Free Data Science with Python Practice Test3830 Tests taken

The Python practice online test is for those trying to become a data scientist. With this Python exam, you can test your programming skills and be well-prepared for your exam. Python is important for data science professionals and these python exam questions help you prepare by mimicking the exam you will take when getting certified. Take this python test from Simplilearn and start your journey toward certification today!

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Data Science with Python

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  • Instructions:

  • FREE test and can be attempted multiple times.
  • 60 Minutes
  • 50 Multiple Choice Questions
  • You can pause the test in between and you are allowed to re-take the test later.
1. The {_____} function returns its argument with a modified shape, whereas the _____ method modifies the array itself.
2. Which of the following functions helps create a new array object that looks at the same data?
3. Which of the following statements limits both x and y axes to the interval [0, 6]?
4. In NumPy, what does the shape (2,3,2) indicate?
5. What type of chart should we use if we have estimated a set of data and want to plot the uncertainty of the estimation?
6. In statistics, a Type II error occurs when:
7. In BeautifulSoup, .parent is used to:
8. In Beautiful Soup, which of the following is used to create a new tag?
9. In BeautifulSoup, what are the options to search a web tree?
10. We need to define an index in Pandas.
11. In Pandas series, data can be accessed through different functions such as:
12. What will be the result in vector addition if labels are not found in a series?
13. Which function will you use from the NumPy library to convert the angles from degrees to radians?
14. Which of the following structures is used for three-dimensional data analysis in Pandas?
15. How can you view the first 10 records in a Pandas DataFrame?
16. What does the following code do? import pandas as pd df = pd.read_csv('log-access_file.csv')
17. Who is a data scientist?
18. In NLP, stemming is a technique to:
19. Predict the correct output of the following code: >>>a=np.arange(6) >>>print(a)
20. In Machine learning, predictive modeling works on:
21. If a database is imported, and there is no index for its values and dates, how do you create one?
22. A client reading data from the HDFS file system in Hadoop _____.
23. Hadoop is written in:
24. In Spark, RDDs can be created from the datasets stored externally
25. MapReduce was devised by_____.
26. In BeautifulSoup,how can you remove all modified tags?
27. In BeautifulSoup , how can you view tag attributes?
28. Who developed the BeautifulSoup library?
29. Which of the following parsers has an external C dependency?
30. Which of these classes can be used to parse a part of a document?
31. Which of the following operations is performed by Search Engines?
32. How can you edit the Navigable String?
33. Which of the following parsers cannot be used for parsing a part of a document?
34. Which of the following is a very slow parser?
35. What will be the output of the following code line? feature_extraction.text.CountVectorizer([...])
36. How will you save a plot as a PNG image in matplotlib?
37. Which of the following methods is used to create a model in Scikit-learn?
38. In the Kmeans clustering technique, which method sets the number of clusters?
39. Which of the following is an important component of the text processing pipeline?
40. What is the operation conducted by the following code line?>>>for link in soup.find_all('a'):print(link.get('href'))
41. Which of the following is useful to save a model?
42. Which of the following code lines has a valid syntax? >>>soup = BeautifulSoup(open("index.html")) >>>soup = BeautifulSoup("<html>data</html>")
43. Which of the following code snippets is used to print all the tag children?
44. To find out unique target classes in the dataset, which of the following code snippet is useful?
45. What is the built-in database used for Python?
46. Is the following slicing technique right? >>tuple[-4]
47. Which library is used to check the accuracy of a predictive model in sklearn?
48. How can you view only keys in a basic data structure dictionary?
49. Which of the following is a useful technique to reduce the number of dimensions from 5 to 3?
50. in method returns a boolean value.


  • Will this practice test helps in clearing the actual certification exam?

    Yes, this practice test gives you a simulated test like environment as you would experience in the actual test. The questions in the practice test are much like the questions of the Data Science certification exam.

  • What is included in this practice test?

    This Data Science with Python mock test consists of 50 questions that are to be solved in 60 minutes. You can pause the test if required and continue it afterward.

  • What is the Data Science with Python Practice Test?

    The Data Science with Python Practice Test is the is the model exam that follows the question pattern of the actual Python Certification exam. It contains a total of 50 questions that will test your Python programming skills. It aims to testify your knowledge of various Python packages and libraries required to perform data analysis.

  • Can I retake this Practice Test?

    Yes, you can re-take the practice test to know where you should improvise and how to manage time. Make sure that you take the test after thorough preparation to get the accurate feedback.

  • Who can take up this Data Science with Python Certification mock test?

    This data science mock exam is free of cost and ideal for those who wish to pass the real Python Certification exam and become a certified data scientist.

  • Are these the same questions I'll see on the real exam?

    Yes, the questions included in the practice resemble the ones that are expected to be seen in the actual data science with Python certification exam.

  • What will I learn from this practice test?

    A total of 50 data science related questions included in the mock test will testify your proficiency in data science and analytical techniques using Python. With the help of this practice test, you can differentiate your strong areas with the weaker ones among the different topics of Python programming, machine learning, data analytics, web scraping, data visualization, and natural language processing.

  • I didn’t do well on this practice test. What should I do now?

    You can go for multiple attempts to gauge your actual potential in the field of data science. However, if you seek a better learning path for understanding Python, you can go through our Python for Data Science Certification Training Course.

  • What are the requirements to take this practice test?

    This practice test can be taken without any particular condition.

  • Will the Practice Tests be updated frequently?

    Yes, we take the responsibility of upgrading our practice tests so that the candidates can find all the necessary latest information included in it.

  • Disclaimer
  • PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, and OPM3 are registered marks of the Project Management Institute, Inc.