problem in the first place, determining
which models & methods are applicable, inspecting your data etc.
before jumping in an actually training a model. I now have a much
better idea of where to start when applying AI & ML.
I thoroughly enjoyed the
workshop. Learnt a fair amount and using the knowledge in my
workplace. My key take-home lessons were that starting a basic
machine learning project is not hard. However perfecting the
model is the challenge. And second, there are lot of free tools
and libraries.
I think this course was
excellent in giving all the information needed in a relatively
short amount of time. Perhaps offering a further course that goes
back and gives another, longer deep dive into a few of the topics
would be beneficial, however I don't think that's necessary as
the 5-day course gave so much information and to a depth where I
feel like I understand to a degree that lets me conduct further
research in my own time.
I’m so glad that I have
this chance to attend in your training. it was fantastic. I think
if you cover Data Visualisation in this course, it sounds more
better and helpful. If you prepare all labs on windows
environment before running the labs, I think you save more time
for training.
There are a lot of tools
out their that can be applied for Machine learning and ANN, how
to access and use the tools is critical to deriving benefit from
ML/ANN. It would be good to spread this over a number of weeks,
so that you can go away and do some homework in between.