LLM Fundamentals in Python
Skill Path
This path gives you the core skills to work with large language models in Python. You'll start by understanding how AI chatbots work, then learn to use LLM APIs programmatically — managing conversations, applying prompt engineering, and implementing advanced patterns like function calling and MCP. You'll finish by building interactive web applications that integrate with AI models using Streamlit.
- Intermediate friendly
- 1 month (5 hrs/week)
- Self paced
- 4 Courses
- 2 projects
Python skills you'll learn
- ✓ Understanding the capabilities and limitations of AI chatbots and large language models
- ✓ Using the OpenAI Chat Completions API to build AI-driven applications
- ✓ Applying prompt engineering techniques and implementing advanced patterns including function calling and MCP
- ✓ Building interactive AI-powered web applications using Streamlit
Outline of Python courses
1 steps · 4 courses
LLM Fundamentals in Python [4 courses]
Understand the capabilities and limitations of AI chatbots, then learn to work with LLMs programmatically through the OpenAI Chat Completions API. Manage conversation context, apply prompt engineering, and implement advanced patterns including function calling and MCP. Finish by building interactive AI-powered web applications with Streamlit.
- Course 1
AI Chatbots: Harnessing the Power of Large Language Models with Chandra
2hExplore how AI chatbots and large language models are reshaping communication through guided interaction, real examples, and hands-on practice.
Course Objectives ▾
- Understand the basics of AI, machine learning, deep learning, natural language processing, and chatbots.
- Learn how to craft effective prompts and interact with chatbots to improve learning outcomes.
- Explore practical use cases for AI chatbots in education, work, and personal projects.
- Gain hands-on experience using Chandra on the Dataquest platform.
- Course 2
Prompting Large Language Models in Python
6hExamine real-world applications of large language models by designing prompts, managing context, and building AI-driven workflows in Python.
Course Objectives ▾
- Utilize OpenAI's Chat Completions API to generate tailored AI-driven responses
- Manage conversation histories to maintain context in AI conversations
- Create custom Python functions for dynamic interactions with large language models
- Learn prompt engineering techniques to guide AI responses effectively
- Regulate token usage within the OpenAI API framework for efficient scripting
- Adopt best practices in prompt engineering to improve the quality of AI-generated text
- Course 3
Tool Use with LLMs in Python
6hLearn to build reliable LLM systems with structured outputs, function calling, and tool integration. Move beyond basic prompting to create maintainable workflows using validation, agentic loops, and the Model Context Protocol.
Course Objectives ▾
- Generate validated, structured outputs from LLM responses
- Implement agentic loops that handle multi-step tool execution
- Create reusable tool servers using the Model Context Protocol
- Design prompt templates and pipelines for reliability
- Handle errors and validation failures in LLM workflows
- Course 4
Designing Dynamic Python Applications with Streamlit
4hDesign interactive Python applications with Streamlit by creating dynamic interfaces, managing state, and integrating LLM-powered chat features.
Course Objectives ▾
- Grasp the essentials of Streamlit for interactive web app development.
- Create user-friendly interfaces with Streamlit's array of widgets.
- Manage application state for dynamic user experiences.
- Integrate AI LLM models for responsive chatbots.
- Leverage Streamlit's latest chat widgets for effective communication.
Python projects you'll build
2 hands-on projects across the path
Building an AI Chatbot with Streamlit
For this project, you'll step into the role of a Python developer to integrate an AI chatbot with a Streamlit user interface, allowing users to interact with your "Sassy Chatbot" through a public web app.
Developing a Dynamic AI Chatbot
For this project, you'll become a developer at a tech company, using Python and the OpenAI API to create an engaging AI chatbot. You'll gain skills in conversation management, persona creation, and token handling as you build a chatbot that adapts to different platforms.
Earn your LLM Fundamentals in Python Certificate
Add this Python certificate to your resume or LinkedIn to showcase your skills and stand out in job applications.
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