NICE Actimize Business Analyst and Specialist Interview Questions and Answers

Q1. What are the relevant projects in Data science & expertise in whatt all tools & technologies
Ans. 
Relevant projects in Data Science and expertise in tools and technologies
• Projects: Predictive modeling, Natural Language Processing, Computer Vision, Recommender Systems, Time Series Analysis

• Tools: Python, R, SQL, Tableau, Hadoop, Spark, TensorFlow, Keras, Scikit-learn

• Technologies: Machine Learning, Deep Learning, Big Data, Cloud Computing, Data Visualization
Answered by AI
Add your answer

Q1. He asked only coding question in Python & time duration is less & expectations are pretty unclear .
Add your answer

Platform HackerEarth
9 Questions
2 Coding Questions on Python based on Dynamic Programming
7 Questions MCQ on Data Science and SQL

Q1. Data Science Projects discussion Python Coding by sharing screen
Add your answer

Q1. Data Science Projects Detailed Questions
Add your answer
Q2. In Depth Knowledge on any one of your project.
Add your answer
Q3. Cross Questioning on Regression, Classfication Problems. Dummy Variable Trap Statistics Questions
Add your answer
Q4. Questions on Deep Learning Models working and architecture like RNN Exploding/Vanishing Gradient Problem, Solutions like LSTM, CNN model working and different terminologies used.
Add your answer

Q1. Again this round was pure Technical. All questions were on Data Science Projects and scenario based. 2 Questions on Probability and puzzle based.
Add your answer

Q1. Final Round Discussion about Company's Policies and Roles. Your Expectations from the company, the kind of role you are looking for and why Tiger.
Add your answer

Q1. Python programming, basic linear regression and logistic regression
Add your answer

Q1. Linked list, dynamic programming questions
Add your answer

Q1. Dicision Tree algorithm
Ans. 
Decision Tree algorithm is a supervised learning algorithm used for classification and regression tasks.
• Decision Tree algorithm is based on a tree-like model of decisions and their possible consequences.

• It uses a set of rules to split the data into branches and make predictions at the leaf nodes.

• The algorithm selects the best attribute to split the data based on certain criteria like information gain or Gini index.

• Deci...read more
Answered by AI
Add your answer

Q1. Decision tree based questions
Add your answer
Q2. Evaluation matrix based questions
Add your answer