What you get:
10 ideas for machine learning projects.
Free datasets to use for your projects.
Examples of libraries and algorithms for each case.
Nikolaos is one of the people I mentored. Through a personalized approach to mentoring, we developed a plan of action to help him reach his goals.
First, we worked on enhancing his resume, LinkedIn, and GitHub profiles to ensure that they accurately represented his skills and experience in data science.
Next, we honed Nikolaos' Python coding skills, which are essential for data science roles. We focused on hands-on projects.
In addition to coding skills, we also focused on enhancing Nikolaos' knowledge of machine learning.
Finally, we concentrated our energies on preparing Nikolaos for behavioral interview questions, which aim to evaluate his compatibility with the organization's culture and team.
Ultimately, our efforts paid off, and Nikolaos landed a data science job within three months of starting our mentorship.
I am proud to have played a role in his success and grateful for the opportunity to have shared my knowledge and experience with a motivated and hardworking individual like Nikolaos.
Here is the transcription of the interview I did with him.
My name is Nikolaos Zavitsanos and I am from Greece.
I completed a Bachelor's degree in Computer Science at City University and then a master's in Artificial Intelligence at the University of Edinburgh.
My focus during my master's was NLP and recommendation systems.
I am currently working as a Data Scientist in the TUI group.
When we met I was working in a start-up as a machine learning engineer. While I really enjoyed the projects and the team, I wanted to expand my experience and exposure across multiple areas, as I am still in the early stages of my career.
TUI Group presented the opportunity of broad exposure to a wide variety of projects, as well as, specifically, recommendation systems which I have been very interested in since my Master's.
It was not a lengthy process to secure my new position as I had initiated the application process promptly.
Approximately two months after our last conversation, I received an offer for the position.
The handbook was really useful to me. I used it all the time for my interviews, and it helped me recall what I learned during my Master's. The project anatomy section was especially helpful for my own side projects. Overall, having these resources made things so much easier for me.
The hiring process consisted of one 30-minute interview, followed by a 2.5-hour interview and a coding challenge.
Both of the interviews included a mix of technical questions, behavioral questions, and some questions specific to my background.
My main piece of advice is to be targeted in your application process - only applying to and spending time on applications that you are truly interested in and that match your skill set.
You should also focus on ensuring that you have the core coding skills required and a comprehensive understanding of key data science concepts.
I am thrilled about my new employment opportunity. From the onset, I have been exposed to new and challenging tasks that allow me to expand my skill set. Additionally, I have the privilege of working with recommender systems, which was the subject matter of my dissertation.
Overall, this is a fantastic experience.
In the end, Nikolaos' story is one of determination, hard work, and perseverance.
Through his dedication to learning and his willingness to seek out mentorship and guidance, he was able to make a remarkable transformation and secure a job in data science within a short period of time.
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