(Valid For First 1000 Enrollment)
Variational, Generative, Adversarial, Genetic Algorithm & Bayesian Inferences: Beginners Course on Machine Algorithms
Teaching & Academics | Other Teaching & Academics | Udemy |
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This course will provide a prospect for participants to establish or progress their considerate of optimization algorithms through critical examination of research process, approaches and publishing dimensions.
The course introduces elements of the research process within quantitative, qualitative, and mixed methods domains. Participants will use these underpinnings to begin to critically understand design thinking, large scale optimization, graph mining and hashing algorithms. They would be able to develop understanding to formulate a research question and answer it by framing an effective research methodology based on market algorithms. Furthermore, they would learn to derive meaningful inferences using Google analytics and disruptive research and innovative strategies.
They would be able to report and publish a papers in renowned journals, conferences and to foster technical reports in their areas of interest.
Design Thinking Using Immersion and Sense Making.
Large Scale Graph Mining.
Hashing Algorithms.
Marketing Algorithms.
Disruptive Strategy for Innovation.
To familiarize with research terminology.
Be aware of the principles of research, ethical challenges and approval processes.
Describe quantitative, qualitative and mixed methods approaches to research.
Identify the components of a literature review process.
Critically analyze published research.
Able to write, submit and publish technical, scientific and review paper.
Research Publishing Ethics including data privacy, informed consent and declaration of competitive interests.
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