Data Scientist - 1

Tip 1: Read basic ML concepts from Andrew Ng, NPTEL, IIIT, or IITM.
Tip 2: Have a basic understanding of linear algebra.

We can start with a normal join, but check if a left or right join could lead to a more optimal query.

Tip 1: Read about linear algebra.

Tip 2: Have an understanding of mathematical concepts used in deep/machine learning (Jacobian, derivatives, etc.).

Tip 1: Provide answers or approximations instead of simply giving up.
Tip 2: Have confidence in yourself, and clearly explain related topics if you don’t know the full answer.

Tip 1: You can study transformers from online resources.

Tip 2: Practice making diagrams, as it will boost your confidence.

Tip 1: Have an understanding of the basics of neural networks.

Tip 2: Know the pros and cons of different models and approaches.

Tip 1: Have an idea about different statistical distributions.

Tip 2: Ask for clarifications on assumptions if the problem statement is not clear.

Step 1: Write the basic formula for calculating percentile.
Step 2: Option 1: Create a map of the students and sort it.
Option 2: Just create a map and perform the calculation during function calling.
Step 3: Identify the position or rank of the input student and use it to calculate the percentile.

Tip 1: Have knowledge about the company.

Tip 2: Have an idea about the latest developments and products in your tech stack.

Tip 1: Involve discussion of competitors and recent startup ideas.

Tip 2: Discuss recent technologies and their possible inclusion in the product or service.