How I Nailed My First Data Science Internship

Author(s): Akula Hemanth Kumar

Originally published on Towards AI.

I am just a noob in studies. I am 2019 passed out of NIT Nagpur, with 6.4 CGPA. I did not get a job in campus placement.

But the big question!!

How an unplaced guy got an off-campus Intern?

I have joined Massive Open Online Courses(MOOCs), after completing the MOOCs, I started to apply for Internships in Internshala. I was in a feeling that at least seeing my college name (NIT Nagpur), I would at least get a call for interviews. I applied to 200 interns in 2 months. I did not get a call from a single company.

I started to realize that projects like

1. Twitter Sentiment Analysis
2. Iris Dataset Classification
3. Bike Sharing Demand
4. House Loan prediction
5. Titanic Regression

won't help me to land in an internship. They are just a starting point. In the meantime, I have developed an interest in Computer Vision. But I was confused about where to start.

I have found Monk_Object_Detection, Monk is a low code Deep Learning tool and a unified wrapper for Computer Vision. I started trying examples provided in Repo. Examples are so easy that anyone like me how has a basic understanding of object detection can easily get started.

Features which I like about the Monk:

U+1F4CC Its Framework Independent, we need not learn multiple frameworks like Tensorflow, Pytorch, Mxnet.

U+1F4CCIt has State of the art(SOTA) models like SSD, YoloV3, Faster-RCNN, Efficient-Det, RFBNet, CornerNet-Lite.

I started to develop confidence in myself. I started applying to Internships again, now only related to computer vision. I got my first call from Flutura. I got selected in my first interview call itself.

Where to apply for Internships?

1. Internshala
2. LinkedIn
3. Hirist
4. Angellist

How to prepare for Interview?

1. Get familiar with Linux.

2. Other than deep learning, you will be expected to be familiar with making Rest Apis.

I guess this will give you some idea on how to crack a Data Science intern interview. Remember, it is a tough road.

Some of the useful links for Computer Vision enthusiasts for Object detection:

1. Monk
2. VGG16
3. ResNet
4. YOLO
5. SSD
6. A paper list of object detection using deep learning
7. Object detection series

Thanks to Abhishek and Akash.

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.

Published via Towards AI