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I appeared for an interview in Jun 2024.
It was basic apptitude questions consisting of logical and verbal
Top trending discussions
I appeared for an interview in Jul 2024.
HR professionals are responsible for recruiting, training, managing employee relations, and ensuring compliance with labor laws.
Recruiting and hiring new employees
Training and development programs for staff
Managing employee relations and resolving conflicts
Ensuring compliance with labor laws and regulations
Developing and implementing HR policies and procedures
posted on 24 Feb 2025
I appeared for an interview in Jan 2025.
I have a basic aptitude test, and I also possess fundamental knowledge regarding the subject.
posted on 7 Mar 2025
posted on 10 Mar 2025
I appeared for an interview before Mar 2024.
Questions was related to Human resource management, financial accounting and etc.
posted on 16 Aug 2023
Law of demand states that as the price of a good or service decreases, the quantity demanded increases, and vice versa.
Inverse relationship between price and quantity demanded
Consumers buy more of a good when its price decreases
Illustrated by downward sloping demand curve
Exceptions include Giffen goods and Veblen goods
I am expecting a competitive CTC based on my qualifications and experience.
I am looking for a salary that is in line with industry standards for Assistant Professor roles.
I have considered factors such as my education, teaching experience, and research background when determining my expected CTC.
I am open to negotiation based on the specific responsibilities and benefits offered by the institution.
posted on 5 Oct 2023
I applied via Company Website and was interviewed in Sep 2023. There were 5 interview rounds.
Aptitude & General Questions
posted on 24 Feb 2025
Machine learning is a subset of artificial intelligence that focuses on developing algorithms to make predictions based on data, while deep learning is a subset of machine learning that uses neural networks to learn from large amounts of data.
Machine learning is a broader concept that encompasses various techniques such as decision trees, support vector machines, and random forests.
Deep learning specifically refers to ...
Supervised machine learning in modern businesses includes applications in customer segmentation, fraud detection, recommendation systems, and predictive analytics.
Customer segmentation for targeted marketing campaigns
Fraud detection in financial transactions
Recommendation systems for personalized product suggestions
Predictive analytics for forecasting sales or demand
Sentiment analysis for understanding customer feedbac
Supervised learning uses labeled data to train the model, while unsupervised learning uses unlabeled data.
Supervised learning requires a target variable to be predicted, while unsupervised learning does not.
In supervised learning, the model learns from labeled examples provided in the training data, while in unsupervised learning, the model finds patterns and relationships in the data without guidance.
Examples of super...
Reinforcement learning in chess involves training a system to make optimal moves based on rewards and penalties.
The system starts by randomly exploring different moves and receives rewards or penalties based on the outcome.
Over time, the system learns to make better moves by maximizing rewards and minimizing penalties.
Examples of reinforcement learning in chess include AlphaZero and Stockfish, which use neural networks
Decision Tree Classifier is a machine learning algorithm that creates a tree-like model of decisions based on features.
Uses tree-like structure of decisions to classify data
Easy to interpret and visualize
Can handle both numerical and categorical data
Can handle multi-output problems
Prone to overfitting if not pruned properly
Clustering in data mining is the process of grouping similar data points together based on certain criteria.
Clustering is an unsupervised learning technique used to discover hidden patterns or structures in data.
It helps in organizing data into meaningful groups without any prior knowledge of the groupings.
Examples of clustering algorithms include K-means, Hierarchical clustering, and DBSCAN.
Applications of clustering ...
Common tools used in Big Data include Hadoop, Spark, Kafka, and SQL databases.
Hadoop: Distributed storage and processing framework for large data sets.
Spark: In-memory data processing engine for speed and ease of use.
Kafka: Distributed streaming platform for handling real-time data feeds.
SQL databases: Traditional relational databases used for structured data storage and querying.
posted on 10 Mar 2025
I appeared for an interview in Feb 2025.
Our commitment to excellence, innovation, and collaboration makes us the ideal choice for aspiring academics.
Strong research opportunities: We encourage faculty to pursue groundbreaking research, exemplified by recent grants awarded to our team.
Collaborative environment: Our department fosters teamwork, as seen in interdisciplinary projects that have led to significant advancements.
Commitment to student success: We pri...
I possess the necessary qualifications, experience, and passion for teaching and research in this academic role.
Strong academic background: I hold a Ph.D. in my field, which equips me with in-depth knowledge.
Teaching experience: I have taught undergraduate courses, receiving positive feedback from students for my engaging teaching style.
Research contributions: I have published several papers in reputable journals, demo...
posted on 10 Mar 2025
based on 1 interview
Interview experience
Assistant Professor
30
salaries
| ₹3 L/yr - ₹6.2 L/yr |
Associate Professor
6
salaries
| ₹5.2 L/yr - ₹6.8 L/yr |
Lab Technician
5
salaries
| ₹1.2 L/yr - ₹1.6 L/yr |
Student Relation Officer
4
salaries
| ₹1.2 L/yr - ₹2 L/yr |
Engineer
3
salaries
| ₹4.4 L/yr - ₹4.5 L/yr |
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