What will you learn in this Generative AI for Software Developers Specialization Course
Understand the fundamentals of generative AI and its applications in software development.
Explore popular generative AI models and tools for text, code, image, audio, and video generation.
Master prompt engineering techniques to create effective and impactful prompts.
Utilize generative AI tools to generate code snippets, scripts, test cases, and applications.
Develop innovative software engineering solutions using AI-powered tools and large language models (LLMs).
Program Overview
Course 1: Generative AI: Introduction and Applications
⏳ 7 hours
- Learn the basics of generative AI, its capabilities, and real-world use cases across various industries.
Course 2: Generative AI: Prompt Engineering Basics
⏳ 7 hours
- Delve into prompt engineering concepts, exploring techniques like zero-shot and few-shot prompting, and tools to create effective prompts.
Course 3: Generative AI: Elevate Your Software Development Career
⏳ 17 hours
- Apply generative AI tools and techniques in software development processes such as code generation, design and architecture, bug detection, and optimization.
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Job Outlook
Completing this specialization prepares you for roles such as Software Developer, AI Specialist, or Machine Learning Engineer.
The skills acquired are applicable across various industries that utilize software development and AI technologies.
Enhance your employability by gaining practical experience in applying generative AI to software development workflows.
Specification: Generative AI for Software Developers Specialization
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FAQs
- Basic programming experience, especially in Python or JavaScript, is recommended.
- Prior AI or ML experience is helpful but not mandatory.
- The course introduces generative AI concepts from the ground up.
- Focuses on practical implementation in software development.
- Suitable for developers looking to integrate AI into applications.
- Assists in generating boilerplate code and templates.
- Improves code completion and debugging through AI suggestions.
- Automates repetitive coding tasks.
- Enables creation of AI-powered applications and tools.
- Accelerates prototyping and experimentation with new features.
- Python and relevant AI/ML libraries like TensorFlow, PyTorch, or Hugging Face.
- APIs for integrating generative AI into applications.
- Tools for deploying AI models in software projects.
- Version control and collaborative development integration.
- Techniques for fine-tuning models for specific software tasks.
- Useful for web and mobile application development.
- Applicable in automation, chatbots, and AI assistants.
- Enhances gaming, simulation, and visualization projects.
- Useful in enterprise software for productivity tools.
- Skills transferable to startups, large companies, and consulting projects.
- Includes projects integrating AI into functional software.
- Exercises cover model deployment and API integration.
- Encourages building portfolio-ready applications.
- Provides step-by-step guidance for AI implementation.
- Reinforces concepts through practical coding and testing scenarios.
