10 Days: Prompt Engineering, Generative AI and Data Science
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).
Requirements
- Basic Proficiency of Python (Loops, Functions)
- A computer with internet access and the willingness to learn.
Description
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!
Who this course is for:
- Developers and data analysts wanting to deepen their Prompt Engineering and Generative AI skills.
- Professionals seeking to integrate AI-driven solutions into business workflows.
- Computer science students interested in learning about the latest machine learning techniques and how to implement them.
- Anyone curious about combining Python, and OpenAI APIs to build real-world projects.
Instructor
- 4.5 Instructor Rating
- 5,725 Reviews
- 40,010 Students
- 11 Courses
Diogo is a data analytics and business analytics professional with years of experience in the field. He has expertise in various methodologies, including time series forecasting for predicting sales trends, econometrics for analyzing economic data, and machine learning for optimizing marketing campaigns.
His background includes working for a major e-commerce company, where he used these techniques to drive business growth, and collaborating with the United Nations on a Mobile Money project in Lesotho, where he helped increase financial inclusion in the country.
In his courses, Diogo aims to provide practical and applicable knowledge through real-life examples and datasets. For example, he often uses case studies from his own work experiences to illustrate key concepts and demonstrate their relevance in the professional world. His goal is to equip students with the skills and tools necessary to succeed in their own careers in data science.