Generative AI and Prompt Engineering Certification Course
- Get Trained by Trainers from ISB, IIT & IIM
- 200+ Hours of Intensive Classroom & Online Training
- 64 Hours of Python, SQL, EDA Live or Videos
- 2 to 4 Live Projects
- Job Placement Assistance
Academic Partners & International Accreditations
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.
Generative AI & Prompt Engineering
INR 1,10,000 80,000+Tax
Generative AI & Prompt Engineering Training Programme Overview
"Prompt engineering" may appear to be a challenging undertaking. However, in practice, it's really easy to understand and doesn't even need a high level of technical expertise. Understanding these principles will enable you to take use of the amazing potential of Generative AI right now. Tools like ChatGPT that use Generative AI have countless applications. Professionals are using this technology to automate laborious tasks, generate fresh ideas, do research instantly, and much more. It also helps to simplify the development of content. Gaining an understanding of rapid engineering is the first step in enabling all of these possibilities.
What is Generative AI and Prompt Engineering?
Systems using generative artificial intelligence (AI) are made to produce certain results according to how well prompts are given. Generative AI models that use prompt engineering are better able to understand and react to a broad variety of questions, ranging from the very basic to the very complex. Fundamentally, excellent impulses lead to good outcomes. Prompt engineering and Generative AI are two increasingly valuable technologies that companies may use. Here's a handbook to help you become an expert in these methods and maintain your competitive edge. Recognise the concets of Generative AI: A branch of artificial intelligence called "Generative AI" deals with creating original and new text/video/audio data via the use of algorithms.
- To comprehend complex Generative AI ideas for text production
- To investigate deep learning methods associated with rapid engineering
- To examine moral issues in the creation of content using AI
- To comprehend the scalability and interpretability of AI language models
- To understand quality control and use cases in timely engineering
- To recognise and foresee emerging patterns in data (text/video/audio) production powered by AI
Generative AI & Prompt Engineering Training Learning Outcomes
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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Who Should Sign Up?
- Data Scientists
- Data and Analytics Manager
- Business Analysts
- Data Engineers
- DevOps Engineers
- IT/Software Engineers
- Machine Learning Architects
- Model Risk Managers/Auditors
- Lecture with a blend of theoretical & practical exposure
- Discussions & final exam to attain the certificate
- Quizzes and group activities
- Internship opportunity for eligible candidates
Generative AI & Prompt Engineering Certification Modules
Since the tech sector has embraced Generative AI and AI systems, the term "prompt engineer" has lately surfaced. But while AI prompt engineering is still in its infancy, there isn't yet a particular accreditation for it. Certifications are issued by associations for professionals in the field or by educational establishments; however, real-world experience with Generative AI applications and machine learning models is sometimes more valuable than certifications for those who are interested.
- Introduction to Vector Databases and Their Role in AI
- Deep Dive into RDBMS (SQL), NoSQL, and Vector Databases. Understand the Pros and Cons of these solutions.
- Understanding the vector databases' role in the field of product development with Generative AI.
- Improving the responsiveness and contextual understanding of AI-driven chatbots and virtual assistants with Vector Embeddings.
- Using vector databases in image and video generation.
- Introduction to Prompt Engineering and Foundations of Prompting.
- Practical exercises and demonstrations on creating prompts for various tasks such as information retrieval, creative writing, and more, using ChatGPT.
- Explore different types of Prompts, Prompting Strategies, and Principles of effective prompt designing.
- Zero-shot and One-shot Prompting: Techniques for creating prompts that guide the AI in performing tasks without prior examples or with a single example.
- Information Retrieval and Creative Writing: Strategies for extracting information effectively and for generating imaginative content.
- Advanced Prompt Structuring: Exploring context expansion, content summarization, and template filling to achieve specific outcomes.
- Prompt Reframing and Combination: Methods for altering and combining prompts to refine AI responses.
- Interactive Storytelling and Language Translation: Crafting prompts for dynamic storytelling, role-playing, and accurate language translation with contextual nuance.
- Sequential Prompting and Self-Consistency: Developing sequences of prompts for complex tasks and ensuring consistent AI responses.
- Analogical and Meta-Ask Prompting: Using analogies and meta-questions to enhance understanding and consistency.
- ReAct and OPRO: Techniques for reactive, context-aware responses, and optimization prompting for performance improvement.
- Chain-of-Thought and Iterative Prompting: Encouraging the AI to "think aloud" and refining prompts through iteration for clarity and depth.
- Best practices for maintaining user privacy and security measures to prevent misuse of AI technology.
- Exploring Prompting Tools: Introduction to libraries, models, and frameworks available for prompt engineering, including practical applications and case studies.
- Deriving insights by performing sentiment analysis with Text Mining and NLP
- Learn the Transformer architectures implemented for machine translation and automated summarization.
- Learn about the groundbreaking uses of BERT and GPT in automated content creation.
- Implementing Chatbots to enhance interaction quality and operational efficiency for effective customer engagement across industries.
- Learn how LLMs like GPT and BERT are revolutionizing with improved accuracy of information retrieval across digital libraries.
- Learn to build specialized models in healthcare, and the financial sector as part of Domain-Specific LLMs.
- Discover the role of LLMs in developing sophisticated AI chatbots.
- Understand the models that are applied in real-time translation services.
- Dive into the use of generative models for original written content generation.
- Exploring the World of AI-generated imagery with Dall-E 3 and Imagen.
- Learn the creation of realistic video sequences from textual inputs, significantly reducing production time and costs.
- Leveraging tools like ViT and SDXL Turbo in Automated Image Analysis.
- Explore the use of advanced AI models like BLIP-2 and Flamingo in enhancing user experience.
- Discover how models are used in e-commerce platforms for image-based product search and recommendation systems.
- Learn about the GenAI models for AI-driven object detection in real-time decision-making.
- Explore the capabilities of Generative AI tools like Soundful and Lyria in transforming music production.
- Enhancing Multimedia Experiences with the Video-Audio-Text Transformer (VATT).
- Improving audio quality and enabling innovative sound manipulation techniques with models like Distil-Whisper and SALMONN.
- enhancing user engagement through tailored listening experiences.
- Enhancing user engagement through tailored listening experiences by automating Music Curation and Personalization with GenAI.
- Introduction to learning platforms that respond to both text and image inputs.
- Explore advanced models like LLaVA and GPT-4V for integrating visual and textual information.
- Transforming digital marketing, storytelling, and educational content generation with models like Fuyu and Fuyu-8B that combine text, image, and video.
- Learn about the importance of diverse datasets like PMD, COCO, and Flickr30K in training AI.
- Examine how benchmarks like VQAv2 and TextVQA are used to evaluate the effectiveness of multimodal AI models in generating human-like responses.
- Visual search and image-based analysis with innovative models BriVL and Qwen-VL.
- Creating enriched multimedia experiences in virtual reality, video editing, and automated captioning with SALMONN.
- Develop Generative AI models with AWS services: Amazon Bedrock and SageMaker.
- Generating code snippets and entire functions with Amazon CodeWhisperer.
- Using high-performance computing services AWS Trainium and Inferentia to Optimize the training and deployment of AI models.
- Innovating with Generative AI on the Cloud.
- Discover the broad spectrum of Generative AI applications on Cloud platforms.
Trends in Generative AI & Prompt Engineering
Enterprise apps and services are starting to use Generative AI in prompt engineering, which has a lot of promise. But there are drawbacks as well, such applications that lag and possible AI hallucinations (like the Australian mayor's lawsuit against OpenAI and Google's Bard misstating planetary images). Chatbot misinformation might result in unsafe repairs and brand harm. Businesses that are successful will create countermeasures to reduce false information and figure out how Generative AI may benefit their consumers and bottom line.
- Creation based on prompts
- Business use cases are unlocked via APIs
- Rethink organisational procedures
- Better health applications
- Improved artificial intelligence data
- More proficient scenario development
- Hybrid vehicles increase dependability
- Customised generative programmes
- Apps that are domain-specific
- Interfaces using natural language
How we prepare you
- Additional Assignments of over 60+ hours
- Live Free Webinars
- Resume and LinkedIn Review Sessions
- Lifetime LMS Access
- 24/7 Support
- Job Placements in Generative AI Fields
- Complimentary Courses
- Unlimited Mock Interview and Quiz Session
- Hands-on Experience in Live Projects
- Offline Hiring Events
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