Python Development with ChatGPT: Fullstack App Development

External: Coursera Courses ↗ · Coursera

Open Course on External: Coursera

Free to audit · Opens on External: Coursera

Python Development with ChatGPT: Fullstack App Development

Coursera · Intermediate ·🧠 Large Language Models ·2mo ago
Imagine unlocking the capabilities of ChatGPT AI in full-stack development—an idea turned into reality, now at your fingertips! Designed for web developers and Python enthusiasts, this Guided Project empowers you to seamlessly integrate Chat GPT AI into the creation of innovative full-stack applications. Through practical tasks, you'll master the development of a full-stack news aggregator, automate content generation with Chat GPT, and enhance backend processes using Python programming. Navigate the challenges of real-world application integration to craft a state-of-the-art news platform. This intermediate to advanced project is perfect for those well-versed in Python code reading, library utilization, and eager to embrace the future of web development entwined with AI. The project's uniqueness lies in its fusion of traditional Python development with cutting-edge AI, particularly Chat GPT. To succeed in this project, a robust understanding of Python and familiarity with mainstream libraries are prerequisites. Join us on this journey to redefine web development through the lens of advanced AI integration. Prerequisites: Learners should have Python reading proficiency, which includes: Ability to read Python code, debug Python scripts, and utilize common Python data structures (lists, dictionaries, tuples). Learners should have experience with Python control structures (loops, conditionals) and an understanding of Python functions and modules. Learners should also have API integration experience, which includes: Proficiency in using RESTful APIs with Python. Experience with Python libraries like Requests for API interactions. Ability to parse and handle JSON or XML data returned from APIs.
Watch on External: Coursera ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related AI Lessons

Explainable Causal Reinforcement Learning for bio-inspired soft robotics maintenance under real-time policy constraints
Learn how Explainable Causal Reinforcement Learning can be applied to bio-inspired soft robotics maintenance under real-time policy constraints, enabling more efficient and autonomous decision-making in complex systems.
Dev.to AI
LLMs That Actually Pen Test: What Post-Training for Security Means for Your AI Stack
Learn how post-training for security enables LLMs to perform pen testing and its implications for your AI stack
Dev.to · theAIGeek
I spent two weeks optimizing 96GB of VRAM for local LLMs. Paid APIs still won.
Optimizing 96GB of VRAM for local LLMs may not be enough to outperform paid APIs, highlighting the importance of considering alternative solutions
Dev.to · Andre Zaiats
Securing LLM Agent Teams: Inside NRT-Defense v0.4.0
Learn how to secure LLM agent teams using NRT-Defense v0.4.0 and mitigate adaptive multi-turn attacks
Dev.to · Fenix
Up next
5 Levels of AI Agents - From Simple LLM Calls to Multi-Agent Systems
Dave Ebbelaar (LLM Eng)
Watch →