Honors in Generative AI
Generative AI
Enquire now: 9480223900
why choose Generative AI?
Learn Generative AI, Python Programming, AI Applications, Prompt Engineering, Machine Learning, AI Ethics, and more.
Earn Professional Certificates from Google Cloud and IBM in Generative AI.
Gain skills for developing AI-driven applications and chatbots through practical case studies and project work.
Immerse in project-based learning through Capstone projects
Platform and tools to learn - Google Cloud, OpenAI APIs, Python, Vertex AI, GitHub Copilot, Microsoft Excel for AI automation, and more.
Access to career resources - resume review, interview prep, career support on pathway completion
Accelerate your career with an Honors Degree
Online / 18 credits / Self-paced learning
Criteria
B.E / BTECH students in their 5th sem onwards who want to diversify their careers in the industry
Lectures from renowned subject matter experts from leading academia and industry across the world
Built in hands-on environment for practical implementation of the technologies covered with capstones.
Unlimited access to Coursera's catalog of 7,000+ world-class courses, hands-on projects, and job-ready
What will you learn from the program?
Total credits earned : 18 credits, 270 hours of learning
Gain skills for developing AI-driven applications and chatbots through practical case studies and project work.
Platform and tools to learn - Google Cloud, OpenAI APIs, Python, Vertex AI, GitHub Copilot, Microsoft Excel for AI automation, and more.
Key Learnings: Generative AI, Python Programming, AI Applications, Prompt Engineering, Machine Learning, AI Ethics, and more.
Immerse in project-based learning through Capstone projects
Access to career resources - resume review, interview prep, career support on pathway completion
Curriculum
The courses offer a deep dive into the realm of generative AI, covering foundational concepts, applications, and ethical considerations. They emphasize the development of skills in Python programming, prompt engineering, and deploying AI in cloud environments like Google Cloud. The pathway explores the use of AI in creating engaging content, managing projects, and enhancing business strategies. It also includes specific training for developing AI-powered web applications, chatbots, and software writing assistance. Additionally, the courses address the critical aspects of ethical AI use, responsible implementations, and the construction of trust within AI systems. These courses are designed to prepare learners for roles such as AI developers, project managers in AI projects, and specialists in AI-driven content creation. The completion of these courses provides learners with the expertise to harness AI technologies effectively in various professional contexts.
Generative AI
Generative AI for Everyone
- In the Generative AI for Everyone course, led by AI pioneer Andrew Ng, students gain a comprehensive understanding of generative AI: how it operates, its capabilities, and its limitations. Practical hands-on exercises provide experiences in using generative AI. Key takeaways include insights into what generative AI can achieve, its potential, its constraints, and its real-world applications. Active engagement in generative AI projects enables learners to apply their knowledge practically, understanding its impact on business and society. The course aims to ensure that everyone can participate in our AI-driven future.
Innovating with Google Cloud Artificial Intelligence
- This course forms part of the Google Cloud Digital Leader Training Professional Certificate, aiming to impart a foundational understanding of industry-relevant subjects and tools. Upon enrollment, learners embark on a journey to acquire new concepts from industry experts and develop job-relevant skills through hands-on projects. Successful completion of the course earns the learner a shareable career certificate from Google Cloud, underlining their enhanced proficiency and knowledge in the particular field.
Introduction to Generative AI Studio
- Enrollment in this course also provides access to the Generative AI for Developers Specialization. The course aims to impart new concepts from industry professionals and establish a solid foundation in the subject or tool it covers. Emphasis is placed on building job-relevant skills through hands-on projects. Successful completion of the course results in a shareable career certificate.
Generative AI: Introduction and Applications
- The course is tailored for a wide audience, including professionals, executives, students, and enthusiasts interested in understanding and utilizing generative AI. It serves as an introduction to the capabilities of generative AI, underscored by various models including large language models (LLMs). Participants will learn about generative AI's fundamentals and its evolution, exploring its applications in domains such as text, image, audio, video, virtual worlds, code, and data. The course also illuminates generative AI's applications across diverse sectors and industries and familiarizes learners with common generative AI models and tools, including GPT, DALL-E, Stable Diffusion, and Synthesia. Includes hands-on labs provide opportunities for learners to investigate the use cases of generative AI through the IBM Generative AI Classroom and popular tools like ChatGPT. Learners will also gain insights from practitioners about the capabilities, applications, and tools of generative AI.
Generative AI: Prompt Engineering Basics
- This course, suitable for professionals, students, and enthusiasts, introduces prompt engineering techniques to maximize generative AI tools like ChatGPT. Participants learn to guide AI models effectively, mastering techniques like zero-shot and few-shot to enhance the quality of large language models. They explore prompt strategies, including the Interview Pattern, Chain-of-Thought, and employ commonly used tools like IBM WatsonX Prompt Lab and Spellbook. Through hands-on labs in the IBM Generative AI Classroom, learners practice crafting effective prompts and gain insights from industry experts.
Prompt Engineering for ChatGPT
- This course aims to provide expertise in using generative AI tools like ChatGPT, highlighting their potential in tasks such as tutoring, meal planning, or software development. The course features the emergent intelligence and reasoning capabilities of these AI tools, demonstrating how they can enhance everyday productivity. Usage of natural language prompts to instruct large language models is emphasized, noting that while these models have the potential to disrupt various fields, many users lack the skills to write effective prompts. This course introduces patterns and approaches to crafting effective prompts, progressing from basic to sophisticated tactics. Successful completion equips students with robust prompt engineering skills, enabling the use of large language models for a wide array of tasks in various domains.
AI Foundations: Prompt Engineering with ChatGPT
- The prompt engineering course, developed by Andrew Maynard, a specialist in transformative technologies, allows students to explore ChatGPT and Large Language Models (LLMs). It equips students with skills to evaluate and construct effective prompts, thereby harnessing the full potential of ChatGPT. The curriculum includes modules on prompt templates, creative prompt structures, and prompt design for various tasks and applications. The course is accessible to all learners without requiring specific engineering skills, focusing instead on clear and creative language use. This makes it particularly relevant for students in fields like English, languages, humanities, and social sciences.
Introduction to Generative AI
- This beginner-friendly course offers a comprehensive introduction to generative AI. Starting with a high-level understanding of what generative AI is, the course progresses to teach essential skills like crafting effective prompts and refining generated outputs through interactive lessons and hands-on examples. It takes a deep dive into major generative AI models, exploring their unique capabilities and limitations. Learners will gain practical experience using leading systems such as GitHub Copilot, DALL-E, and OpenAI for generating code, images, and text. The course prepares beginners to experiment with generative AI responsibly and effectively for various applications, setting the stage for further exploration of this rapidly evolving technology.
Introduction to AI and Machine Learning on Google Cloud
- This course introduces the artificial intelligence (AI) and machine learning (ML) offerings on Google Cloud that support the data-to-AI lifecycle through AI foundations, AI development, and AI solutions. It explores the technologies, products, and tools available to build an ML model, an ML pipeline, and a generative AI project based on the different goals of users, including data scientists, AI developers, and ML engineers.
Introduction to Large Language Models
- This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps.
Generative AI with Large Language Models
- Generative AI with Large Language Models (LLMs) is an intermediate-level course that delves into the fundamentals of generative AI, including its deployment in real-world scenarios. Upon completion of the course, learners will understand generative AI, transformer architecture, and how LLMs are trained. Practical skills include optimizing models using empirical scaling laws and applying advanced training, tuning, and deployment methods. Course material highlights industry challenges and opportunities through case studies by industry professionals. This course, beneficial for developers, equips learners with the knowledge to make informed decisions and create functional prototypes effectively. The course requires Python coding experience, familiarity with machine learning basics, and potentially previous completion of the Machine Learning or Deep Learning Specialization from DeepLearning.AI.
Rust for Large Language Model Operations (LLMOps)
- This innovative course prepares learners to become Rust developers at the cutting edge of the AI revolution. It provides in-depth training in Large Language Model Operations (LLMOps) using Rust, focusing not just on an overview, but thoroughly exploring the integration of Rust with advanced LLM frameworks such as HuggingFace Transformers. The course also covers the effective deployment of these extensive models on cloud infrastructures like AWS, concurrent with the application of DevOps methodologies specific to LLMOps.
Amazon Bedrock - Getting Started with Generative AI
- Amazon Bedrock is a fully managed service that makes foundation models (FMs) from Amazon and leading artificial intelligence (AI) startups available through an API. In this course, you will learn the benefits of Amazon Bedrock. You will learn how to start using the service through a demonstration in the Amazon Bedrock console. You will also learn about the AI concepts of Amazon Bedrock and how you can use the service to accelerate development of generative AI applications.
Amazon CodeWhisperer - Getting Started with Generative AI
- In this course, you will learn the benefits and technical concepts of CodeWhisperer. If you are new to the service, you will learn how to start interacting with CodeWhisperer through Visual Studio Code, JetBrains PyCharm, and AWS Lambda. You will also learn how the built-in features can help you streamline code writing.
Rust for DevOps
- Rust For DevOps is an intermediate level course targeted towards software engineers, system administrators, and technical professionals. Designed for those with beginner-level programming experience and familiarity with Linux, Git, and Docker, it offers practical Rust skills for building, deploying, and monitoring applications using DevOps workflows. Through video lessons and coding exercises, learners will implement containerization, automate routine administration tasks, and ensure code observability. Upon completion, they will possess the Rust and DevOps skills necessary to develop robust, large-scale applications efficiently, irrespective of their specific technical role.
Coding with Generative AI
- With this comprehensive course, learn to expedite code development through efficient techniques. Dive into the intricacies of array manipulation. Elevate your programming skills by mastering the implementation of functions and classes, gain a keen eye for identifying and rectifying syntax errors, ensuring the integrity and quality of your code. And explore the nuances of semantic search with ChatGPT, distinguishing it from traditional search methods like StackOverflow's exact search.
Prompt Engineering for Web Developers
- Subpar results from AI language models, specifically ChatGPT and Google Bard can be improved with the right input. A better understanding of 'prompt engineering' can significantly enhance the outputs. There are numerous resources available on the topic, but this specific course homes in on teaching the art and science of prompt engineering, enhancing the usage of AI language models, and fortifying web development skills. The course aims at transmuting its students into skilled prompt engineers, who can harness AI language models like ChatGPT, making them the penultimate coding assistant and collaborative programming partner. It promises better planning, learning, generating, debugging and documenting the code, and exploring it like never before, with added challenges and recommendations for future learning.
Build AI Apps with ChatGPT, Dall-E, and GPT-4
- The course enables web developers to create applications utilizing OpenAI's API, marking their initiation as AI Engineers. Practical experience with GPT-4 and Dall-E APIs are incorporated using OpenAI's JavaScript SDK. The initial project, 'MoviePitch', introduces OpenAI API, channeling the power of AI to generate unique ideas and images. The second project, 'KnowItAll', employs the ChatGPT-4 model, focusing on the construction of chatbots - a typical AI application for web developers. The final project emphasizes fine-tuning the chatbot by uploading a dataset to OpenAI and training a model with it. This process equips the chatbot to answer queries specific to the provided data; an essential skill when handling AI.
Generative AI: Impact, Considerations, and Ethical Issues
- The course provides a thorough examination of the influence of generative artificial intelligence (AI) on society, workforce, organizations, and the environment, catering to a varied demographic including professionals, executives, policymakers, and students. It delves into essential components like the ethical, economic, and social consequences of generative AI and its responsible usage. It brings to light the ethical challenges faced with generative AI, notions of data privacy, biases, copyright violations, and hallucination, along with the potential misuses like deepfakes. The course also facilitates a detailed understanding of the requirements for responsible usage of generative AI, examining its wider impact on transparency, responsibility, privacy, and safety, along with its socioeconomic implications. Applicants get to learn about these considerations through real-life examples and cases, gaining insights from practitioners about the on-ground realities, limitations, and ethical considerations of generative AI.
Generative AI: Foundation Models and Platforms
- The course addresses enthusiasts and practitioners fascinated with the fast-evolving field of generative AI. It directs focus to the fundamental concepts and models underpinning generative AI. The course encompasses deep learning, large language models, GANs, VAEs, transformers, and diffusion models as integral building blocks. It familiarizes learners with the concept of foundation models and delves into the capabilities of pre-trained models and platforms for AI application development, demonstrating how foundation models utilize them to generate text, images, and code. Attention is dedicated to different generative AI platforms like IBM watsonx and Hugging Face. The course offers hands-on labs that allow exploration of generative AI use cases via the IBM generative AI classroom and platforms like IBM watsonx. It exposes learners to various models including IBM Granite, OpenAI GPT, Google flan, and Meta Llama while also providing insights from expert practitioners about generative AI capabilities, applications, and tools.
Generative AI: Business Transformation and Career Growth
- This succinct course enlightens learners about the transformative influence of generative AI on businesses and professionals. Designed to suit anyone keen on exploring business and career prospects presented by generative AI, it caters to an array of audiences including professionals across domains, executives, managers, startup founders, and students. The course navigates through the impact of generative AI on existing businesses and the potential for new ventures, instructing learners on preparing a business for the adoption of generative AI and its influence across various industries. It also presents potential career opportunities in generative AI and how it can boost career advancements by impacting and enhancing existing functions, skills, and job roles across sectors. It includes practitioner insights on current trends and future perspectives of generative AI and its potential to transform industries and redefine professions. The course culminates with provision for hands-on labs and a project for demonstration of skills and understanding of generative AI.
Responsible AI in the Generative AI Era
- This one-week microlearning course provides an introduction to the Principles of Responsible AI and how those principles align with the Generative AI or GenAI space. It also informs the learners about the various challenges that Generative AI brings. You will explore the fundamental principles of responsible AI, and understand the need for developing Generative AI tools responsibly. By the end of this course, you will be able to discuss the challenges posed by Generative AI and the principles of Responsible AI.
Trustworthy Generative AI
- News reports are often flooded with instances of Generative AI tools such as ChatGPT making mistakes and producing inaccurate information, primarily due to inappropriate usage by humans. Misinterpretation of Hallucination as a bug rather than a feature exposes underlying issues in problem-solving and risk assessments. This course addresses these concerns by teaching techniques to identify whether a problem aligns with Generative AI's capabilities, how to frame problems to minimize risk, the art of prompt engineering for trust, and ensuring human engagement at adequate levels. Students are equipped with practical insights on prompt designs, methods for output validation, utilization of Generative AI for creative ideation and augmentation of human skills, along with other ethically advantageous applications. Areas of learning include leverage of prompt engineering techniques for reliable outputs, mastery over output verification, problem-framing to mitigate risks, creative ideation application via generative AI, and generative AI utilisation to accentuate rather than replace human reasoning and imagination.
Leveraging AI for Enhanced Content Creation
- The course serves as a foundation for evaluating and employing a range of Generative Artificial Intelligence (AI) tools, namely ChatGPT, Bing Chat, Google Bard, Midjourney, Runway, and Eleven Labs. This educational pursuit ensures hands-on experience by driving learners through the phases of ideation, creation, and finalization of a simulated advertising campaign employing the collective strengths of these AI tools. It is crafted for content creators, marketing professionals, business strategists and anyone interested in harnessing the collective power of premier Generative AI tools for innovative content solutions. A basic comprehension of AI concepts and affinity for innovative content formation techniques are the prerequisites. The course aims to make learners adept at harnessing the potent features of these leading Generative AI tools, as evident from the creation of an inclusive advertising campaign, showcasing the smooth integration and elevated competencies of these tools in content creation.
Leveraging Virtual Assistants for Personal Productivity
- This beginner-friendly course introduces the concept of enhancing personal productivity using virtual assistants and chatbots in today's fast-paced world. It educates users about effectively utilizing AI-powered tools for task management and overall efficiency improvement. Post-completion, learners gain a deep understanding of these components, with insights into real-life applications like automating emails and scheduling appointments. Designed for a wide audience, it requires no prior coding knowledge, but familiarity with basic computer skills and software applications is essential. Taking the course empowers learners to optimize their productivity using AI-driven personal assistants.
Honours Degree from VTU University
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Program Fee
Paid |
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Application Process
Register to Honour/Minor degree by filling online application and by paying registration fee.
Get your online application approved.
Start enrolling to Honour/Minor degree program.
Admissons are closed once the requisite number of participants enroll for the upcoming cohort. Apply early to secure your seat.
Deadline:30-Apr-2024
Frequently Asked Questions
What Is a Honors Degree?
The Honors degree programme is designed to empower graduate engineering students with industry and career readiness through skill-based learning and application tools.
How will this programme help students in building their proficiency?
This programme is envisaged to help build a strong foundation across various streams through digital lectures, industry interviews, formative and summative assessments, capstone projects, and
How is this programme different from other industry programmes?
This programme is designed by globally renowned industry and university content partners to combine academic concepts with emerging industry skills and technologies for the students entering
What will students get once they enroll and complete this Honors pathway?
Once you enroll into the Honors pathway, you will get unlimited access to Coursera for Campus catalog of 10,000+ world-class courses, hands-on projects, and job-ready certificate programs. Yo
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