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  • LLM Engineering in Practice with Streamlit and OpenAI

LLM Engineering in Practice with Streamlit and OpenAI

with Petar Petrov
5/5
(4)

Dive into the world of AI solutions with this hands-on course. Learn how to design, develop, and deploy an interview simulator project using Streamlit, integrating language models, feedback systems, and advanced prompts. Master key concepts in AI, prompt engineering, and app development while solving real-world challenges.

3 hours of content 52 students

$99.00

Lifetime access

Buy now
14-Day Money-Back Guarantee

What you get:

  • 3 hours of content
  • 6 Downloadable resources
  • World-class instructor
  • Closed captions
  • Q&A support
  • Future course updates
  • Course exam
  • Certificate of achievement

LLM Engineering in Practice with Streamlit and OpenAI

A course by Petar Petrov

$99.00

Lifetime access

Buy now
14-Day Money-Back Guarantee

What you get:

  • 3 hours of content
  • 6 Downloadable resources
  • World-class instructor
  • Closed captions
  • Q&A support
  • Future course updates
  • Course exam
  • Certificate of achievement

$99.00

Lifetime access

Buy now

$99.00

Lifetime access

Buy now
14-Day Money-Back Guarantee

What you get:

  • 3 hours of content
  • 6 Downloadable resources
  • World-class instructor
  • Closed captions
  • Q&A support
  • Future course updates
  • Course exam
  • Certificate of achievement

What You Learn

  • Build interactive and user-friendly web applications using Streamlit and Python.
  • Master prompt engineering to design, refine, and test effective prompts for AI applications.
  • Gain a solid understanding of the development process for AI-powered applications.
  • Learn how to leverage large language models (LLMs) for real-world use cases.
  • Understand how to create activity diagrams to plan and map out your application's architecture.
  • Learn how to tackle real-world challenges, including prompt injections, hallucinations, and scaling applications.

Top Choice of Leading Companies Worldwide

Industry leaders and professionals globally rely on this top-rated course to enhance their skills.

Course Description

Are you ready to dive into the fascinating world of AI-powered applications?

Do you want to solve real-world problems using cutting-edge large language models (LLMs)?

This is the perfect course for you!

This course is your step-by-step guide to designing, developing, and deploying an AI application using Streamlit, Python, and OpenAI models. You’ll not only learn the theory and development process but also gain hands-on experience with a practical, real-world example: ACE Interview, a powerful AI-driven interview application that has already helped thousands of people prepare for their interviews. By exploring the structure of ACE Interview, you’ll see how the concepts taught in this course are applied in practice. Moreover, we’ll share the challenges and mistakes we encountered during its development—and how we overcame them—so you can avoid similar pitfalls in your own projects.

By completing this course, you’ll acquire a versatile and highly practical skill set including:

  • Python Programing with Streamlit – Learn to build interactive, user-friendly web apps using one of the most popular frameworks.
  • Prompt Engineering – Master the art of designing, refining, and testing prompts to maximize the performance of your AI projects.
  • Architecture Design – Learn to create activity diagrams to visually map out your application’s structure, making it easier to plan and communicate your ideas effectively.
  • Utilizing LLMs: Understand how to leverage large language models for different use cases, including the differences between hosting models and using APIs, as well as open-source versus closed-source options.
  • Cost Management: Analyze and predict the cost associated with your AI projects to make informed decisions.

Our course takes you through every stage of the development process:

  • Planning stage: Design the architecture, database and prompts to lay a strong foundation for your project.
  • Prototype stage: Build a fully functional Streamlit to showcase in your portfolio.
  • Development stage: Explore the real-world challenges you may encounter while working on your project and learn effective strategies to solve them. These include issues like prompt injections, handling hallucinations, scaling your application, optimizing token usage, and managing cost to ensure your project is both efficient and scalable.

By the end of this course, you’ll have more than just a working prototype of an AI interview simulator—you’ll have the knowledge and confidence to create your own AI-powered applications. Whether you’re looking to break into AI development or enhance your existing skill set, this course is designed to help you succeed.

Take the next step in your AI journey—enroll today!

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Learn for Free

Hosting an LLM vs Using an API

2.1 Hosting an LLM vs Using an API

4 min

Open-Source vs Closed-Source Models

2.2 Open-Source vs Closed-Source Models

7 min

Interactive Exercises

Practice what you've learned with coding tasks, flashcards, fill in the blanks, multiple choice, and other fun exercises.

Practice what you've learned with coding tasks, flashcards, fill in the blanks, multiple choice, and other fun exercises.

true-false exercise
single-choice exercise
multiple-choice exercise
flashcards exercise
fill-blank-typing exercise
fill-blank-selection exercise
order exercise
categorize exercise

Curriculum

  • 1. Introduction to the Course
    3 Lessons 10 Min

    This section sets the stage for your journey into creating cutting-edge AI-driven projects. Learn about the ACE Interview tool as a real-world example of successful AI integration and understand the skills you’ll gain by completing this course.

    Introduction to the Course
    3 min
    What does the course cover?
    2 min
    The Interview Tool’s Specifics
    5 min
  • 2. Planning stage
    10 Lessons 44 Min

    Lay the groundwork for your AI-powered application by mastering the planning process. In this section, you’ll explore key decisions like hosting LLMs vs. using APIs, open-source vs. closed-source models, and cost analysis. Additionally, you’ll learn how to design activity diagrams, database schemas, and prompts to ensure a strong foundation for your project.

    Hosting an LLM vs Using an API
    4 min
    Open-Source vs Closed-Source Models
    7 min
    Tokens
    5 min
    Pricing: Hosting an LLM vs Pay-by-Token
    4 min
    Initial Prompt Development: Part 1
    5 min
    Initial Prompt Development: Part 2
    5 min
    Database Design and Schema Development
    3 min
    What Is an Activity Diagram
    4 min
    Creating an Activity Diagram
    5 min
    Concluding the Planning Stage
    2 min
  • 3. Crafting and Testing AI Prompts
    5 Lessons 24 Min

    You’ll explore the OpenAI Playground to experiment with LLM capabilities, learn how to optimize parameters like temperature and top-p for different use cases, and master prompt engineering for software development. Finally, you’ll test and validate your prompt templates to ensure reliable and accurate AI performance.

    Adding Funds to Your OpenAI API Account Read now
    2 min
    The OpenAI Playground
    7 min
    Optimizing Temperature and Top P for Different Use Cases
    5 min
    Prompt Engineering for Software Development
    6 min
    How to Test Out a Prompt Template
    4 min
  • 4. Getting to Know Streamlit
    6 Lessons 22 Min

    This section introduces you to Streamlit, a powerful framework for building interactive web applications with Python. You’ll learn how to set up your environment, explore Streamlit’s pros and cons, and work with key elements like titles, text methods, chat components, and session state. By the end, you’ll have a strong foundation in Streamlit to develop user-friendly applications.

    Setting up environment
    3 min
    Streamlit's Pros and Cons
    3 min
    Streamlit Elements: Titles, Headers, and Formatting
    3 min
    Streamlit Elements: Text Methods
    3 min
    Streamlit Elements: Chat Elements
    4 min
    Session State
    6 min
  • 5. Developing the prototype
    9 Lessons 46 Min

    In this section, you’ll bring an AI application to life by building a fully functional prototype of an interview app. Learn how to initialize an OpenAI client, implement chatbot functionality, and enhance interactions using session state. You’ll also dive into adding feedback features, refining your project, and deploying your application to GitHub and Streamlit, making it ready for real-world use.

    Initializing an OpenAI Client
    4 min
    Implementing the Chat Functionality
    6 min
    Building the Setup Page
    7 min
    Enhancing Chatbot Interaction with Session State
    6 min
    Refining Our Project
    3 min
    Implementing Feedback Functionality: Part 1
    4 min
     Implementing Feedback Functionality: Part 2
    7 min
    Uploading Your Project in GitHub
    5 min
    Deploying Your Streamlit App
    4 min

Topics

PythonStreamlitTheoryPrompt EngineeringAi EngineeringProgrammingOpenai

Tools & Technologies

python
git
theory

Course Requirements

  • Intermediate programming knowledge in Python is required to get the most out of this course.
  • A foundational understanding of AI will enhance your learning experience.

Who Should Take This Course?

Level of difficulty: Advanced

  • Perfect for beginners in AI with good Python fundamentals.
  • Aspiring developers, app designers, and stakeholders aiming to create impactful solutions using AI.
  • Ideal for anyone eager to understand and harness AI's potential.

Exams and Certification

A 365 Data Science Course Certificate is an excellent addition to your LinkedIn profile—demonstrating your expertise and willingness to go the extra mile to accomplish your goals.

Exams and certification

Meet Your Instructor

Petar Petrov

Petar Petrov

Software Developer at 365 Data Science

1 Courses

4 Reviews

52 Students

Petar holds a Bachelor's degree in Computing from Glasgow Caledonian University. With a keen interest in AI and data science, he has worked on various projects, including AI-powered tools, mobile applications, and data science solutions. Petar is dedicated to developing innovative business solutions and applications, helping to simplify complex concepts and drive tech advancement.

See More

What Our Learners Say

Sweta Sharma
Sweta Sharma
18.01.2025

365 Data Science Is Featured at

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