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This course on Coursera is a comprehensive training program designed to bridge core architectural concepts with hands-on generative AI application development. Taught in collaboration with Edureka, this course guides learners through Google’s advanced multimodal AI capabilities—spanning text, vision, document analysis, and natural language-to-database queries using the Gemini Live API and Google AI Studio. Students explore how to design autonomous agents with the Agent Development Kit, apply prompt engineering for code generation, and fine-tune models using LoRA and QLoRA techniques on Vertex AI. Through practical demos and real-world deployment scenarios, participants develop the technical foundation required to balance cost, latency, and performance while building enterprise-ready AI solutions on Google Cloud Platform.
Topics This Course Covers
- Gemini Multimodal Architecture & Core APIs: Exploring Gemini’s multimodal capabilities across text, vision, code generation, function calling, and document processing.
- Prompt Engineering & Application Development: Designing prompt patterns, implementing natural language-to-database interfaces, and leveraging the Gemini Live API for real-time applications.
- Vertex AI & Model Garden Exploration: Navigating Google Cloud’s foundation models (Gemini, Imagen, Veo) and configuring development environments.
- Intelligent Agent Development: Building, testing, and optimizing AI agents using the Agent Development Kit and task-specific prompt structures.
- Model Tuning, Evaluation & Deployment: Applying LoRA and QLoRA fine-tuning methods, evaluating model performance, and balancing throughput and latency for production workloads.
Who Will Benefit from Taking This Course
- Software Engineers & Developers: Practitioners seeking to embed multimodal capabilities, automated code generation, and function calling into modern software applications.
- Data Scientists & AI Practitioners: Professionals aiming to master Parameter-Efficient Fine-Tuning (PEFT) techniques like LoRA/QLoRA and evaluate LLM performance on Vertex AI.
- Cloud & Machine Learning Solutions Architects: Technical leaders responsible for designing scalable, cost-effective AI agent architectures on Google Cloud Platform.
- Technical Innovators & AI Enthusiasts: Learners with a basic understanding of Python who want to move from basic chat prompts to building production-grade generative AI systems.
Why Take This Course
Enrolling in this course provides a direct pathway to mastering Google's modern AI ecosystem without getting lost in purely theoretical concepts. While many introductory courses cover basic prompt writing, this program combines architectural deep dives with actionable coding workflows—taking you from API calls to fine-tuning and agent deployment. By mastering multimodal prompt engineering, database integration, and model optimization strategies directly on Google Cloud, you acquire high-demand cloud AI skills. This knowledge enables you to build intelligent, low-latency, and cost-effective AI applications that address complex business challenges.
