The Prompt Engineering Master Course 2K24 by Digital Marketing Seekho is a comprehensive program designed to equip individuals with advanced skills and knowledge in the field of Artificial Intelligence. This specialized course combines the principles of engineering with modern digital marketing techniques to provide participants with a unique blend of technical expertise and strategic marketing insights. Through a combination of live online classes, self-paced learning modules, and hands-on projects, participants will gain proficiency in working with the latest AI tools also learning how to effectively they can use Prompt Engineering and AI as a combination. Led by industry experts and experienced instructors, this course offers a holistic approach to Prompt engineering, preparing participants to excel in today’s competitive market. Whether you’re a seasoned prompt engineer looking to expand your skill set or a newcomer to the field seeking to leverage digital marketing strategies, the Prompt Engineering Master Course 2K24 provides the tools and resources you need to succeed.
Generative AI Prompt Engineering Master course 2K24 content
- Introduction to Generative AI: Understand the fundamentals of generative AI and its applications.
- Deep Learning Basics: Learn the basics of deep learning algorithms and architectures.
- Generative Models: Explore different types of generative models such as GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and more.
- Hands-on Projects: Engage in practical projects to apply your learning and gain hands-on experience in developing generative AI models.
- Advanced Topics: Dive into advanced topics such as conditional generative models, style transfer, and image-to-image translation.
- Deployment and Optimization: Learn how to deploy and optimize generative AI models for real-world applications.
- Industry Applications: Explore various industry applications of generative AI in fields such as art, design, healthcare, and more.
- Live Online Sessions: Participate in live online sessions conducted by industry experts to deepen your understanding and address any queries. Certification: Upon successful completion of the course, receive a certification to showcase your expertise in generative AI.
Join our Generative AI Prompt Engineering Master Course 2K24 today to unlock your potential in this cutting-edge field!
The Generative AI Prompt Engineering Master Course 2K24 certification program is tailored for engineers, software professionals, and data experts seeking advanced generative AI training and a ChatGPT course. If programming is new for you, then contact admissions to map your enrolment path to see how you can get certification on Generative AI.
Almost all Generative AI courses in India require basic programming knowledge (should have done programming before, either in academics or professionally) since they take a project-based learning approach with ChatGPT and generative AI tools. If programming is new to you and you still want to enroll in Generative AI courses, contact our admissions team to map your enrolment path to see how you can get Generative AI certifications.
Our comprehensive courses on Generative AI Prompt Engineering Master Course 2K24 equip you with in-demand expertise in MidJourney, DALL-E, and more. There is also a dedicated ChatGPT course within our program. Upon completing the Generative AI training course, you earn an upGrad certificate and alumni status to validate your Generative AI course certificate.
Overall, you need to spend 6+ hours/per week on bite-sized videos from our courses on Generative AI. The remaining hours involve working on industry projects and applications of tools like ChatGPT, attending Generative AI masterclasses, and mentoring sessions by experts, and more. This blend is why ours is one of the best Generative AI courses in the country.
Features
- Introduction to Python and Programming Python Data Types, Variables, Operators, Data Structures Python Programming Constructs: Conditionals, Loops, Functions UDFs, Best Coding Practices and Exception Handling Python for Data Science and Pandas: Working with relational databases, Data Cleaning, Preprocessing, Analysis Advanced Text Processing using Pandas Basics of Linux: Commands, Setting up Local Environment
- Define the different components of the bot and design the workflow for creating the bot Understand the working of LLMs like GPT3 that power ChatGPT: Attention Mechanisms, Transformers, Reinforcement Learning, RLHF among others Apply prompting techniques to create prompts for asking questions and evaluating the customer's response Establish metric(s) to measure model performance Prompt Engineering: Improve the assistant's responses by applying simple (non-reasoning) prompting techniques Prompt Engineering: Improve the assistant's accuracy by applying Chain of Thought reasoning-based prompting techniques
- Understand various search techniques and the generative search paradigm Understand the working of embeddings and how they help in semantic search Create and analyse embeddings for semantic search Understand the entire semantic search pipeline including chunking, embedding, and retrieval Create embeddings for large documents by creating chunks Create a Q/A system that fetches answer using similarilty search over embeddings
- Define the components of the knowledge retrieval system and design the workflow Explore how LangChain can connect the different components of the system Understand the different parts of LangChain - Models, Prompts, Indexes, Chains, Memory and Agents Explore the different tools in LangChain and initialise an agent that uses the tools to read different types of files or data present in the company database Build the backend for the system using Vectorstore options present in LangChain Divide the documents into chunks and apply the LLM to create the embeddings and extract entity for the chunks of document and store them in the Vectorstore
- Explore the Generative AI services offered by various cloud services Modify the workflow design of knowledge retrieval system for scalability Identify the cloud services required for creating the scalable system Expose the system through a chat based front end to the user
- Mitigating risks in AI: Responsible AI RLHF as a Product to train your own LLM Multimodal Learning: Audio, Image, Text, Heatmap among others within a LLM
- Understand how images are stored and manipulated digitally and work on image processing tasks Understand the process by which artificial neural networks and their variants such as convolutional neural networks handle image analysis Understand and implement legacy image generation models such as variational autoencoders and generative adversarial networks Understand the components of diffusion models and the process by which images are generated and work on building a stable diffusion pipeline component-by-component Set up a simple stable diffusion pipeline and create suitable prompts for image generation and use the model to generate relevant images
- Understand prompting for code generation and generate code for data science tasks in a larger ML problem Automate ML workflows using language generation models including data preprocessing and machine learning modelling Use vector embeddings to solve a real-world use-case problem based on semantic similarity Fine-tune language generation models for a particular problem statement and evaluate the model
Target audiences
- INTERMEDIATE
- GRADUATION
- POST GRADUATION