I applied through Linkedin, on there Linkedin account.
Round 1( Aptitude): 30 MCQs about data science, Machine Learning
Round 2 (Problem-solving Scenario): Machine learning solving round, given a Machine learning problem and to solve by using python /R
Round 3(Technical Interview): Two interviewees interviewed me. Most questions are on OOP, Python, Java Collections & Hadoop
- What is a tuple in python?
- Differences between supervised learning and unsupervised learning.
- What is the K N N classifier?
- Differences between classification and regression.
- What is OOP?
- Inheritance types in java and python?
- How can we achieve multithreading?
- Explain Python libraries?
- Sklearn discussion?
- What is big data?
- Differences between Hadoop and Apache Spark?
- What is map-reduce and define mapper and reducer?
- What is RDBMS?
- How do we connect to the python database?
- Can we add duplicate entries in Tuple?
- What is an iterator in java?
- Differences between java and python?
- Why java is faster than python?
- What else you know except Mysql?
- Types of Inheritance in java and python.
- Discussed my internship.
- Discussed the technologies that I know.
- Data cleaning is easy or data processing is easy.
- How do we convert String values to categorical numeric values?
- What are pandas and NumPy?
- How do we create a data frame?
- How many ways to create a data frame in python?
- Can we create a data frame with two lists?
Round 4 (HR Round):
- What are your Achievements
- Analytics Vidhya rank
- Hackathons you participated
Attention reader! Don’t stop learning now. Get hold of all the important DSA concepts with the DSA Self Paced Course at a student-friendly price and become industry ready. To complete your preparation from learning a language to DS Algo and many more, please refer Complete Interview Preparation Course. In case you are prepared, test your skills using TCS, Wipro, Amazon and Microsoft Test Serieses.