Udemy

10 Days: Prompt Engineering, Generative AI and Data Science

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  • 3,209 Students
  • Updated 11/2025
4.5
(402 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
14 Hour(s) 33 Minute(s)
Language
English
Taught by
Diogo Alves de Resende
Rating
4.5
(402 Ratings)

Course Overview

10 Days: Prompt Engineering, Generative AI and Data Science

All-in-One Prompt Engineering, Generative AI & Data Science Bootcamp: Build a Portfolio with GenAI & AI Agents Projects

Welcome to the 10 Days of Prompt Engineering, Generative AI, and Data Science Course

Get hands-on with Prompt Engineering, Generative AI, and Data Science in just 10 days.

I’m Diogo, and I’ve structured this course to take you from basics to advanced topics quickly.

We’ll cover live sessions, hands-on labs, and real-world projects—all in 14 hours and 30 minutes of published video content. You’ll also receive lifetime updates so your learning never goes stale.


You will build a portfolio of project on topics like:

  • Prompt Engineering Fundamentals: Understand transformers, attention mechanisms, and how to structure prompts for optimal performance.

  • Generative AI Workflows: Master tools like Google Colab, Jupyter Notebook, LM Studio, and learn how to fine-tune system messages and model parameters.

  • OpenAI API for Text & Images: Integrate the OpenAI API into Python projects, explore parameters for better text generation, and tap into image generation (coming soon).

  • Machine Learning with XGBoost & Random Forest: Explore advanced ML topics, including parameter tuning, SHAP values, and real-world approaches to customer satisfaction modeling.

  • AI Agents with CrewAI: Dive into the next wave of AI automation (coming in Q1 2025).


COURSE BREAKDOWN

Introduction

  • Meet your instructor, download course materials, set up your environment (Google Colab, Jupyter Notebook, RStudio).

  • Preview the core projects we’ll tackle.

Day 1 – Basics of Prompt Engineering

  • Learn about transformers, attention, and chain-of-thought prompting.

  • Experiment with LM Studio to practice explicit instructions, one-shot, and few-shot techniques.

Day 2 – System Messages & LLM Parameters

  • Tokenization, system messages, and parameter tuning.

  • Break the system message (on purpose) to see how LLMs respond, then learn how to guide them back.

Days 3 - Prompt Engineering for better reasoning

  • Proven ways to improve the reasoning in LLMs.

  • Overcoming LLM Hallucinations

Day 4 –Reasoning LLMs - Coming in Q1 2025

  • How Reasoning Works in LLMs

  • Prompt Injection for LLMs like the O1.

  • A hot take on whether LLMs can reason or not.

Day 5 – OpenAI API for Text Generation

  • Integrate the OpenAI API in Python.

  • Adjust temperature, handle few-shot learning, and refine your text generation workflow.

Day 6 – CAPSTONE PROJECT: OpenAI API

  • Build a “Rock-Paper-Scissors” AI.

  • Create new strategies, test temperature parameters, and see how GPT adapts.

Days 7 - OpenAI API for Images

  • Fee images via links and encoded to the Multimodal LLM

  • Add Web-browsing capabilities to the LLM

Day 8 – Random Forest for Customer Satisfaction

  • End-to-end project on gathering actionable insights on customer satisfaction.

  • Guide on how to build a great chart.

Day 9 – XGBoost

  • Discover XGBoost in both Python and R.

  • Handle data processing, parameter tuning, cross-validation, and SHAP values for model interpretation.

Day 10 – AI Agents with CrewAI

  • Coming in Q2 2025—learn to build AI agents that automate tasks and collaborate efficiently.


WHY ENROLL NOW?

  • Lifetime Updates: You get all future course modules automatically, including advanced sections scheduled for 2025.

  • Practical Projects: Apply what you learn in real-world scenarios (Rock-Paper-Scissors AI, XGBoost for customer satisfaction).

  • Structured Curriculum: Each day is designed to build on the previous one, speeding up your learning and progress.

  • Community & Feedback: Engage in discussions, get direct feedback, and influence new content updates.

Ready to accelerate your Prompt Engineering, Generative AI, and Data Science skills?
Sign up now and gain immediate access to all published content, including the future modules. Let’s start building the future of AI together!

Course Content

  • 12 section(s)
  • 147 lecture(s)
  • Section 1 Introduction
  • Section 2 Day 1 - Basics of Prompt Engineering
  • Section 3 Day 2 - Prompt Engineering with System Message and LLM Parameters
  • Section 4 Day 3 - Prompt Engineering for Better Reasoning LLMs
  • Section 5 Day 4 - Reasoning LLMs
  • Section 6 Day 5 - OpenAI API for Text Generation
  • Section 7 Day 6 - CAPSTONE PROJECT: OpenAI API
  • Section 8 Day 7 - OpenAI API for Images
  • Section 9 Day 8 - Random Forest for Customer Satisfaction
  • Section 10 Day 9 - XGBoost
  • Section 11 Day 10 - AI Agents with CrewAI
  • Section 12 What's Next?

What You’ll Learn

  • Design Powerful Prompts for large language models to boost AI accuracy., Master Generative AI Techniques to create text, images, and more with minimal effort., Optimize System Messages for better control and consistency in AI-driven projects., Leverage Data Science Tools like Python, R, and XGBoost for deeper insights., Integrate OpenAI APIs into real-world applications for text generation and analysis., Fine-Tune Model Parameters to maximize performance and personalize AI outputs., Automate Common Tasks with AI, saving time and resources in business workflows., Apply Prompt Engineering to solve cybersecurity and compliance challenges., Develop Hands-On Projects that showcase AI capabilities to stakeholders., Build AI Agents using CrewAI for advanced task automation (coming soon).


Reviews

  • A
    Arun Kannan
    5.0

    good for the new learners.

  • D
    DUSTIN SMITH
    1.0

    This guy is not much better at prompt engineering than a standard jr high student. This course is not worth the time

  • B
    Bindhu Madhavi Kandikonda
    5.0

    good

  • r
    rodney dwy
    3.0

    direction for installing collabratory not ideal. where is this python folder located i downloaded the the heros file but no single python file i have XGBoost - Python but is that the correct file to put into colobaratory?

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