Generative AI offers a comprehensive exploration of foundational concepts, practical applications, and advanced techniques. Participants will learn about the evolution of generative AI and key models like Autoencoders, VAEs, GANs, and LLMs. Hands-on labs cover text generation, language translation, image generation, and classification using transformers and other advanced methods. Practical applications include Google Cloud's Gemini for developing AI applications, creating clusters, and deploying solutions for various engineering roles. Advanced topics include multimodal AI, time series applications, and ethical considerations in AI development. Graduates will gain skills to develop, optimize, and responsibly deploy generative AI models across industries.
Introduction to generative AI-Brief history and evolution- Importance and applications in various domains-Overview of popular generative models-Autoencoders-Variational Autoencoders (VAEs)-Generative Adversarial Networks (GANs)-Autoregressive models-Introduction to Large Language Models - Introduction to Responsible AI - Responsible AI: Applying AI Principles with Google Cloud-Hands on lab
Introduction to Natural Language Processing (NLP)- Text Generation with Transformers-Language Translation with Google Translate-Introduction to Computer Vision-Image Generation with Generative Adversarial Networks (GANs)-Image Classification with Convolutional Neural Networks (CNNs)-Attention Mechanism -Encoder-Decoder Architecture - Create Image Captioning Models Hands-on Lab
Overview of Google Cloud Platform (GCP) - Gemini for Application Developers- Develop an app with Gemini assistance - Introduction to Gemini for Cloud Architects - Creating GKE clusters with Gemini - Architect web apps with Gemini-Introducing Gemini for Data Scientists and Analysts - Designing an LLM connected model with Gemini - Introducing Gemini for network engineers - Creating a VPC Network with Gemini - Introducing Gemini for Security Engineers & Gemini for DevOps Engineers-Hands-on Lab
Getting Started with the Vertex AI Gemini API with cURL-Introduction to Function Calling with Gemini-Getting Started with the Vertex AI Gemini API and Python SDK-Deploy a Streamlit App Integrated with Gemini Pro on Cloud Run-Develop GenAI Apps with Gemini and Streamlit- Introduction to Design Optimization- Generative Design with Evolutionary Algorithms- Optimization with Reinforcement Learning-Hands-on Lab
Introduction to Multimodal Generative AI-Generative AI for Time Series and Sequences-Ethics and Fairness in Generative AI-Responsible AI for Developers: Interpretability & Transparency - Machine Learning Operations (MLOps) for Generative AI-Hands-on Lab
Features
Recognized and supported by key players in the respective industry.
Learn actively through hands-on projects—Project-Based Learning builds real-world skills and understanding.
Guided and empowered by mentorship for enhanced learning and skill development.
Frequently Asked Questions
The virtual internship program is 60 Hrs. experiential learning program containing hands-on bootcamps, courses, learning resources and project work.
The training program will be organized online via Zoom.
No. This program is for individual eligible students only, team participation is not acceptable.
Yes. Successful learners will receive a virtual internship completion certificate.
Yes, Dedicated Mentor support is provided to complete your project.
We would provide necessary Learning Resources for the project so that you can understand the concepts before actually developing the whole project.
Participants can use our dedicated support channel to connect with the mentors.
