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Overview
This course is designed to equip software developers with the skills and knowledge to harness the power of Generative AI in their development processes. Participants will learn how to integrate AI models into their software, create innovative AI-driven applications, and optimize workflows using state-of-the-art generative techniques. The course provides hands-on experience with popular AI frameworks and tools, enabling developers to implement AI solutions effectively in real-world scenarios.
Objectives
By the end of this course, leaner will be able to:
- Understand the fundamentals of Generative AI and its applications in software development.
- Implement generative models using popular AI frameworks like TensorFlow and PyTorch.
- Integrate AI models into software projects to enhance functionality and user experience.
- Optimize and fine-tune AI models for specific tasks and applications.
- Develop AI-driven features such as text generation, image synthesis, and code generation.
- Evaluate ethical considerations and best practices when using Generative AI in development.
Prerequisites
- Basic programming knowledge, particularly in Python.
- Familiarity with machine learning concepts is recommended but not required.
- Understanding of software development processes and best practices.
Course Outline
Module 1: Introduction to Generative AICourses2024-08-16T21:32:51+05:30
- Overview of Generative AI and its impact on software development.
- Key concepts: models, training data, and inference.
Module 2: Exploring Language ModelsCourses2024-08-20T10:52:56+05:30
- Understanding and implementing GPT (Generative Pre-trained Transformer).
- Use cases in software development: chatbots, code generation, and content creation.
Module 3: Image Generation with GANsCourses2024-08-16T21:35:11+05:30
- Introduction to Generative Adversarial Networks (GANs).
- Techniques for image synthesis and enhancement.
Module 4: Building AI-Driven FeaturesCourses2024-08-16T21:36:28+05:30
- Integrating AI models into software applications.
- Case studies and real-world examples.
Module 5: Ethics and Best PracticesCourses2024-08-16T21:37:35+05:30
- Addressing bias, fairness, and transparency in AI systems.
- Guidelines for responsible AI deployment.
