What you'll learn
Continuous research in methodology refines quantitative and qualitative research techniques, enhancing their accuracy, validity, and reliability.
This enables researchers to gain a more comprehensive understanding of a phenomenon by utilizing the strengths of both methods.
Improved guidelines and frameworks for ensuring the reproducibility of research results have emerged, emphasizing the importance of replicating studies to valid
The development of methodologies that cater to interdisciplinary research, allowing different fields to collaborate and merge methodologies
Requirements
None
Description
Research in computing is a diverse and dynamic field that encompasses a wide range of disciplines, from artificial intelligence and machine learning to cybersecurity, quantum computing, and more. It's a field that continuously evolves, driven by the pursuit of innovation, problem-solving, and the exploration of new frontiers.Cybersecurity is another critical domain within computing research. As technology advances, so do the methods and complexities of cyber threats. Researchers work on developing robust encryption methods, intrusion detection systems, and other security measures to safeguard data and systems.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.What will you learn in this course: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.
Overview
Section 1: Research In Computing Practical List
Lecture 1 Practical List
Lecture 2 Write a program for obtaining descriptive statistics of data
Lecture 3 Write a program for obtaining descriptive statistics of data in Excel
Lecture 4 Import data from different data sources (from Excel, csv, mysql, sql server, ora
Lecture 5 RIC Practical 01B Excel to Python
Lecture 6 Practical 02 B Analyze Data
Lecture 7 Practical 03 A 1 Sample t Test
Lecture 8 Practical 03 B 2 Sample t Test
Lecture 9 RIC Practical 03 B 2 Sample t Test Python
Lecture 10 Practical 03 B 2 Sample t Test Practice
Lecture 11 Practical 03 C Paired t Test
Lecture 12 Practical 04 A Chi Squared
Lecture 13 Practical 04 A Chi Squared Practice
Lecture 14 Practical 04 A Chi Squared Independence
Lecture 15 Practical 04 B Chi Squared Independence Python
Lecture 16 RIC Practical 05 A Z test
Lecture 17 RIC Practical 05 B Z test Two samples
Lecture 18 RiC Practical 06 A One way ANOVA
Lecture 19 RIC Practical 06 A One way ANOVA Excel
Lecture 20 RIC Practical 06 B Two way ANOVA Python
Lecture 21 RIC Practical 06 B Two way ANOVA Excel
Lecture 22 RIC Practical 06 C MANOVA Python
Lecture 23 Practical 08 A Positive Correlation
Lecture 24 Practical 08 B Negative Correlation
Lecture 25 RIC Practical 08 C No Correlation
Lecture 26 RIC Practical 09 B Poly Regression
Lecture 27 RIC Practical 10 A Multi Linear Regression
Lecture 28 RIC Practical 10 B Logistic Linear Regression
Lecture 29 Sample question sets
Students interested in Research



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