Generative AI for Software Engineers & Developers

This course introduces the essentials of Gemini AI and Vertex AI, blending architectural insights with hands-on coding, multimodal development, and intelligent agent creation. Designed to give you both theoretical foundations and practical experience, it explores how Google’s most advanced AI systems are transforming software development, data analysis, and real-world applications. Through guided lessons and demonstrations, you’ll learn to work with Gemini’s multimodal architecture, leverage APIs for text and vision, build smarter apps with AI-driven code generation, and design intelligent agents on Vertex AI. You will also explore advanced model tuning, grounding techniques, and deployment strategies to create reliable, production-ready AI solutions. By the end of this course, you will be able to: • Understand Gemini’s multimodal architecture, APIs, and core capabilities. • Implement Gemini for text, vision, and code tasks, including function calling and document understanding. • Apply prompt engineering strategies and best practices for code generation, optimization, and testing. • Develop multimodal applications using Gemini Live API and natural language-to-database techniques. • Explore Vertex AI foundations, model garden, and Google’s foundation models (Gemini, Imagen, Veo). • Build and enhance intelligent agents with the Agent Development Kit and task-specific prompt guidance. • Tune, evaluate, and optimize Gemini and Vertex AI models using LoRA, QLoRA, and evaluation metrics. • Deploy AI systems with strategies to balance cost, latency, throughput, and performance. This course is ideal for developers, data scientists, and AI practitioners who want to build next-generation applications powered by Google Gemini AI and Vertex AI. A basic understanding of Python and machine learning will be helpful, but no prior experience with Gemini or Vertex AI is required. Join us to explore the cutting edge of multimodal AI and discover how to build smarter, more reliable applications with Gemini and Vertex AI!

This program offers a detailed exploration of AI-powered software development, guiding participants through the latest advancements and practical applications of intelligent coding tools. Tailored for developers, software engineers, and technical leads, it provides the skills to effectively integrate AI coding assistants such as GitHub Copilot, Tabnine, and Amazon Q into real-world projects. You’ll begin by mastering GitHub Copilot, exploring how to supercharge coding with intelligent code suggestions, debugging support, documentation, and collaborative workflows. From personalized completions to advanced integrations in CI/CD pipelines, you’ll gain hands-on expertise in applying Copilot effectively across individual and team development. Next, you’ll dive into Tabnine AI, unlocking context-aware completions, inline actions, and AI-powered chat to boost productivity. You’ll learn how to review, refactor, and document code with AI, while also addressing security and ethical considerations in modern development. Tabnine’s integrations and maintenance capabilities will help you streamline large-scale projects with confidence. The program concludes with Amazon Q for Developers, Amazon’s powerful AI assistant for coding and cloud-based development. You’ll explore setup, configuration, and practical usage of commands like /transform and /dev to generate, refactor, and test code. By comparing Amazon Q with Copilot and Tabnine, you’ll understand their strengths and trade-offs, empowering you to select the right AI tool for diverse workflows. By the end of this program, you will be able to: - Accelerate development with GitHub Copilot for intelligent suggestions, debugging, reviews, and DevOps automation. - Boost productivity with Tabnine AI for context-aware completions, code review, documentation, and secure coding practices. - Harness Amazon Q Developer for inline suggestions, code transformation, testing, and AWS integration. - Collaborate effectively in multi-developer projects using AI to enhance pull requests, code reviews, and pair programming. - Apply AI responsibly to build secure, scalable, and maintainable software across the entire development lifecycle. This program is ideal for software engineers, DevOps professionals, and technical leads aiming to integrate AI seamlessly into their coding workflows. A foundational understanding of programming concepts, version control, and software development best practices is recommended. Join us to unlock the power of AI in software engineering and transform the way you code, collaborate, and innovate.

This program offers a structured journey into the transformative world of AI-powered code understanding, quality assurance, and intelligent development workflows. Designed for developers, software engineers, and technical leads, this course empowers you to leverage cutting-edge AI tools for efficient code navigation, review, debugging, security, and optimization. By the end of this program, you will be able to: - Analyze and explore large codebases quickly with AI tools for faster understanding and onboarding. - Review and evaluate code automatically to ensure high-quality, reliable, and maintainable software. - Create, refactor, and debug code efficiently using intelligent AI-powered assistants. - Secure applications by detecting vulnerabilities, managing dependencies, and enhancing code safety. - Optimize and improve performance with AI-driven profiling, tuning, and resource management tools. This program is ideal for software engineers, AI professionals, and tech leads aiming to enhance their coding workflows with AI. A foundational understanding of programming concepts, version control, and basic software development practices is recommended. Join us to unlock the power of AI in software engineering and transform the way you navigate, build, and maintain code.