Prompt Engineering with LLMs
IT and Product Development / Software Development

Prompt Engineering with LLMs

Creating Machine Learning-based Web application using Prompt Engineering

0 AIXplorers Enrolled
Intermediate
English
This Course Includes:
  • 1h 02m
  • 10 Lectures
  • 2 Downloadable Assets
  • Full Lifetime Access
  • Access On Mobile And Tv
  • Certificate On Completion

Overview

What will AIXplorers learn in this course?
  • Techniques for crafting effective prompts to guide AI behavior.
  • Building and training machine learning models like XGBoost.
  • Setting up and deploying web applications using frameworks.
  • How to integrate advanced language models (LLMs) into web applications
  • Testing, debugging, and optimizing applications for better performance.
  • Preparing and managing data for machine learning projects.
What are the requirements or prerequisites for taking this course?
  • Back-end/ front-end web development experience.
  • Basic understanding of Machine Learning concepts.
  • Basic understanding of algorithms.
Who is the course for?
  • Machine Learning Enthusiasts
  • Software Engineers
  • Data Scientists
  • Prompt Engineers
  • Artificial Intelligence Experts and Enthusiasts
Description

Course Content

  • 5 Sections
  • 10 Lectures
  • 1h 02m Total Length
Section 1
Introduction to Prompt Engineering and LLMs

• Understanding Prompt Engineering
• Overview of Large Language Models (LLMs)
• Use Cases of Prompt Engineering in ML Applications
• Fundamentals of Crafting Effective Prompts

Time 02m
Lectures 1
Introduction to Prompt Engineering and LLMs
0:02:54
Section 2
Foundations of Machine Learning Development and Regression Analysis

This section provides a comprehensive introduction to setting up a robust development environment for machine learning projects, exploring advanced regression techniques, and mastering data preparation.

Time 17m
Lectures 3
Section 3
Advanced Model Development and LLM Integration

This section focuses on building and training XGBoost models for optimal performance while seamlessly integrating Large Language Models (LLMs) into your development workflow. Learn to enhance your machine learning projects by combining advanced regression techniques with the power of LLMs to create

Time 27m
Lectures 3
Section 4
Deployment, Testing, and Optimization

In this section, you'll master the deployment of web applications integrated with machine learning models and LLMs.

Time 12m
Lectures 2
Section 5
Outro

Wrap up your learning journey with a recap of key concepts, next steps, and resources to continue your growth.

Time 02m
Lectures 1

About Tutor

Etibar Aliyev
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Courses 1
Biography

As an AI expert , I specialize in training and fine-tuning LLM-based systems, computer vision systems, and traditional ML models. My career has spanned prominent roles at Volvo, UBS, Credit Suisse, WPP, and Baykar, Turing, where I have successfully consulted international companies on AI implementation and strategy. Currently, I serve as an AI Advisor at AlphaSense, assisting investors in evaluating AI-based products, making informed investment decisions, and understanding the intricacies of AI technologies.

In addition, I am an AI Consultant at AI IXX, where I set up AI-based systems for potential customers, train teams on core AI concepts, test AI products, and provide technical consultations. My key strengths lie in my analytical and practical approach to problem-solving, my ability to develop and optimize complex AI and ML systems, and my commitment to delivering efficient, scalable solutions. I am known for my structured approach, attention to detail, and ability to work independently to achieve precise and impactful results.

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