Research Methodology

CCS NIAM Launched Online Certified Course in Research Methodology

To equip students with the skills necessary to conduct scientific research effectively

Understand how to design studies, collect and analyse data, interpret results, and draw meaningful conclusions.
Teach ethical research practices and critical thinking skills, enabling students to scrutinise various sources and types of information.
Cover fundamental concepts in research methodology, such as research design, data collection and analysis, ethical considerations, and writing and publication processes crucial for producing reliable and valid research findings

Enrolled students will get a chance to:

create research proposals, conduct pilot studies, or analyse case studies.
utilise online forums or discussion boards to discuss topics, share ideas, and solve problems collaboratively
use online quizzes, peer reviews, and regular feedback to assess and enhance student learning.
access multiple test series on different topics to understand contemporary research methodologies
avail revision classes.
avail live doubt classes once a week to help aspirants clear their doubts.
The course is mapped with AI and data science use to provide insights into advanced topics and current trends in research.
Students will get access to live classes for the first time and then recorded content with practice tests attached to every lecture.
CCS NIAM will conduct the final test for certification approval.

Day	Topic	Details
1	Introduction to Research	Overview of research; AI's impact.
2	Defining the Research Problem	Identifying questions; AI tools for problem identification.
3	Literature Review	Effective search strategies; AI-driven tools.
4	Research Design	Types of designs; AI's role.
5	Sampling Techniques	Methods; AI applications in sampling.
6	Data Collection Methods	Traditional vs. AI-enhanced methods.
7	Data Analysis - Quantitative	Statistical methods; AI algorithms.
8	Data Analysis - Qualitative	Thematic analysis; AI tools for data.
9	Research Ethics	Considerations in research; AI and ethics.
10	Writing Research Proposals	Proposal structure; AI writing tools.
11	AI in Research Simulation	Practical AI session; case study analysis.
12	Data Visualization	Techniques and tools; AI-enhanced visualization.
13	Publishing Research Findings	Selecting platforms; AI in manuscript preparation.
14	Peer Review and Feedback	The peer review process; AI for feedback.
15	Future Trends in AI-driven Research	Emerging technologies; preparing for AI advancements.

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