MCQ for Data Science Users

This book is a comprehensive manual created to assess and improve your comprehension of many concepts and methodologies in data science. The course encompasses a broad spectrum of subjects, such as data preprocessing, Machine Learning techniques, data visualization, statistical analysis, and additional topics. Every chapter is organized with a series of multiple-choice questions that test your understanding and allow you to evaluate your expertise in the subject. 

The book's objective is to offer a pragmatic and captivating approach for readers to enhance their proficiency in data science through practical exercises. The book provides an extensive examination of several subjects in data science, encompassing data preprocessing, statistical analysis, Machine Learning techniques, data visualization, and additional areas.

This extensive knowledge helps readers acquire a full and all-encompassing comprehension of the subject matter. The chapters in this book adhere to a structured framework, which includes multiple-choice questions that enable readers to assess their understanding and grasp of the content. 

KEY FEATURES  

• Comprehensive coverage of data science concepts and features.
• Multiple-choice questions to test and assess knowledge effectively.
• Over 5000 multiple-choice questions for practice.

WHAT YOU WILL LEARN

• Mastering data science concepts through multiple-choice questions.
• Strengthening problem-solving skills by practicing diverse scenarios.
• Interpreting the results of data analyses and Machine Learning models effectively.
• Evaluating the performance of different Machine Learning models using metrics.
• Developing critical thinking skills to assess the suitability of various data science approaches.
• Preparing for exams, interviews, and quizzes, etc.

WHO THIS BOOK IS FOR

This data science MCQ book is perfect for anyone looking to test and improve their knowledge of data through multiple-choice questions.

1. Fundamental of Data Science and Data Analytics
2. Data Science Tools and Applications
3. Fundamentals of Programming
4. Introduction to Python Programming
5. Data Analysis: NumPy and Pandas Library
6. Data Visualization: Matplotlib and Seaborn Library
7. Data Structures and Algorithms
8. Database Management and Warehousing
9. Data Acquisition, Data Mining and Big Data
10. Data Pre-processing and Feature Engineering
11. Probability and Statistics
12. Linear Algebra
13. Calculus and Optimization
14. Artificial Intelligence
15. Machine Learning
16. Deep Learning
17. Pattern Recognition and Knowledge Representation
18. Natural Language Processing and Text Analytics
19. Web Analytics and Mining
20. Computer Vision

Dr. Dhananjay Bisen is an Assistant Professor in the Centre for Internet of Things, Madhav Institute of Technology and Science, Gwalior. He completed his Ph. D. from Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, Madhya Pradesh (2019). He received B.Tech Degree from Government Engineering College Jabalpur, Madhya Pradesh (2007) and M.Tech from School of Information Technology, Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, Madhya Pradesh (2009). He has been teaching since 2010 and guiding M.Tech students. In the meantime, he has authored 1 book and published more than 30 research papers in the journals of international repute in the area of Machine Learning, Deep Learning and Human Activity Recognition, and so on. He has attended various short-term training programmes, refresher courses, workshops, seminars and conferences in India.

Dr. Neeraj Sahu is working in G H Raisoni University, Amravati, Maharashtra. He received the Ph.D. degree in Computer Science and Engineering from the Singhania University, Rajasthan, India, in 2014. He is currently working as an Assistant professor in G H Raisoni University, Amravati, Maharashtra, India. His research interests include Data Mining, E-Commerce, Voice Recognition,Cyber Crime and Network Security.

Dr. Brijesh Bakariya is an Assistant Professor in the Department of Computer Science and Engineering, I.K. Gujral Punjab Technical University (IKGPTU) Campus Hoshiarpur, Punjab . He completed his Ph. D. from Maulana Azad National Institute of Technology (NIT- Bhopal), Madhya Pradesh (2016). He received MCA Degree from Devi Ahilya Vishwavidyalaya, Indore, Madhya Pradesh (2009). He has been teaching since 2009 and guiding M.Tech/Ph.D. students. In the meantime, he has authored 3 books and published more than 30 research papers in the journals of international repute in the area of Data Mining, Machine Learning, Deep Learning, Image Processing, Human Activity Recognition, and so on. Currently, He supervised three Ph.D. scholars and three are working with him. He has attended various short-term training programmes, refresher courses, workshops, seminars and conferences in India.