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Home / Generative AI (Gen AI) / Generative AI Certification Course Online
The vibrant IT sector in India, which consists of both well-established companies and rapidly growing startups, is leading the way in integrating AI across several disciplines. The adoption of AI-driven solutions by well-established organisations in the banking, e-commerce, and industrial sectors is indicative of this continuous movement. At the same time, entrepreneurs are using cutting-edge AI applications to upend established sectors and create a thriving ecosystem for technical developments. Keeping up with the changing startup scene and keeping an eye on India's tech news can provide you with insights into the newest developments in artificial intelligence. The government, business, and academic community working together to promote research into artificial intelligence (AI) will further establish India as a centre for cutting-edge AI innovation.
INR 110,000 80,000
With the use of Generative AI, fresh artificial content or data, such as images, videos, music, and even 3D models, may be produced without the need for human labour. The emergence of Generative AI is a result of LLM developments. Large datasets & patterns are the basis for training and learning the datasets and designs within the data for Generative AI models. Similar to the training data, they are able to produce fresh instances. Without any guidance from humans, these models are able to produce new material. To put it simply, it entails utilising AI models that have been trained to recognise various patterns and structures in existing data in order to produce new, unique data. What is Generative AI? A sort of artificial intelligence known as generative artificial intelligence (Generative AI) is capable of producing original ideas and information, such as dialogues, tales, pictures, movies, and music. In non-traditional computer tasks like image identification, natural language processing (NLP), & translation, artificial intelligence (AI) technologies aim to emulate human intellect. The next development in artificial intelligence is Generative AI. It may be trained to study any complicated topic, including biology, chemistry, art, and computer languages. It applies training data reuse to fresh issue solving. For instance, it is capable of processing words to form a poem and learning the English language. Generative AI may be used by your company for a number of tasks, including chatbot development, media production, and product design and development. Course Objective The Generative AI and Prompt Engineering course is designed to guide the participants through the foundational concepts of the Neural network models' journey to solve complex problems. The Evolution of Large Language Models has provided ground-breaking solutions for businesses. You will learn to leverage the existing solutions by getting a deep understanding of the current LLM architectures, variants, and challenges. This course exposes the practical applications of Generative AI solutions in various domains like Healthcare, Manufacturing, Marketing, etc.
Determine which issues can be solved with artificial intelligence approaches. Utilise a few fundamental AI techniques and assess if more sophisticated ones are applicable. Take part in the creation of intelligent systems that absorb knowledge from their experiences. The main goals of Generative AI include the creation of fresh, unique material, designs, chat answers, synthetic data, and even deepfakes. It is especially useful for addressing new problems and in creative domains since it can produce a wide variety of new outputs on its own. Content may be tailored to each user's preferences thanks to generative artificial intelligence. AI algorithms are able to create personalised learning materials that are tailored to your individual learning style through the analysis of learning patterns and preferences. This enables improved comprehension and engagement.
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It's critical to understand what Generative AI means before beginning to utilise it. Drawing on the collaborative efforts of scholars and technologists from many domains, our interpretation of the word encompasses the use in artificial intelligence to generate content (such as text, graphics, or presentations) in reaction to user-inputted prompts. The objective of this wide definition is to reflect the rapidly expanding variety of technologies being developed for these reasons. Furthermore, Generative AI is distinct from other kinds of AI in that it uses predefined data sources to generate material in response to a specific prompt. Other forms of AI are employed in a number of contexts, such as gaming, information curation, and vehicle operation.
Artificial intelligence (AI) is still developing quickly as we head into the fourth industrial revolution, with Generative AI setting the standard for innovation and change. We may anticipate innovative breakthroughs that will transform industries, elevate our daily lives, and revolutionise creative processes in 2024 and beyond. The following are the main ways that Generative AI is changing marketing and sales operations: Automated repetitive duties, such as keyword research, administrative work, content formatting, as well as data analysis; Sales enablement and customised materials; Exceptionally fast sales and marketing content generation. The applications of Generative AI are virtually endless, ranging from personalised content to AI-powered healthcare & climate change mitigation. Nonetheless, it's critical to approach these developments cautiously in light of the moral and legal ramifications.
Businesses, academics, and governments must collaborate as we traverse this exciting AI-driven future to make sure that AI technologies handle any concerns and benefit society as a whole. By doing this, we can fully use the promise of Generative AI to enhance our quality of life, spur innovation, and build a more just and sustainable society.
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The course on Generative AI could have a different length. Generally, it can take anything from a few weeks to many months, depending on how in-depth and complicated the programme is.
A background of computer science, mathematics, and a related discipline is frequently advised, however eligibility requirements may differ. It might help to have a basic understanding of programming and machine learning techniques.
Yes, many courses are designed to accommodate beginners. However, it's advisable to review the course prerequisites to ensure a foundational understanding of relevant concepts.
Yes, most Generative AI courses offer a certificate upon successful completion. This certificate can be a valuable asset to showcase your skills and knowledge in the field.
The cost of the course may vary depending on the platform or provider. It is recommended to check the official website & contact the course provider for accurate cost information.
Some institutions may offer scholarships or financial aid. It's advisable to inquire with the course provider about available options and application procedures.
Many Generative AI courses offer placement assistance, which may include resume building, interview preparation, and job placement support. Details regarding placement assistance can be obtained from the course provider.
The flexibility of the course may vary. Some courses offer part-time options to accommodate individuals with other commitments, while others may be full-time programs.
Generative AI courses often include hands-on projects to apply theoretical knowledge. These projects may involve creating generative models, working with real-world datasets, and solving practical problems.
Many Generative AI courses provide a platform for students to interact, discuss concepts, and collaborate on projects. This fosters a sense of community and allows for networking opportunities.
The course may cover programming languages such as Python and tools like TensorFlow, PyTorch, or other frameworks commonly used in Generative AI. Familiarity with these tools is often beneficial for successful completion of the course.
Some Generative AI courses may have specific hardware or software requirements. This could include a certain level of computational power for running complex models. Ensure that your system meets the specified requirements before enrolling.
Many Generative AI courses are offered online, allowing participants to access lectures and materials remotely. Some courses may also offer in-person sessions or a hybrid model. Check the course details for specific information on the mode of delivery.
Most courses provide access to course materials, including lectures and resources, even after completion. This allows you to review the content for future reference and stay updated on emerging trends in Generative AI.
Assessments and exams are common components of Generative AI courses. These evaluations may include quizzes, assignments, and a final project. Understanding the assessment structure is crucial for successful course completion.
Some courses allow for flexibility in scheduling, allowing participants to pause and resume their studies. Extensions may also be available in certain circumstances. It's important to check the course policies regarding pauses and extensions.
Some platforms may offer a trial period or provide access to a demo version of the course. This allows prospective students to explore the course structure and content before making a commitment.
Generative AI courses typically provide support through forums, discussion groups, or dedicated channels where participants can seek help from instructors or interact with fellow students. Understanding the available support channels is important for a smooth learning experience.
The course may prepare participants for various roles in the field of artificial intelligence, such as machine learning engineer, data scientist, or AI researcher. Understanding the potential career paths can help align your expectations with the goals of the course.
Considering how quickly artificial intelligence is developing, it's critical to understand if the course material is updated often to reflect the most recent advancements in Generative AI. Courses that place a high priority on being up to date offer more worthwhile and relevant learning opportunities.
Generative AI jobs involve various roles and expertise levels, including theoretical research, machine learning model development, data analysis, predictive modeling, and software solutions. They also focus on ethical implications, market management, and AI-driven products. The field is interdisciplinary, requiring individuals with backgrounds in computer science, mathematics, statistics, engineering, and related fields. Roles can vary based on industry, with applications in healthcare, finance, gaming, and art. As AI advances, new roles and specializations will emerge, offering a broad spectrum of career possibilities.
Generative AI professionals' salaries can vary significantly based on factors like experience, location, skills, education, and industry. Entry-level professionals can expect salaries ranging from $60,000 to $100,000 per year. Mid-level professionals can earn between $100,000 and $150,000 annually. Those with significant experience, specialized skills, or leadership roles can command salaries of $150,000 to $250,000 or more, especially in tech hubs or high-demand areas. These figures are approximate and can be influenced by location, demand, company financial standing, and expertise.
India is witnessing a surge in Generative AI projects, with companies and research institutions collaborating with industry and government. Infosys, a leading IT firm, has invested in AI-powered solutions, including generative models, for various industries. Wipro's HOLMES platform also uses Generative AI for various applications. Sigmoid, another Indian AI company, focuses on AI solutions for marketing, finance, and healthcare. Niramai uses AI for early breast cancer detection. Accenture, a global consulting firm, has AI labs in India for global clients. The AI landscape in India is rapidly evolving, with startups and research institutions contributing to AI projects in various sectors.
Open source tools are crucial in advancing Generative AI research and development by democratizing access to resources, fostering collaboration, and accelerating innovation. They make advanced AI techniques accessible to a wider audience, encouraging experimentation and learning. Open source projects thrive on community contributions, allowing developers to share ideas, contribute code, and improve tools. This collaborative effort often leads to rapid advancements and innovations, pushing the boundaries of Generative AI.
Generative AI offers various training modes, combining theoretical understanding with hands-on practice. Connecting with professionals, finding mentors, participating in AI hackathons, and watching lectures on it can provide valuable insights. Engaging in AI-related competitions and hackathons can also enhance practical application.
Generative AI is utilized in various industries for creating, simulating, and generating new content. It can test autonomous vehicles without physical prototypes, generate scripts, music, art, and special effects for movies, games, and music compositions, and recommend content based on user preferences
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