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Python Data Science coding test is for recruiters and hiring managers to assess the Python skills of a data scientist. Our Python Data Science coding test helped many enterprises to identify the right fit candidates and reduce time-to-hire by 40% & hiring costs by 45%.
Data science experts have continued with their increasing development in Python for data analysis. This process mostly includes learning the Python fundamentals in the data science domain along with learning a few Python data science libraries for example NumPy, Pandas, Matplotlib, Scikit-Learn, etc. During this process, building a portfolio is also important i.e. by adapting Data Cleansing Projects, Data Visualization Projects, Machine Learning Projects, etc. Hence, Python is used at every step in the data science process for e.g. data scientists can use Python and Panda’s library to clean and sort the data into a data frame (table) which is ready for analysis, exploring, and visualizing the data.
Python Data Science coding test helps tech recruiters and hiring managers to assess candidates’ data science with Python skills. Data scientist with Python technical test is designed by experienced Subject Matter Experts (SME) to evaluate and hire data scientists with Python as per the industry standards.
Test Duration: 60 minutes
No. of Questions: 27
Level of Expertise: Entry/Mid/Senior
Our Python Data Science test assesses a candidate's ability to work on python and also checks knowledge of libraries
iMocha's Python Data Science coding test evaluates the ability to data analysis, data mining & wrangling to draw the right conclusion and support decision making
The Python Coding Test For Data Science checks proficiency in SQLite coding to understand the candidate's knowledge of handling data
Python Data science test assesses a candidate's knowledge of Classification and Regression to evaluate the relationship between two or more independent variables
Choose from our 100,000+ question library or add your own questions to make powerful custom tests
Question types:
Multiple Option
Topic:
Matplotlib
Difficulty:
Hard
Question types:
Multiple Option
Topic:
Classification and Regression Algorithms
Difficulty:
Easy
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“We realized that to acquire quality talent, our recruitment process was in dire need of automation. Too many of our technical team were simply wasting hours conducting interviews that did not yield the desired results. For us, the foremost criteria was to find a recruitment partner who could tick all the right boxes.”