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Generative AI, also known as generative adversarial networks (GANs), is a subset of artificial intelligence that focuses on generating new content, such as images, videos, music, or text, using machine learning algorithms. Here are five key points about generative AI:
- Principle: Generative AI works on the principle of using two neural networks, the generator and the discriminator, which work in tandem. The generator generates new content, while the discriminator evaluates the content and provides feedback to the generator. This feedback loop helps the generator improve its output over time.
- Creative Content Generation: Generative AI can be used to create realistic and high-quality content, such as lifelike images, by training the generator on a large dataset of existing content. The generator can then generate new content that closely resembles the patterns and styles learned from the training data.
- Applications: Generative AI has found applications in various domains. It can be used in art and design to generate unique visuals, in entertainment to create virtual characters or enhance special effects, in medicine for synthetic data generation or drug discovery, and in natural language processing to generate human-like text or dialogue.
- Challenges: Training generative AI models can be challenging due to issues like mode collapse, where the generator fails to explore the entire space of possible outputs, and training instability. Researchers are continuously working on addressing these challenges to improve the quality and reliability of generative AI.
- Ethical Considerations: The ability of generative AI to create highly realistic fake content raises ethical concerns. It can be misused for generating deepfake videos, fake news, or other forms of malicious content. Ensuring responsible use and addressing the potential for misuse are important considerations in the development and deployment of generative AI systems.
Generative AI holds great potential for creative applications and innovation. However, it also requires responsible development and usage to address ethical concerns and mitigate potential risks.
1. Why are you applying for Financial Aid? (150 words minimum required)
Ans: I’m a student from India and want to learn IBM Data Science. I think it will be beneficial for my work. But I’ve no job of my own to carry the expenses to pay for the certificate of this course. I live only for my scholarship, it is very much difficult for me to gather such an amount of money for the certificate. Financial Aid will help me take this course without any adverse impact on my monthly essential needs. So I’m badly in need of this financial aid. I want to take this course as I want to learn. This course will boost my job prospects after graduation from my institute. It will help me perform better in understanding and learning this technology and give me an edge over my competitors. A verified certificate will attach credibility to the certificate I receive from this course. I plan to complete all assignments on or before time as I have done in previous Signature Track Courses. Also, I intend to participate in Discussion Forums, which I have found to supplement my learning immensely in the other online courses I have taken on Coursera. I also plan to grade assignments that are peer-reviewed which I believe will be an invaluable learning opportunity.
2. How will taking this course help you achieve your career goals? (150 words minimum required)
Ans: My main career goal is to learn every day. I really want to learn and progress in my career. Programming requires constant learning and improvement. Taking this course will help me to learn and study Data Science and also implement it. It can help me advance my knowledge. This course will help me in defining Data Science, understand how Python could potentially impact our business and industry, write a thought leadership piece regarding use cases and industry potential of Data Science, explain Data Science to clients, and friends, join a community of economists, business leaders, entrepreneurs, and technologists that are shaping this technology as we speak. Identifying which aspects of Data Science seem most important and relevant to us, Walking away with a strong foundation in where Data Science is going, what it does, and how to prepare for it. The Data Science course will help me achieve it to learn. Courses on Coursera helped me to greatly increase my programming knowledge in the past.
Would you consider using a low-interest loan to pay for your courses?
Selected: NO
3. If you answered no, please help us understand why.
Ans: I don’t possess a good financial condition at this stage to afford this course for the above-mentioned reasons. I don’t have enough money to invest in my education, I can invest only my time now.
Conclusion
Coursera has made it easier to get through their courses and programs using financial aid, this is beneficial to anyone who cannot afford to pay for it genuinely. Coursera will normally approve your request and hope you finish the course.
How To Apply
COURSE LINK-: Apply Here
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