Machine Learning LVL 1 | Meet ACA Tutors
In this series of articles we are discovering new professions and getting to know Armenian Code Academy tutors who are sharing their experience and knowledge with ACA students. Shahane and Hovhannes are the tutors of Machine Learning LVL 1. Shahane mostly is going to cover the programming part and Hovhannes is going to cover the mathematics part. Let’s get to know them.
What is your educational and work background?
Shahane: I have studied at the American University of Armenia, majoring in Computer Science for both bachelor and master degrees. I have started my career in Mathematics as a creator of educational materials and have pursued my career as a software developer in parallel. I have then decided to combine the two fields and started my first steps in the Data Science field with an introductory Machine Learning course organized in Picsart, followed by an in-depth five-month course at ACA. After that, I started working at Ucom and recently moved to Philip Morris International continuing my career as a data scientist.
Hovhannes: I have got my Bachelor’s degree in the Faculty of Physics at Yerevan State University. Then I enrolled in a one-year postgraduate diploma program for High Energy Physics at the International Centre for Theoretical Physics (ICTP) in Trieste, Italy. After this, I received my Master’s degree in the Faculty of Physics at Yerevan State University, majoring in Theoretical Physics. After this, for one year, I focused on Theoretical Physics and its related research at Bonn University in Germany. I have then got my Ph.D. in A. Alikhanyan National Laboratory (Yerevan Physics Institute), and currently, I work there.
How and why did you decide to tutor?
Shahane: I had noticed my ability to share my knowledge and teach when I was still in high school. I have always been able to not only properly share my knowledge and skills with the others but, most importantly, understand how to have a unique approach with each individual. I believe that the key to succeeding in the position of a tutor is understanding, patient, and knowing the right approach to each individual because you can never use the same teaching “technique” on everyone.
Hovhannes: Although this is just my second experience of teaching, I have noticed since my bachelor studies that I enjoy teaching and knowledge sharing. I have noticed that during teaching and explaining, I start to understand many things deeper, and I have to find many different points of view to explain the same thing. Also, the construction of analogies simplifies the teaching process. So this process is very interesting, challenging, and creative.
You are about to start your first course in Machine Learning LVL 1. What are you most excited about?
Shahane: Meeting new people who have a desire to become a part of this field is already exciting for me. I can’t wait to share my knowledge and to make sure that they have as good of an experience as I had years ago, making my first steps. I am excited to share all the “tricks” that come with real experience that no theoretical books or practical tutorials can teach you.
Hovhannes: Since I will teach the math part, I think that it is very challenging because we have very limited time for studying three different subjects in mathematics. Usually, each subject is a one-semester course, but we have to cover many topics in 3 months. Another exciting fact is that all the students have different mathematical backgrounds, and it is challenging to make the course balanced and exciting for all the students.
What do you think, what are the particular skills and knowledge needed to become a good specialist in Machine Learning?
Shahane: Before talking about the actual technical skills, I would say that it is of paramount importance to dive into the specific domain that you are going to work in (e.g., medical, telecommunication, marketing, etc.) and gain as much of the domain knowledge as possible since your algorithm and practical skills will never be enough. A lot of the decisions that you make will be coming from domain knowledge and intuition.
Moving to the technical aspect, the main languages used by data scientists around the world are Python, SAS, and R. Still, you may also be using other languages for some specific tasks. The rest of the tools used will highly depend on the field and the type of project you are working on. Some of the tools include Spark — a big data analytics platform that offers APIs for Python, R, Java, and other languages; Tableau — a data visualization software; Jupiter — allows interactive computing and widely used before the project deployment stage. Some of the most popular libraries used for data science are often referred to as tools as well; Python libraries include Matplotlib, NLTK, Scikit-Learn, TensorFlow.
Hovhannes: First of all, to become a good specialist in any field requires hard work, and machine learning is not an exclusion. But more specifically, one has to have a good knowledge of programming languages, which are used in machine learning such as Python, R, etc.
Moreover, some specific topics from mathematics are also required to understand machine learning algorithms, such as linear algebra, multivariable calculus, probability theory, and statistics. Moreover, knowledge of mathematics helps develop analytical skills, and specifically, probability theory and statistics develop the intuition to work with data.
What can newly applying students expect from the upcoming Machine Learning LVL 1 course?
Shahane: Students should expect a lot of theory along with the practice, since the theory is 90% of the work when going into this field, unlike most of the programming related fields. They should also be ready to dedicate some time outside the class to practice their skills and look through the theory until it becomes intuitive and clear.
Hovhannes: Students will study both mathematics (related to machine learning) and machine learning algorithms during this course. This is a good chance, and the first step to start a career in machine learning and become a good and required specialist.
Register to the course here:
