Learn ChatGPT step by step for real-world development. Use AI to write code, refactor, generate tests, docs, debug, etc.
β±οΈ Length: 2.0 total hours
β 4.56/5 rating
π₯ 7,389 students
π October 2025 update
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- Course Overview
- Unlock the transformative power of AI in your development workflow with this intensive, 2-hour crash course specifically designed for software engineers.
- Go beyond basic AI interaction and dive deep into practical, application-driven strategies for leveraging ChatGPT to augment your coding prowess across multiple languages and project types.
- This course is meticulously crafted to equip you with immediate, actionable skills, allowing you to boost productivity, enhance code quality, and accelerate development cycles from day one.
- We’ll explore how to seamlessly integrate ChatGPT into your existing development environment, transforming it into an indispensable coding partner.
- Gain a foundational understanding of Large Language Models (LLMs) in the context of software development, focusing on how they can be ethically and effectively utilized.
- Discover advanced prompting techniques that move beyond simple requests to complex problem-solving and creative code generation.
- Understand the nuances of different ChatGPT models and their suitability for specific coding challenges, ensuring you select the most efficient tool for the task.
- This course is future-proofed with an October 2025 update, ensuring you’re learning the latest best practices and features in AI-assisted development.
- Target Audience
- This course is ideal for junior to senior developers across various programming backgrounds (e.g., web, mobile, backend) looking to embrace AI as a productivity multiplier.
- Software engineers, team leads, and technical managers seeking to understand and implement AI-driven development strategies within their teams.
- Students and aspiring developers wanting to gain a competitive edge by mastering cutting-edge AI tools for coding.
- Anyone frustrated with repetitive coding tasks, tedious documentation, or time-consuming debugging who wants to find an AI-powered solution.
- Key Learning Objectives & Skill Development
- Master the art of prompt engineering for code generation, enabling you to translate complex requirements into functional code snippets with remarkable accuracy.
- Develop proficiency in using ChatGPT for code modernization and optimization, transforming legacy code into more efficient and maintainable solutions.
- Learn to leverage AI for rapid prototyping and exploring different architectural patterns, significantly reducing the time spent on initial project setup.
- Gain practical experience in generating comprehensive and accurate code documentation, ensuring your projects are well-understood and easily navigable by others.
- Enhance your debugging skills by learning how to articulate problems to ChatGPT and interpret its diagnostic suggestions effectively.
- Explore AI-assisted strategies for creating robust and comprehensive unit and integration tests, improving code reliability and reducing post-deployment issues.
- Understand how to employ ChatGPT to explore and implement design patterns, leading to more scalable and well-structured applications.
- Acquire the ability to critically evaluate AI-generated code, ensuring it aligns with best practices, security standards, and project-specific constraints.
- Learn advanced techniques for leveraging ChatGPT’s conversational memory to maintain context across longer coding sessions and complex problem-solving dialogues.
- Discover how to effectively utilize file uploads and project-level tools within ChatGPT to manage larger codebases and development contexts.
- Grasp the strategic advantages and limitations of ChatGPT when compared to specialized AI coding assistants, enabling informed tool selection.
- Requirements / Prerequisites
- Basic to intermediate programming knowledge in at least one common language (e.g., JavaScript, Python, Java, C#).
- Familiarity with fundamental software development concepts and a standard development environment.
- An active OpenAI account or the ability to create one.
- A reliable internet connection for accessing ChatGPT.
- A willingness to experiment and adopt new technologies.
- Skills Covered / Tools Used
- AI-Powered Code Generation: Writing boilerplate, algorithms, and custom functions.
- Code Refactoring & Optimization: Improving existing code for performance and readability.
- Debugging Assistance: Identifying and fixing errors, understanding stack traces.
- Test Case Generation: Creating unit, integration, and end-to-end tests.
- Automated Documentation: Generating READMEs, function docs, and API descriptions.
- Prompt Engineering for Developers: Crafting effective queries for code-related tasks.
- Model Selection: Choosing between different ChatGPT models for optimal results.
- Data Privacy Configuration: Understanding and managing personal data within ChatGPT.
- Custom Instructions: Tailoring ChatGPT’s responses to your specific needs.
- ChatGPT Features: Utilizing memory, voice input, file uploads, and project tools.
- Comparative Analysis: Understanding the role of ChatGPT against tools like Copilot and Cursor.
- Multiple Programming Languages: Practical application in JavaScript, Python, and other common languages.
- Benefits / Outcomes
- Accelerated Development: Significantly reduce the time spent on repetitive coding tasks and accelerate project timelines.
- Enhanced Code Quality: Generate more robust, well-tested, and documented code, leading to fewer bugs and easier maintenance.
- Increased Productivity: Free up your valuable time to focus on complex problem-solving and innovative feature development.
- Skill Augmentation: Elevate your coding capabilities by integrating AI as a powerful assistant.
- Deeper Understanding of AI in Development: Gain practical, hands-on experience with cutting-edge AI tools for software engineering.
- Competitive Advantage: Stay ahead of the curve by mastering essential AI skills in the modern development landscape.
- Improved Learning Curve for New Technologies: Quickly grasp new languages, frameworks, or APIs with AI-driven explanations and examples.
- PROS
- Concise & Actionable: Delivers essential skills in a short, impactful timeframe, perfect for busy developers.
- Practical Focus: Emphasizes real-world applications and immediate integration into development workflows.
- Comprehensive Overview: Covers a wide range of AI-assisted development tasks beyond just code writing.
- Updated Content: Incorporates recent advancements and features in AI coding tools.
- CONS
- Depth vs. Breadth: Due to its crash course format, the course may prioritize breadth over deep dives into highly specialized AI coding techniques or theoretical underpinnings of LLMs.
Learning Tracks: English,IT & Software,Other IT & Software
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