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I applied via Indeed and was interviewed before Aug 2023. There were 2 interview rounds.
Seeking new challenges and opportunities for growth.
Looking for new challenges and opportunities to learn and grow
Interested in working with new technologies or in a different industry
Seeking better work-life balance or career advancement
Company restructuring or changes in management impacting job stability
I admire my former manager for her strong leadership skills and dedication to mentoring her team.
Strong leadership skills
Dedication to mentoring team
Effective communication
Ability to inspire and motivate others
I applied via campus placement at National Institute of Technology (NIT), Calicut and was interviewed in Nov 2024. There were 2 interview rounds.
"I applied via campus placement First round was an aptitude containing quant,english, logical reasoning and data interpretation (60 mins ,60 questions) plus technical round (30 mins,30 questions) conducted via Aon platform. Aptitude was easy but was a bit lengthy. Technical test was also moderate and covered all topics from mechanical core. After the written test there was a resume shortlisting for people who cleared round one.Prepare ur resume according to the role ur applying. From around 87 members 27 were shortlisted for GD round. ."
They divided us into 4 groups and group discussion went on for around 20 mins my topic was (Are ev vehicle's an efficient solution for pollution). In gd round listen to the topic carefully. Don't hesitate to put ur thoughts first donot interfere while other is speaking listen to them and put ur thoughts in a politeful way , mostly stick to the topic. After 20 mins the recruiters asked me to summarise the topic and i gave a brief summary keeping everyone's and my thoughts in mind. After GD 9 members were selected for the interview.Gd and interview happened on the same day.
posted on 6 Dec 2024
Normal aptitude test containing behavioural, mathematical, English questions
Oopc, dbms, sql, se concepts were there with few os, dsa and got related questions
posted on 15 Sep 2024
I applied via Campus Placement and was interviewed in Sep 2024. There were 3 interview rounds.
Good thinking about it was just thinking of you guys are doing well done💯 with our relationship between us and our house🏠 is it possible for me to be on your face time⌚
Myself I don't know what you think about how much we can help with your friends with me for more than just don't know what you think about how much you want to see
I applied via Company Website and was interviewed in Jun 2024. There were 2 interview rounds.
I applied via campus placement at College of Engineering ( Formerly Pune Instiute of Enginering and Technology ), Pune and was interviewed in Sep 2024. There were 2 interview rounds.
If everyone is cheating you should also do it?
Linear regression is used for continuous variables, while logistic regression is used for binary outcomes.
Linear regression is used to predict a continuous outcome based on one or more input variables.
Logistic regression is used to predict the probability of a binary outcome based on one or more input variables.
Linear regression assumes a linear relationship between the independent and dependent variables, while logist...
Normalization in DBMS is the process of organizing data in a database to reduce redundancy and improve data integrity.
Normalization involves breaking down data into smaller, more manageable tables and establishing relationships between them.
It helps in reducing data redundancy, minimizing data anomalies, and improving data consistency.
There are different normal forms such as 1NF, 2NF, 3NF, BCNF, and 4NF, each with spec...
Array difference is finding the elements that are present in one array but not in another.
Use set operations like difference to find elements in one array but not in another.
Example: arr1 = ['a', 'b', 'c'], arr2 = ['b', 'c', 'd'], arr_diff = set(arr1) - set(arr2) = ['a']
A medium python program
Optimizing code for better performance and efficiency
Use built-in functions and libraries for faster execution
Minimize unnecessary loops and conditions
Avoid redundant code and optimize data structures
Implement caching or memoization for repetitive computations
Optimizing Python code involves improving efficiency and performance.
Use built-in functions and libraries instead of writing custom code
Avoid unnecessary loops and nested loops for better performance
Optimize data structures and algorithms for faster execution
Numpy is a powerful library for numerical operations in Python, with efficient array operations and mathematical functions.
Use vectorized operations instead of loops for better performance.
Avoid unnecessary copying of arrays to save memory.
Utilize broadcasting to perform operations on arrays of different shapes.
Use numpy functions like np.sum(), np.mean(), np.max(), etc. for efficient calculations.
Optimize code by prof
posted on 22 Dec 2024
Reliance Industries
Shell
Indian Oil Corporation
Schlumberger