SASAN MEHRABIAN

Manager, Exposure and Capital Analytics at Scotiabank

PROGRAM NAME

DATA SCIENCE TRAINING PROGRAM

PROGRAM TYPE

CERTIFICATE PROGRAM

 

PROGRAM INFROMATION

I strongly support Lantern’s activities and believe the growth of their company would benefit others in receiving quality training and job-landing assistance.
I have been a Lantern student for the last 4 months and was able to land a job in one of the top 5  banks of Canada through them. I was able to get the job before finishing the whole program mostly because of Lantern’s unique features. In my point of view, Lantern has two important features that other educational institutes don’t have: 

  1. Their instructors, who are industry experts and senior professionals. From day one, I noticed the passion the Lantern team committed to providing high-quality training and job landing assistance to students. Also, Lantern cares a lot about networking, and that is why their instructors have a strong network. The instructors introduce students to their network by setting up coffee meetings or informational interviews. They also refer students to managers who are hiring,  which was my case. 
  2. Lantern’s tuition model. Students pay tuition only after securing employment. This removed a  financial barrier that would have otherwise deterred or stopped me from receiving equivalent training. Additionally, it demonstrated the seriousness and commitment of the company to help its students secure employment. 
SASAN MEHRABIAN

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TECHNICAL ASSESSMENT

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OUR RESULTS DRIVEN TRAINING MODELS

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The instructors are busy professionals, but they generously exchange ideas and supervise the projects and usually accept mentorship requests. The scopes of the projects vary from 1 month for the basic courses, to 4 months for the advanced courses. The system is very co-operative and in my personal case, I have learnt a lot from my classmates, while collaborating on different projects. Lantern has skin in the game and charges a small registration fee relative to the norm of the industry; its bulk of income depends on future graduates’ success in landing a decent career.

Prior to Lantern, I had specialized in UofT’s Analytics stream, which was just a theoretical exposure to 4 data science courses. At Lantern, I practically developed my coding skills. Serious students who dedicate time and effort (at least 20-30 hours a week) will develop the fundamental coding skills in Python and R within a 3-month time period, and then they can build up more complex Machine Learning and in-depth analytical projects supervised by instructors all of whom are industry professionals. The class size is approximately 20 students for general courses and gets smaller for more advanced courses. Throughout the semester, students get career advice, resume review, soft skills catch up, mock interviews and should also deliver a few presentations about the projects they have developed.