Gain the skills necessary for working with AI, from automating tasks to engaging with LLMs via API in Python, and progress to building AI-driven applications. This path is essential for professionals aiming to integrate AI into their toolkit.
- Developing core Python programming skills for AI-related tasks in Python
- Learning to interface with large language models through APIs to automate and enhance workflows
- Gaining the skills to construct and operate AI-driven chatbots using effective prompt engineering
- Designing and implement AI-powered web applications with practical functionality
Part 1: Fundamentals of Python and Generative AI [3 courses]
- 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.
Part 2: Intermediate Python and APIs [3 courses]
- Master essential command-line tools to navigate, manage, and manipulate files and directories.
- Understand and implement virtual environments and environment variables to manage Python packages and configurations.
- Gain proficiency in using Git for version control to track changes, collaborate on projects, and manage code.
- Evaluate, select, and set up an Integrated Development Environment (IDE) to enhance productivity and streamline the Python development process.
Part 3: Working with Large Language Models in Python [2 courses]
- 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
- 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.
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Projects in this path
Guided Project: Build a Food Ordering App
Create a functional and interactive food ordering application using Python. You’ll use dictionaries, functions, loops, and variables of varying scope levels to add, modify, or remove food items to a user’s cart until they are ready to checkout.
Guided Project: Garden Simulator Text Based Game
Create a gardening game. From foraging seeds to nurturing plants and selling the produce, every action in the game is an opportunity to practice Python concepts such as Object-Oriented Programming (OOP) and error handling.
Project: Selecting and Installing an Integrated Development Environment (IDE)
In this lesson, you’ll learn about Integrated Development Environments (IDEs), with a special focus on tools essential for Python developers. You’ll explore popular IDEs like VS Code and PyCharm, understanding their unique features and how to choose the appropriate IDE for your specific requirements. You’ll also gain practical experience installing and configuring your chosen IDE and Python on your local machine, setting the stage for productive coding sessions. Moreover, you’ll create and run a Python script, introducing you to the fundamentals of Python coding within an IDE.
Guided Project: Developing a Dynamic AI Chatbot
In this guided project, you’ll develop a dynamic AI chatbot from scratch, showcasing your ability to implement sophisticated conversation management and diverse prompt engineering strategies. The chatbot should be versatile and able to adapt to different contexts and user inputs, demonstrating potential for real-world applications.