Research in Computing - Made Simple
Research in Computing
Teaching and Academics ,Other Teaching & Academics,Research Methods
Lectures -29
Duration -1.5 hours
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Course Description
This course is designed to introduce students to the principles and practices of conducting research in the field of computing. It provides a structured framework for students to explore advanced topics, develop critical research skills, and engage in independent or group research projects.
Goals
- Understand the research process in the field of computing, including problem identification, literature review, hypothesis development, data collection, and analysis.
- Develop critical thinking and problem-solving skills necessary for designing and executing research projects.
- Gain familiarity with various research methodologies and tools commonly used in computing research.
- Learn how to critically evaluate and synthesize existing research literature.
- Plan and execute an independent or group research project in a specific area of computing.
- Effectively communicate research findings through written reports and oral presentations.
- Develop ethical guidelines and awareness for responsible conduct in research.
Prerequisites
None

Curriculum
Check out the detailed breakdown of what’s inside the course
Full Practical List
29 Lectures
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RIC Practical List 02:16 02:16
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Write a program for obtaining descriptive statistics of data 04:00 04:00
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Write a program for obtaining descriptive statistics of data in Excel 02:58 02:58
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Import data from different data sources (from Excel, csv, mysql, sql server, oracle to R/Python/Excel) 03:25 03:25
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RIC Practical 01B Excel to Python 02:33 02:33
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Practical 02 B Analyze Data 05:28 05:28
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Practical 03 A 1 Sample t Test 03:31 03:31
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Practical 03 B 2 Sample t Test 07:07 07:07
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RIC Practical 03 B 2 Sample t Test Python 03:26 03:26
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Practical 03 B 2 Sample t Test Practice 07:52 07:52
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Practical 03 C Paired t Test 03:15 03:15
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Practical 04 A Chi Squared 05:05 05:05
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Practical 04 A Chi Squared Practice 04:06 04:06
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Practical 04 A Chi Squared Independence 06:23 06:23
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Practical 04 B Chi Squared Independence Python 02:25 02:25
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RIC Practical 05 A Z test 01:45 01:45
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RIC Practical 05 B Z test Two samples 02:02 02:02
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RiC Practical 06 A One way ANOVA.mp4 02:20 02:20
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RIC Practical 06 A One way ANOVA Excel 01:53 01:53
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RIC Practical 06 B Two way ANOVA Python 00:54 00:54
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RIC Practical 06 B Two way ANOVA Excel 01:37 01:37
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RIC Practical 06 C MANOVA Python 00:56 00:56
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Practical 08 A Positive Correlation 00:50 00:50
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Practical 08 B Negative Correlation 00:40 00:40
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RIC Practical 08 C No Correlation 00:43 00:43
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RIC Practical 09 B Poly Regression 01:06 01:06
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RIC Practical 10 A Multi Linear Regression 00:55 00:55
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RIC Practical 10 B Logistic Linear Regression 00:18 00:18
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Sample question sets 11:30 11:30
Instructor Details

Pushpa Mahapatro
Currently, Mrs. Pushpa Mahapatro is a faculty member in the Department of Information Technology at Vidyalankar School of Information Technology, Wadala East, Mumbai -37. Mrs. Pushpa Mahapatro's extensive knowledge and practical experience in Bioinformatics, AI and machine learning make her a highly qualified author for this research paper. Her contributions are integral to the discussion of the technical aspects and ethical considerations of the research paper.
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